Caffe Barista: Brewing Caffe with FPGAs in the Training Loop


Caffeinated FPGAs: FPGA Framework For Convolutional Neural Networks


CaiRL: A High-Performance Reinforcement Learning Environment Toolkit


Cain: Automatic Code Generation for Simultaneous Convolutional Kernels on Focal-plane Sensor-processors


Cal or No Cal? -- Real-Time Miscalibration Detection of LiDAR and Camera Sensors


Cal-DETR: Calibrated Detection Transformer


Cal-DPO: Calibrated Direct Preference Optimization for Language Model Alignment


Cal-QL: Calibrated Offline RL Pre-Training for Efficient Online Fine-Tuning


Cal-SFDA: Source-Free Domain-adaptive Semantic Segmentation with Differentiable Expected Calibration Error


CalFAT: Calibrated Federated Adversarial Training with Label Skewness


Calabi-Yau Four/Five/Six-folds as $\mathbb{P}^n_\textbf{w}$ Hypersurfaces: Machine Learning, Approximation, and Generation


Calculating Nash Equilibrium on Quantum Annealers


Calculating Optimistic Likelihoods Using (Geodesically) Convex Optimization


Calculating Point Spread Functions: Methods, Pitfalls and Solutions


Calculating elements of matrix functions using divided differences


Calculating pair-correlations from random particle configurations


Calculating the Expected Value of Sample Information in Practice: Considerations from Three Case Studies


Calculating the divided differences of the exponential function by addition and removal of inputs


Calculation of $c_\mathrm{SW}$ at one-loop order for Brillouin fermions


Calculation of Epidemic First Passage and Peak Time Probability Distributions


Calculation of explicit expressions for the Hopf bifurcation limit cycles in delay-differential equations


Calculus with combinatorial differential forms for fluid flow analysis in porous and fractured media


Calendar Graph Neural Networks for Modeling Time Structures in Spatiotemporal User Behaviors


Calendar-based graphics for visualizing people's daily schedules


Calib-Anything: Zero-training LiDAR-Camera Extrinsic Calibration Method Using Segment Anything


Calib3D: Calibrating Model Preferences for Reliable 3D Scene Understanding


CalibQuant: 1-Bit KV Cache Quantization for Multimodal LLMs


CalibRefine: Deep Learning-Based Online Automatic Targetless LiDAR-Camera Calibration with Iterative and Attention-Driven Post-Refinement


CalibraEval: Calibrating Prediction Distribution to Mitigate Selection Bias in LLMs-as-Judges


Calibrate and Boost Logical Expressiveness of GNN Over Multi-Relational and Temporal Graphs


Calibrate and Debias Layer-wise Sampling for Graph Convolutional Networks


Calibrate your listeners! Robust communication-based training for pragmatic speakers


Calibrate-Extrapolate: Rethinking Prevalence Estimation with Black Box Classifiers


Calibrated Adaptive Probabilistic ODE Solvers


Calibrated Adaptive Teacher for Domain Adaptive Intelligent Fault Diagnosis


Calibrated Computation-Aware Gaussian Processes


Calibrated Domain-Invariant Learning for Highly Generalizable Large Scale Re-Identification


Calibrated Feature Decomposition for Generalizable Person Re-Identification


Calibrated Interpretation: Confidence Estimation in Semantic Parsing


Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data


Calibrated Learning to Defer with One-vs-All Classifiers


Calibrated Model Criticism Using Split Predictive Checks


Calibrated Multiple-Output Quantile Regression with Representation Learning


Calibrated One-class Classification for Unsupervised Time Series Anomaly Detection


Calibrated Optimal Decision Making with Multiple Data Sources and Limited Outcome


Calibrated Out-of-Distribution Detection with a Generic Representation


Calibrated Seq2seq Models for Efficient and Generalizable Ultra-fine Entity Typing


Calibrated Teacher for Sparsely Annotated Object Detection


Calibrated and Partially Calibrated Semi-Generalized Homographies


Calibrated inference: statistical inference that accounts for both sampling uncertainty and distributional uncertainty


Calibrating Bayesian Generative Machine Learning for Bayesiamplification


Calibrating Bayesian Tension Statistics using Neural Ratio Estimation


Calibrating Concepts and Operations: Towards Symbolic Reasoning on Real Images


Calibrating Deep Neural Networks using Focal Loss


Calibrating Energy-based Generative Adversarial Networks


Calibrating Factual Knowledge in Pretrained Language Models


Calibrating Gyrochronology using Kepler Asteroseismic targets


Calibrating Higher-Order Statistics for Few-Shot Class-Incremental Learning with Pre-trained Vision Transformers


Calibrating LLMs with Information-Theoretic Evidential Deep Learning


Calibrating LLMs with Preference Optimization on Thought Trees for Generating Rationale in Science Question Scoring


Calibrating Label Distribution for Class-Imbalanced Barely-Supervised Knee Segmentation


Calibrating Language Models with Adaptive Temperature Scaling


Calibrating Large Language Models Using Their Generations Only


Calibrating Local Volatility Models with Stochastic Drift and Diffusion


Calibrating Long-form Generations from Large Language Models


Calibrating Multi-modal Representations: A Pursuit of Group Robustness without Annotations


Calibrating Neural Simulation-Based Inference with Differentiable Coverage Probability


Calibrating Panoramic Depth Estimation for Practical Localization and Mapping


Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement


Calibrating Reasoning in Language Models with Internal Consistency


Calibrating Transformers via Sparse Gaussian Processes


Calibrating Translation Decoding with Quality Estimation on LLMs


Calibrating Wireless Ray Tracing for Digital Twinning using Local Phase Error Estimates


Calibrating a Deep Neural Network with Its Predecessors


Calibrating and Improving Graph Contrastive Learning


Calibrating cardiac electrophysiology models using latent Gaussian processes on atrial manifolds


Calibrating coordinate system alignment in a scanning transmission electron microscope using a digital twin


Calibrating dimension reduction hyperparameters in the presence of noise


Calibrating doubly-robust estimators with unbalanced treatment assignment


Calibrating general posterior credible regions


Calibrating the Adaptive Learning Rate to Improve Convergence of ADAM


Calibrating the Dice loss to handle neural network overconfidence for biomedical image segmentation


Calibrating the Rigged Lottery: Making All Tickets Reliable


Calibration Attacks: A Comprehensive Study of Adversarial Attacks on Model Confidence


Calibration Error Estimation Using Fuzzy Binning


Calibration Matters: Tackling Maximization Bias in Large-scale Advertising Recommendation Systems


Calibration Meets Explanation: A Simple and Effective Approach for Model Confidence Estimates


Calibration Strategies for Robust Causal Estimation: Theoretical and Empirical Insights on Propensity Score-Based Estimators


Calibration Wizard: A Guidance System for Camera Calibration Based on Modelling Geometric and Corner Uncertainty


Calibration and Option Pricing with Stochastic Volatility and Double Exponential Jumps


Calibration and generalizability of probabilistic models on low-data chemical datasets with DIONYSUS


Calibration by Distribution Matching: Trainable Kernel Calibration Metrics


Calibration errors in interferometric radio polarimetry


Calibration in Machine Learning Uncertainty Quantification: beyond consistency to target adaptivity


Calibration of Continual Learning Models


Calibration of Deep Probabilistic Models with Decoupled Bayesian Neural Networks


Calibration of Google Trends Time Series


Calibration of Multiple Asynchronous Microphone Arrays using Hybrid TDOA


Calibration of Natural Language Understanding Models with Venn--ABERS Predictors


Calibration of Network Confidence for Unsupervised Domain Adaptation Using Estimated Accuracy


Calibration of Neural Networks using Splines


Calibration of P-values for calibration and for deviation of a subpopulation from the full population


Calibration of Spatio-Temporal Forecasts from Citizen Science Urban Air Pollution Data with Sparse Recurrent Neural Networks


Calibration of Time-Series Forecasting: Detecting and Adapting Context-Driven Distribution Shift


Calibration of a SEIR-SEI epidemic model to describe the Zika virus outbreak in Brazil


Calibration of a bumble bee foraging model using Approximate Bayesian Computation


Calibration of an SKA-Low Prototype Station Using Holographic Techniques


Calibration of imperfect geophysical models by multiple satellite interferograms with measurement bias


Calibration of the Halpha Age-Activity relation for M dwarfs


Calibration tests in multi-class classification: A unifying framework


Calibration with confidence: A principled method for panel assessment


Calibration-Disentangled Learning and Relevance-Prioritized Reranking for Calibrated Sequential Recommendation


Calibration-Free Driver Drowsiness Classification based on Manifold-Level Augmentation


Calibration-based Dual Prototypical Contrastive Learning Approach for Domain Generalization Semantic Segmentation


Calibration-free single-frame super-resolution fluorescence microscopy


Calibre: Towards Fair and Accurate Personalized Federated Learning with Self-Supervised Learning


California Crop Yield Benchmark: Combining Satellite Image, Climate, Evapotranspiration, and Soil Data Layers for County-Level Yield Forecasting of Over 70 Crops


California Test System (CATS): A Geographically Accurate Test System based on the California Grid


Call Graph Evolution Analytics over a Version Series of an Evolving Software System


Call Graph Soundness in Android Static Analysis


Call for Customized Conversation: Customized Conversation Grounding Persona and Knowledge


Callback-based Completion Notification using MPI Continuations


Callee: Recovering Call Graphs for Binaries with Transfer and Contrastive Learning


CalliRewrite: Recovering Handwriting Behaviors from Calligraphy Images without Supervision


Calliar: An Online Handwritten Dataset for Arabic Calligraphy


Callipepla: Stream Centric Instruction Set and Mixed Precision for Accelerating Conjugate Gradient Solver


CaloClouds: Fast Geometry-Independent Highly-Granular Calorimeter Simulation


CaloDREAM -- Detector Response Emulation via Attentive flow Matching


Calorimetric Measurement of Multi-TeV Muons via Deep Regression


Calpric: Inclusive and Fine-grain Labeling of Privacy Policies with Crowdsourcing and Active Learning


Caltech Aerial RGB-Thermal Dataset in the Wild


Cam4DOcc: Benchmark for Camera-Only 4D Occupancy Forecasting in Autonomous Driving Applications


CamContextI2V: Context-aware Controllable Video Generation


CamDiff: Camouflage Image Augmentation via Diffusion Model


CamI2V: Camera-Controlled Image-to-Video Diffusion Model


CamJ: Enabling System-Level Energy Modeling and Architectural Exploration for In-Sensor Visual Computing


CamPro: Camera-based Anti-Facial Recognition


CamSAM2: Segment Anything Accurately in Camouflaged Videos


CamVox: A Low-cost and Accurate Lidar-assisted Visual SLAM System


Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs


Camera Adaptation for Fundus-Image-Based CVD Risk Estimation


Camera Based Two Factor Authentication Through Mobile and Wearable Devices


Camera Calibration through Geometric Constraints from Rotation and Projection Matrices


Camera Calibration using a Collimator System


Camera Distortion-aware 3D Human Pose Estimation in Video with Optimization-based Meta-Learning


Camera Frame Misalignment in a Teleoperated Eye-in-Hand Robot: Effects and a Simple Correction Method


Camera Model Identification Using Audio and Visual Content from Videos


Camera Motion Estimation from RGB-D-Inertial Scene Flow


Camera Pose Auto-Encoders for Improving Pose Regression


Camera Pose Matters: Improving Depth Prediction by Mitigating Pose Distribution Bias


Camera Relocalization in Shadow-free Neural Radiance Fields


Camera Style Adaptation for Person Re-identification


Camera clustering for scalable stream-based active distillation


Camera-Based Remote Physiology Sensing for Hundreds of Subjects Across Skin Tones


Camera-Conditioned Stable Feature Generation for Isolated Camera Supervised Person Re-IDentification


Camera-Incremental Object Re-Identification with Identity Knowledge Evolution


Camera-Independent Single Image Depth Estimation from Defocus Blur


Camera-Only 3D Panoptic Scene Completion for Autonomous Driving through Differentiable Object Shapes


Camera-Tracklet-Aware Contrastive Learning for Unsupervised Vehicle Re-Identification


Camera-based 3D Semantic Scene Completion with Sparse Guidance Network


CameraCtrl: Enabling Camera Control for Text-to-Video Generation


CamoFormer: Masked Separable Attention for Camouflaged Object Detection


Camouflaged Object Detection via Context-aware Cross-level Fusion


Camouflaged Object Detection with Feature Grafting and Distractor Aware


Camouflaged Object Segmentation with Distraction Mining


Camouflaged Object Tracking: A Benchmark


Campus3D: A Photogrammetry Point Cloud Benchmark for Hierarchical Understanding of Outdoor Scene


Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time Scaling


Can 3D Vision-Language Models Truly Understand Natural Language?


Can A Gamer Train A Mathematical Reasoning Model?


Can AI Assistants Know What They Don't Know?


Can AI Relate: Testing Large Language Model Response for Mental Health Support


Can AI Validate Science? Benchmarking LLMs for Accurate Scientific Claim $\rightarrow$ Evidence Reasoning


Can AI be enabled to dynamical downscaling? A Latent Diffusion Model to mimic km-scale COSMO5.0\_CLM9 simulations


Can AI weather models predict out-of-distribution gray swan tropical cyclones?


Can AI-Generated Text be Reliably Detected?


Can Active Learning Preemptively Mitigate Fairness Issues?


Can Active Sampling Reduce Causal Confusion in Offline Reinforcement Learning?


Can Adversarial Training Be Manipulated By Non-Robust Features?


Can Adversarial Weight Perturbations Inject Neural Backdoors?


Can An Image Classifier Suffice For Action Recognition?


Can An Old Fashioned Feature Extraction and A Light-weight Model Improve Vulnerability Type Identification Performance?


Can Audio Captions Be Evaluated with Image Caption Metrics?


Can Authorship Attribution Models Distinguish Speakers in Speech Transcripts?


Can BERT Refrain from Forgetting on Sequential Tasks? A Probing Study


Can Bad Teaching Induce Forgetting? Unlearning in Deep Networks using an Incompetent Teacher


Can Biases in ImageNet Models Explain Generalization?


Can Biologically Plausible Temporal Credit Assignment Rules Match BPTT for Neural Similarity? E-prop as an Example


Can Brain Signals Reveal Inner Alignment with Human Languages?


Can CNNs Be More Robust Than Transformers?


Can Capacitive Touch Images Enhance Mobile Keyboard Decoding?


Can ChatGPT Assess Human Personalities? A General Evaluation Framework


Can ChatGPT Detect DeepFakes? A Study of Using Multimodal Large Language Models for Media Forensics


Can ChatGPT Enable ITS? The Case of Mixed Traffic Control via Reinforcement Learning


Can ChatGPT Perform Image Splicing Detection? A Preliminary Study


Can ChatGPT Perform Reasoning Using the IRAC Method in Analyzing Legal Scenarios Like a Lawyer?


Can ChatGPT Understand Too? A Comparative Study on ChatGPT and Fine-tuned BERT


Can ChatGPT replace StackOverflow? A Study on Robustness and Reliability of Large Language Model Code Generation


Can ChatGPT's Responses Boost Traditional Natural Language Processing?


Can Compressed LLMs Truly Act? An Empirical Evaluation of Agentic Capabilities in LLM Compression


Can Connected Autonomous Vehicles really improve mixed traffic efficiency in realistic scenarios?


Can Custom Models Learn In-Context? An Exploration of Hybrid Architecture Performance on In-Context Learning Tasks


Can Deep Learning Outperform Modern Commercial CT Image Reconstruction Methods?


Can Deep Learning Recognize Subtle Human Activities?


Can Deep Learning be Applied to Model-Based Multi-Object Tracking?


Can Deep Neural Networks Predict Data Correlations from Column Names?


Can Deep Reinforcement Learning Solve Erdos-Selfridge-Spencer Games?


Can Differentiable Decision Trees Enable Interpretable Reward Learning from Human Feedback?


Can Diffusion Model Achieve Better Performance in Text Generation? Bridging the Gap between Training and Inference!


Can Diffusion Models Provide Rigorous Uncertainty Quantification for Bayesian Inverse Problems?


Can Embeddings Adequately Represent Medical Terminology? New Large-Scale Medical Term Similarity Datasets Have the Answer!


Can Encrypted Images Still Train Neural Networks? Investigating Image Information and Random Vortex Transformation


Can Evolutionary Sampling Improve Bagged Ensembles?


Can Explanations Be Useful for Calibrating Black Box Models?


Can Forward Gradient Match Backpropagation?


Can Foundation Models Watch, Talk and Guide You Step by Step to Make a Cake?


Can Foundation Models Wrangle Your Data?


Can Frontier LLMs Replace Annotators in Biomedical Text Mining? Analyzing Challenges and Exploring Solutions


Can G4-like Composite Ab Initio Methods Accurately Predict Vibrational Harmonic Frequencies?


Can GNNs Learn Link Heuristics? A Concise Review and Evaluation of Link Prediction Methods


Can GPT-3.5 Generate and Code Discharge Summaries?


Can GPT-4 Perform Neural Architecture Search?


Can GPT-4V(ision) Serve Medical Applications? Case Studies on GPT-4V for Multimodal Medical Diagnosis


Can GPT-O1 Kill All Bugs? An Evaluation of GPT-Family LLMs on QuixBugs


Can Gaia find planets around white dwarfs?


Can Generative LLMs Create Query Variants for Test Collections? An Exploratory Study


Can Generative Pre-trained Language Models Serve as Knowledge Bases for Closed-book QA?


Can Github issues be solved with Tree Of Thoughts?


Can Global XAI Methods Reveal Injected Bias in LLMs? SHAP vs Rule Extraction vs RuleSHAP


Can Graph Neural Networks Count Substructures?


Can Graph Neural Networks Expose Training Data Properties? An Efficient Risk Assessment Approach


Can Graph Neural Networks Go "Online"? An Analysis of Pretraining and Inference


Can Graph Neural Networks Learn Language with Extremely Weak Text Supervision?


Can Graph Reordering Speed Up Graph Neural Network Training? An Experimental Study


Can Human Sex Be Learned Using Only 2D Body Keypoint Estimations?


Can Hybrid Geometric Scattering Networks Help Solve the Maximum Clique Problem?


Can I Trust Your Answer? Visually Grounded Video Question Answering


Can I Trust the Explainer? Verifying Post-hoc Explanatory Methods


Can I introduce my boyfriend to my grandmother? Evaluating Large Language Models Capabilities on Iranian Social Norm Classification


Can I trust my anomaly detection system? A case study based on explainable AI


Can Identifier Splitting Improve Open-Vocabulary Language Model of Code?


Can Information Flows Suggest Targets for Interventions in Neural Circuits?


Can Interpretability Layouts Influence Human Perception of Offensive Sentences?


Can It Edit? Evaluating the Ability of Large Language Models to Follow Code Editing Instructions


Can Kernel Methods Explain How the Data Affects Neural Collapse?


Can Knowledge Editing Really Correct Hallucinations?


Can Knowledge of End-to-End Text-to-Speech Models Improve Neural MIDI-to-Audio Synthesis Systems?


Can LLM "Self-report"?: Evaluating the Validity of Self-report Scales in Measuring Personality Design in LLM-based Chatbots


Can LLM Generate Culturally Relevant Commonsense QA Data? Case Study in Indonesian and Sundanese


Can LLM Graph Reasoning Generalize beyond Pattern Memorization?


Can LLM Substitute Human Labeling? A Case Study of Fine-grained Chinese Address Entity Recognition Dataset for UAV Delivery


Can LLM Watermarks Robustly Prevent Unauthorized Knowledge Distillation?


Can LLM feedback enhance review quality? A randomized study of 20K reviews at ICLR 2025


Can LLM-Augmented autonomous agents cooperate?, An evaluation of their cooperative capabilities through Melting Pot


Can LLM-Driven Hard Negative Sampling Empower Collaborative Filtering? Findings and Potentials


Can LLM-Generated Misinformation Be Detected?


Can LLM-based Financial Investing Strategies Outperform the Market in Long Run?


Can LLMs Alleviate Catastrophic Forgetting in Graph Continual Learning? A Systematic Study


Can LLMs Classify CVEs? Investigating LLMs Capabilities in Computing CVSS Vectors


Can LLMs Convert Graphs to Text-Attributed Graphs?


Can LLMs Correct Physicians, Yet? Investigating Effective Interaction Methods in the Medical Domain


Can LLMs Design Good Questions Based on Context?


Can LLMs Effectively Leverage Graph Structural Information through Prompts, and Why?


Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMs


Can LLMs Generate Tabular Summaries of Science Papers? Rethinking the Evaluation Protocol


Can LLMs Grasp Implicit Cultural Values? Benchmarking LLMs' Metacognitive Cultural Intelligence with CQ-Bench


Can LLMs Master Math? Investigating Large Language Models on Math Stack Exchange


Can LLMs Predict Citation Intent? An Experimental Analysis of In-context Learning and Fine-tuning on Open LLMs


Can LLMs Reason in the Wild with Programs?


Can LLMs Reason with Rules? Logic Scaffolding for Stress-Testing and Improving LLMs


Can LLMs Reliably Simulate Human Learner Actions? A Simulation Authoring Framework for Open-Ended Learning Environments


Can LLMs Separate Instructions From Data? And What Do We Even Mean By That?


Can LLMs Simulate L2-English Dialogue? An Information-Theoretic Analysis of L1-Dependent Biases


Can LLMs Solve longer Math Word Problems Better?


Can LLMs Speak For Diverse People? Tuning LLMs via Debate to Generate Controllable Controversial Statements


Can LLMs Understand Time Series Anomalies?


Can LLMs Understand the Implication of Emphasized Sentences in Dialogue?


Can LLMs be Good Graph Judge for Knowledge Graph Construction?


Can LLMs perform structured graph reasoning?


Can LLMs reason over extended multilingual contexts? Towards long-context evaluation beyond retrieval and haystacks


Can LLMs replace Neil deGrasse Tyson? Evaluating the Reliability of LLMs as Science Communicators


Can LLMs substitute SQL? Comparing Resource Utilization of Querying LLMs versus Traditional Relational Databases


Can LLMs' Tuning Methods Work in Medical Multimodal Domain?


Can LMs Generalize to Future Data? An Empirical Analysis on Text Summarization


Can LMs Learn New Entities from Descriptions? Challenges in Propagating Injected Knowledge


Can Language Beat Numerical Regression? Language-Based Multimodal Trajectory Prediction


Can Language Models Be Tricked by Language Illusions? Easier with Syntax, Harder with Semantics


Can Language Models Employ the Socratic Method? Experiments with Code Debugging


Can Language Models Evaluate Human Written Text? Case Study on Korean Student Writing for Education


Can Language Models Explain Their Own Classification Behavior?


Can Language Models Falsify? Evaluating Algorithmic Reasoning with Counterexample Creation


Can Language Models Follow Multiple Turns of Entangled Instructions?


Can Language Models Laugh at YouTube Short-form Videos?


Can Language Models Learn to Skip Steps?


Can Language Models Make Fun? A Case Study in Chinese Comical Crosstalk


Can Language Models Perform Robust Reasoning in Chain-of-thought Prompting with Noisy Rationales?


Can Language Models Replace Programmers for Coding? REPOCOD Says 'Not Yet'


Can Language Models Solve Olympiad Programming?


Can Language Models Understand Physical Concepts?


Can Language Models be Biomedical Knowledge Bases?


Can Large Language Model Agents Balance Energy Systems?


Can Large Language Model Agents Simulate Human Trust Behavior?


Can Large Language Model Comprehend Ancient Chinese? A Preliminary Test on ACLUE


Can Large Language Models (or Humans) Disentangle Text?


Can Large Language Models Always Solve Easy Problems if They Can Solve Harder Ones?


Can Large Language Models Augment a Biomedical Ontology with missing Concepts and Relations?


Can Large Language Models Automatically Score Proficiency of Written Essays?


Can Large Language Models Capture Dissenting Human Voices?


Can Large Language Models Design Accurate Label Functions?


Can Large Language Models Detect Errors in Long Chain-of-Thought Reasoning?


Can Large Language Models Discern Evidence for Scientific Hypotheses? Case Studies in the Social Sciences


Can Large Language Models Empower Molecular Property Prediction?


Can Large Language Models Follow Concept Annotation Guidelines? A Case Study on Scientific and Financial Domains


Can Large Language Models Generate High-quality Patent Claims?


Can Large Language Models Grasp Event Signals? Exploring Pure Zero-Shot Event-based Recognition


Can Large Language Models Grasp Legal Theories? Enhance Legal Reasoning with Insights from Multi-Agent Collaboration


Can Large Language Models Help Multimodal Language Analysis? MMLA: A Comprehensive Benchmark


Can Large Language Models Identify Authorship?


Can Large Language Models Improve SE Active Learning via Warm-Starts?


Can Large Language Models Improve the Adversarial Robustness of Graph Neural Networks?


Can Large Language Models Infer Causation from Correlation?


Can Large Language Models Learn Independent Causal Mechanisms?


Can Large Language Models Match the Conclusions of Systematic Reviews?


Can Large Language Models Predict the Outcome of Judicial Decisions?


Can Large Language Models Provide Security & Privacy Advice? Measuring the Ability of LLMs to Refute Misconceptions


Can Large Language Models Really Recognize Your Name?


Can Large Language Models Reason about the Region Connection Calculus?


Can Large Language Models Replicate ITS Feedback on Open-Ended Math Questions?


Can Large Language Models Solve Robot Routing?


Can Large Language Models Transform Computational Social Science?


Can Large Language Models Truly Understand Prompts? A Case Study with Negated Prompts


Can Large Language Models Understand Internet Buzzwords Through User-Generated Content


Can Large Language Models Understand Preferences in Personalized Recommendation?


Can Large Language Models Understand Real-World Complex Instructions?


Can Large Language Models Understand You Better? An MBTI Personality Detection Dataset Aligned with Population Traits


Can Large Language Models Unlock Novel Scientific Research Ideas?


Can Large Language Models Write Parallel Code?


Can Large Language Models be Effective Online Opinion Miners?


Can Large Language Models be Trusted for Evaluation? Scalable Meta-Evaluation of LLMs as Evaluators via Agent Debate


Can Large Language Models emulate an inductive Thematic Analysis of semi-structured interviews? An exploration and provocation on the limits of the approach and the model


Can Large Multimodal Models Uncover Deep Semantics Behind Images?


Can Learned Optimization Make Reinforcement Learning Less Difficult?


Can Less be More? When Increasing-to-Balancing Label Noise Rates Considered Beneficial


Can Linguistic Distance help Language Classification? Assessing Hawrami-Zaza and Kurmanji-Sorani


Can Linguistic Knowledge Improve Multimodal Alignment in Vision-Language Pretraining?


Can Long-Context Language Models Subsume Retrieval, RAG, SQL, and More?


Can MLLMs Perform Text-to-Image In-Context Learning?


Can MLLMs Understand the Deep Implication Behind Chinese Images?


Can Machines Generate Personalized Music? A Hybrid Favorite-aware Method for User Preference Music Transfer


Can Machines Read Coding Manuals Yet? -- A Benchmark for Building Better Language Models for Code Understanding


Can Machines Resonate with Humans? Evaluating the Emotional and Empathic Comprehension of LMs


Can Mamba Learn How to Learn? A Comparative Study on In-Context Learning Tasks


Can Mean Field Control (MFC) Approximate Cooperative Multi Agent Reinforcement Learning (MARL) with Non-Uniform Interaction?


Can Millimeter Wave Cellular Systems provide High Reliability and Low Latency? An analysis of the impact of Mobile Blockers


Can Model Fusing Help Transformers in Long Document Classification? An Empirical Study


Can Model Uncertainty Function as a Proxy for Multiple-Choice Question Item Difficulty?


Can Models Help Us Create Better Models? Evaluating LLMs as Data Scientists


Can Modern LLMs Act as Agent Cores in Radiology Environments?


Can Modifying Data Address Graph Domain Adaptation?


Can Multimodal LLMs Perform Time Series Anomaly Detection?


Can NLI Provide Proper Indirect Supervision for Low-resource Biomedical Relation Extraction?


Can Neural Nets Learn the Same Model Twice? Investigating Reproducibility and Double Descent from the Decision Boundary Perspective


Can Neural Network Memorization Be Localized?


Can Neural Networks learn Finite Elements?


Can OOD Object Detectors Learn from Foundation Models?


Can Open-Source LLMs Compete with Commercial Models? Exploring the Few-Shot Performance of Current GPT Models in Biomedical Tasks


Can Orbital Servers Provide Mars-Wide Edge Computing?


Can Out-of-Domain data help to Learn Domain-Specific Prompts for Multimodal Misinformation Detection?


Can Persistent Homology provide an efficient alternative for Evaluation of Knowledge Graph Completion Methods?


Can Physics-Informed Neural Networks beat the Finite Element Method?


Can Poverty Be Reduced by Acting on Discrimination? An Agent-based Model for Policy Making


Can Pre-trained Language Models Interpret Similes as Smart as Human?


Can Pre-trained Networks Detect Familiar Out-of-Distribution Data?


Can Pretrained Language Models (Yet) Reason Deductively?


Can Pretrained Language Models Derive Correct Semantics from Corrupt Subwords under Noise?


Can Pretrained Vision-Language Embeddings Alone Guide Robot Navigation?


Can Prompt Probe Pretrained Language Models? Understanding the Invisible Risks from a Causal View


Can Push-forward Generative Models Fit Multimodal Distributions?


Can Question Generation Debias Question Answering Models? A Case Study on Question-Context Lexical Overlap


Can Question Rewriting Help Conversational Question Answering?


Can RLHF be More Efficient with Imperfect Reward Models? A Policy Coverage Perspective


Can Reasoning LLMs Enhance Clinical Document Classification?


Can Reinforcement Learning Solve Asymmetric Combinatorial-Continuous Zero-Sum Games?


Can Retriever-Augmented Language Models Reason? The Blame Game Between the Retriever and the Language Model


Can SAM Count Anything? An Empirical Study on SAM Counting


Can SAM Segment Anything? When SAM Meets Camouflaged Object Detection


Can Score-Based Generative Modeling Effectively Handle Medical Image Classification?


Can Search-Based Testing with Pareto Optimization Effectively Cover Failure-Revealing Test Inputs?


Can Self Reported Symptoms Predict Daily COVID-19 Cases?


Can Self-Supervised Neural Representations Pre-Trained on Human Speech distinguish Animal Callers?


Can Self-Supervised Representation Learning Methods Withstand Distribution Shifts and Corruptions?


Can Sensitive Information Be Deleted From LLMs? Objectives for Defending Against Extraction Attacks


Can Shuffling Video Benefit Temporal Bias Problem: A Novel Training Framework for Temporal Grounding


Can Single Neurons Solve MNIST? The Computational Power of Biological Dendritic Trees


Can Small Language Models Learn, Unlearn, and Retain Noise Patterns?


Can Synthetic Audio From Generative Foundation Models Assist Audio Recognition and Speech Modeling?


Can Synthetic Data Boost the Training of Deep Acoustic Vehicle Counting Networks?


Can Targeted Clean-Label Poisoning Attacks Generalize?


Can Test-Time Scaling Improve World Foundation Model?


Can Textual Gradient Work in Federated Learning?


Can Textual Semantics Mitigate Sounding Object Segmentation Preference?


Can Transformer Language Models Predict Psychometric Properties?


Can Transformer Models Measure Coherence In Text? Re-Thinking the Shuffle Test


Can Transformer be Too Compositional? Analysing Idiom Processing in Neural Machine Translation


Can Transformers Do Enumerative Geometry?


Can Transformers Learn Full Bayesian Inference in Context?


Can Transformers Learn Optimal Filtering for Unknown Systems?


Can Transformers Reason in Fragments of Natural Language?


Can Tree Based Approaches Surpass Deep Learning in Anomaly Detection? A Benchmarking Study


Can Uncertainty Quantification Enable Better Learning-based Index Tuning?


Can Unconfident LLM Annotations Be Used for Confident Conclusions?


Can Unstructured Pruning Reduce the Depth in Deep Neural Networks?


Can Unsupervised Knowledge Transfer from Social Discussions Help Argument Mining?


Can Users Detect Biases or Factual Errors in Generated Responses in Conversational Information-Seeking?


Can Vehicle Motion Planning Generalize to Realistic Long-tail Scenarios?


Can Vision Language Models Learn from Visual Demonstrations of Ambiguous Spatial Reasoning?


Can Vision-Language Models Evaluate Handwritten Math?


Can Vision-Language Models be a Good Guesser? Exploring VLMs for Times and Location Reasoning


Can Visual Dialogue Models Do Scorekeeping? Exploring How Dialogue Representations Incrementally Encode Shared Knowledge


Can Watermarked LLMs be Identified by Users via Crafted Prompts?


Can Watermarks Survive Translation? On the Cross-lingual Consistency of Text Watermark for Large Language Models


Can We Achieve More with Less? Exploring Data Augmentation for Toxic Comment Classification


Can We Afford The Perfect Prompt? Balancing Cost and Accuracy with the Economical Prompting Index


Can We Break Free from Strong Data Augmentations in Self-Supervised Learning?


Can We Edit LLMs for Long-Tail Biomedical Knowledge?


Can We Effectively Use Smart Contracts to Stipulate Time Constraints?


Can We Enhance Bug Report Quality Using LLMs?: An Empirical Study of LLM-Based Bug Report Generation


Can We Enhance the Quality of Mobile Crowdsensing Data Without Ground Truth?


Can We Faithfully Represent Masked States to Compute Shapley Values on a DNN?


Can We Get Rid of Handcrafted Feature Extractors? SparseViT: Nonsemantics-Centered, Parameter-Efficient Image Manipulation Localization through Spare-Coding Transformer


Can We Learn Communication-Efficient Optimizers?


Can We Leverage Predictive Uncertainty to Detect Dataset Shift and Adversarial Examples in Android Malware Detection?


Can We Mitigate Backdoor Attack Using Adversarial Detection Methods?


Can We Predict Performance of Large Models across Vision-Language Tasks?


Can We Read Speech Beyond the Lips? Rethinking RoI Selection for Deep Visual Speech Recognition


Can We Recycle Our Old Models? An Empirical Evaluation of Model Selection Mechanisms for AIOps Solutions


Can We Talk Models Into Seeing the World Differently?


Can We Transfer Noise Patterns? A Multi-environment Spectrum Analysis Model Using Generated Cases


Can We Trust Recommender System Fairness Evaluation? The Role of Fairness and Relevance


Can We Trust the Performance Evaluation of Uncertainty Estimation Methods in Text Summarization?


Can We Understand Plasticity Through Neural Collapse?


Can We Use Split Learning on 1D CNN Models for Privacy Preserving Training?


Can We Validate Counterfactual Estimations in the Presence of General Network Interference?


Can We Verify Step by Step for Incorrect Answer Detection?


Can Who-Edits-What Predict Edit Survival?


Can Wikipedia Help Offline Reinforcement Learning?


Can Word Sense Distribution Detect Semantic Changes of Words?


Can You Follow Me? Testing Situational Understanding in ChatGPT


Can You Improve My Code? Optimizing Programs with Local Search


Can You Learn Semantics Through Next-Word Prediction? The Case of Entailment


Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with Recurrent Networks


Can You Really Trust Code Copilots? Evaluating Large Language Models from a Code Security Perspective


Can You Spot the Chameleon? Adversarially Camouflaging Images from Co-Salient Object Detection


Can You Trust LLM Judgments? Reliability of LLM-as-a-Judge


Can Your Generative Model Detect Out-of-Distribution Covariate Shift?


Can a Bayesian Oracle Prevent Harm from an Agent?


Can a Confident Prior Replace a Cold Posterior?


Can a Large Language Model Learn Matrix Functions In Context?


Can a MISL Fly? Analysis and Ingredients for Mutual Information Skill Learning


Can a Quantum Support Vector Machine algorithm be utilized to identify Key Biomarkers from Multi-Omics data of COVID19 patients?


Can a Single Tree Outperform an Entire Forest?


Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering


Can a calibration metric be both testable and actionable?


Can a composite heart rate variability biomarker shed new insights about autism spectrum disorder in school-aged children?


Can a large language model be a gaslighter?


Can a negative-mass cosmology explain dark matter and dark energy?


Can a single neuron learn predictive uncertainty?


Can adversarial training learn image captioning ?


Can all variations within the unified mask-based beamformer framework achieve identical peak extraction performance?


Can an Embodied Agent Find Your "Cat-shaped Mug"? LLM-Guided Exploration for Zero-Shot Object Navigation


Can audio-visual integration strengthen robustness under multimodal attacks?


Can bin-wise scaling improve consistency and adaptivity of prediction uncertainty for machine learning regression ?


Can citations tell us about a paper's reproducibility? A case study of machine learning papers


Can counterfactual explanations of AI systems' predictions skew lay users' causal intuitions about the world? If so, can we correct for that?


Can current NLI systems handle German word order? Investigating language model performance on a new German challenge set of minimal pairs


Can deep learning match the efficiency of human visual long-term memory in storing object details?


Can deep neural networks learn process model structure? An assessment framework and analysis


Can denoising diffusion probabilistic models generate realistic astrophysical fields?


Can discrete information extraction prompts generalize across language models?


Can geometric combinatorics improve RNA branching predictions?


Can images help recognize entities? A study of the role of images for Multimodal NER


Can language agents be alternatives to PPO? A Preliminary Empirical Study On OpenAI Gym


Can large language models provide useful feedback on research papers? A large-scale empirical analysis


Can large language models reason about medical questions?


Can lies be faked? Comparing low-stakes and high-stakes deception video datasets from a Machine Learning perspective


Can maker-taker fees prevent algorithmic cooperation in market making?


Can multiple observers detect KS-contextuality?


Can neural networks understand monotonicity reasoning?


Can online attention signals help fact-checkers fact-check?


Can only LLMs do Reasoning?: Potential of Small Language Models in Task Planning


Can open source large language models be used for tumor documentation in Germany? -- An evaluation on urological doctors' notes


Can phones, syllables, and words emerge as side-products of cross-situational audiovisual learning? -- A computational investigation


Can point cloud networks learn statistical shape models of anatomies?


Can political gridlock undermine checks and balances? A lab experiment


Can pre-trained language models generate titles for research papers?


Can pre-trained models assist in dataset distillation?


Can pruning improve certified robustness of neural networks?


Can questions summarize a corpus? Using question generation for characterizing COVID-19 research


Can recurrent neural networks learn process model structure?


Can shallow quantum circuits scramble local noise into global white noise?


Can sparse autoencoders be used to decompose and interpret steering vectors?


Can stable and accurate neural networks be computed? -- On the barriers of deep learning and Smale's 18th problem


Can the COVID-19 epidemic be controlled on the basis of daily test reports?


Can the PageRank centrality be manipulated to obtain any desired ranking?


Can the brain use waves to solve planning problems?


Can the potential benefit of individualizing treatment be assessed using trial summary statistics alone?


Can tides disrupt cold dark matter subhaloes?


Can visual language models resolve textual ambiguity with visual cues? Let visual puns tell you!


Can we Generalize and Distribute Private Representation Learning?


Can we assess research using open scientific knowledge graphs? A case study within the Italian National Scientific Qualification


Can we have it all? On the Trade-off between Spatial and Adversarial Robustness of Neural Networks


Can we infer the presence of Differential Privacy in Deep Learning models' weights? Towards more secure Deep Learning


Can we learn from developer mistakes? Learning to localize and repair real bugs from real bug fixes


Can we obtain significant success in RST discourse parsing by using Large Language Models?


Can we predict the Most Replayed data of video streaming platforms?


Can we predict the impact conditions of meter-sized meteoroids?


Can we trust our energy measurements? A study on the Odroid-XU4


Can you map it to English? The Role of Cross-Lingual Alignment in Multilingual Performance of LLMs


Can you tell? SSNet -- a Sagittal Stratum-inspired Neural Network Framework for Sentiment Analysis


Can't Steal? Cont-Steal! Contrastive Stealing Attacks Against Image Encoders


Can't Touch This: Real-Time, Safe Motion Planning and Control for Manipulators Under Uncertainty


Canadian Adverse Driving Conditions Dataset


Canalization reduces the nonlinearity of regulation in biological networks


Canary in a Coalmine: Better Membership Inference with Ensembled Adversarial Queries


CanaryTrap: Detecting Data Misuse by Third-Party Apps on Online Social Networks


Cancer Metastasis Detection With Neural Conditional Random Field


Cancer Subtype Identification through Integrating Inter and Intra Dataset Relationships in Multi-Omics Data


Cancer Type, Stage and Prognosis Assessment from Pathology Reports using LLMs


Cancer Vaccine Adjuvant Name Recognition from Biomedical Literature using Large Language Models


Cancer-Myth: Evaluating AI Chatbot on Patient Questions with False Presuppositions


Cancer-Net SCa-Synth: An Open Access Synthetically Generated 2D Skin Lesion Dataset for Skin Cancer Classification


CancerNet-SCa: Tailored Deep Neural Network Designs for Detection of Skin Cancer from Dermoscopy Images


Candidate Incentive Distributions: How voting methods shape electoral incentives


Candidate Pseudolabel Learning: Enhancing Vision-Language Models by Prompt Tuning with Unlabeled Data


Candidate Set Re-ranking for Composed Image Retrieval with Dual Multi-modal Encoder


Candidate Soups: Fusing Candidate Results Improves Translation Quality for Non-Autoregressive Translation


Candidate Tidal Disruption Event AT2019fdr Coincident with a High-Energy Neutrino


Cannot See the Forest for the Trees: Aggregating Multiple Viewpoints to Better Classify Objects in Videos


CannyFS: Opportunistically Maximizing I/O Throughput Exploiting the Transactional Nature of Batch-Mode Data Processing


CanonPose: Self-Supervised Monocular 3D Human Pose Estimation in the Wild


Canonical 3D Deformer Maps: Unifying parametric and non-parametric methods for dense weakly-supervised category reconstruction


Canonical Capsules: Self-Supervised Capsules in Canonical Pose


Canonical Decision Diagrams Modulo Theories


Canonical Fields: Self-Supervised Learning of Pose-Canonicalized Neural Fields


Canonical Saliency Maps: Decoding Deep Face Models


Canonical Voting: Towards Robust Oriented Bounding Box Detection in 3D Scenes


Canonical and Noncanonical Hamiltonian Operator Inference


Canonical and Surface Morphological Segmentation for Nguni Languages


Canonical fundamental skew-t linear mixed models


Canonical normalizing flows for manifold learning


CanonicalFusion: Generating Drivable 3D Human Avatars from Multiple Images


Cantilevered, Rectangular Plate Dynamics by Finite Difference Methods


Canvas: End-to-End Kernel Architecture Search in Neural Networks


Canvas: Isolated and Adaptive Swapping for Multi-Applications on Remote Memory


CanvasVAE: Learning to Generate Vector Graphic Documents


Caos: A Reusable Scala Web Animator of Operational Semantics (Extended With Hands-On Tutorial)


Cap2Det: Learning to Amplify Weak Caption Supervision for Object Detection


CapHuman: Capture Your Moments in Parallel Universes


CapS-Adapter: Caption-based MultiModal Adapter in Zero-Shot Classification


CapST: An Enhanced and Lightweight Model Attribution Approach for Synthetic Videos


Capabilities and Skills in Manufacturing: A Survey Over the Last Decade of ETFA


Capabilities for Distributed Authorization in Information-Centric Networking


Capability Instruction Tuning: A New Paradigm for Dynamic LLM Routing


Capability-Based Scaling Laws for LLM Red-Teaming


Capability-based Frameworks for Industrial Robot Skills: a Survey


Capacitance Resistance Model and Recurrent Neural Network for Well Connectivity Estimation : A Comparison Study


Capacity Limits and Multiplexing Gains of MIMO Channels with Transceiver Impairments


Capacity Matters: a Proof-of-Concept for Transformer Memorization on Real-World Data


Capacity and quantum geometry of parametrized quantum circuits


Capacity of Group-invariant Linear Readouts from Equivariant Representations: How Many Objects can be Linearly Classified Under All Possible Views?


Capacity, Bandwidth, and Compositionality in Emergent Language Learning


Capacity-achieving sparse superposition codes with spatially coupled VAMP decoder


CapeX: Category-Agnostic Pose Estimation from Textual Point Explanation


CapillaryNet: An Automated System to Quantify Skin Capillary Density and Red Blood Cell Velocity from Handheld Vital Microscopy


Capital Demand Driven Business Cycles: Mechanism and Effects


Capitalising on Opportunistic Data for Monitoring Species Relative Abundances


Capivara: A Spectral-based Segmentation Method for IFU Data Cubes


CapsDeMM: Capsule network for Detection of Munro's Microabscess in skin biopsy images


CapsFusion: Rethinking Image-Text Data at Scale


CapsGAN: Using Dynamic Routing for Generative Adversarial Networks


Capsule Endoscopy Multi-classification via Gated Attention and Wavelet Transformations


Capsule Network based Contrastive Learning of Unsupervised Visual Representations


Capsule Routing for Sound Event Detection


Capsule networks with non-iterative cluster routing


CapsuleNet: A Deep Learning Model To Classify GI Diseases Using EfficientNet-b7


CapsuleVOS: Semi-Supervised Video Object Segmentation Using Capsule Routing


Caption Anything in Video: Fine-grained Object-centric Captioning via Spatiotemporal Multimodal Prompting


Caption Anything: Interactive Image Description with Diverse Multimodal Controls


Caption Enriched Samples for Improving Hateful Memes Detection


Caption Feature Space Regularization for Audio Captioning


Capturability-based Pattern Generation for Walking with Variable Height


Capture Global Feature Statistics for One-Shot Federated Learning


Capture, Learning, and Synthesis of 3D Speaking Styles


Capturing Actionable Dynamics with Structured Latent Ordinary Differential Equations


Capturing Argument Interaction in Semantic Role Labeling with Capsule Networks


Capturing Between-Tasks Covariance and Similarities Using Multivariate Linear Mixed Models


Capturing Chronology and Extreme Values of Representative Days for Planning of Transmission Lines and Long-Term Energy Storage Systems


Capturing Conversion Rate Fluctuation during Sales Promotions: A Novel Historical Data Reuse Approach


Capturing Delayed Feedback in Conversion Rate Prediction via Elapsed-Time Sampling


Capturing Extreme Events in Turbulence using an Extreme Variational Autoencoder (xVAE)


Capturing Global Informativeness in Open Domain Keyphrase Extraction


Capturing Global Structural Information in Long Document Question Answering with Compressive Graph Selector Network


Capturing Graphs with Hypo-Elliptic Diffusions


Capturing Greater Context for Question Generation


Capturing Humans' Mental Models of AI: An Item Response Theory Approach


Capturing Knowledge of Emerging Entities From Extended Search Snippets


Capturing Logical Structure of Visually Structured Documents with Multimodal Transition Parser


Capturing Long-range Contextual Dependencies with Memory-enhanced Conditional Random Fields


Capturing Minds, Not Just Words: Enhancing Role-Playing Language Models with Personality-Indicative Data


Capturing Nuanced Preferences: Preference-Aligned Distillation for Small Language Models


Capturing Omni-Range Context for Omnidirectional Segmentation


Capturing Perspectives of Crowdsourced Annotators in Subjective Learning Tasks


Capturing Pertinent Symbolic Features for Enhanced Content-Based Misinformation Detection


Capturing Popularity Trends: A Simplistic Non-Personalized Approach for Enhanced Item Recommendation


Capturing Power System Dynamics by Physics-Informed Neural Networks and Optimization


Capturing Semantic Similarity for Entity Linking with Convolutional Neural Networks


Capturing Shape Information with Multi-Scale Topological Loss Terms for 3D Reconstruction


Capturing Smart Contract Design with DCR Graphs


Capturing Smile Dynamics with the Quintic Volatility Model: SPX, Skew-Stickiness Ratio and VIX


Capturing Structure Implicitly from Time-Series having Limited Data


Capturing Temporal Information in a Single Frame: Channel Sampling Strategies for Action Recognition


Capturing Visualization Design Rationale


Capturing and Animation of Body and Clothing from Monocular Video


Capturing complex hand movements and object interactions using machine learning-powered stretchable smart textile gloves


Capturing dynamical correlations using implicit neural representations


Capturing episodic impacts of environmental signals


Capturing heterogeneous time-variation in covariate effects in non-proportional hazard regression models


Capturing patterns of variation unique to a specific dataset


Capturing primordial non-Gaussian signatures in the late Universe by multi-scale extrema of the cosmic log-density field


Capturing the Continuous Complexity of Behavior in C. elegans


Capturing the Macroscopic Behaviour of Molecular Dynamics with Membership Functions


Capturing the Practices, Challenges, and Needs of Transportation Decision-Makers


Capturing the diversity of multilingual societies


Capturing the motion of every joint: 3D human pose and shape estimation with independent tokens


Capturing the temporal constraints of gradual patterns


Car Damage Detection and Patch-to-Patch Self-supervised Image Alignment


Car Object Counting and Position Estimation via Extension of the CLIP-EBC Framework


Car-Studio: Learning Car Radiance Fields from Single-View and Endless In-the-wild Images


CarDD: A New Dataset for Vision-based Car Damage Detection


CarDreamer: Open-Source Learning Platform for World Model based Autonomous Driving


CarMem: Enhancing Long-Term Memory in LLM Voice Assistants through Category-Bounding


Carathéodory Sampling for Stochastic Gradient Descent


Caravan MultiMet: Extending Caravan with Multiple Weather Nowcasts and Forecasts


Caravel: A C++ Framework for the Computation of Multi-Loop Amplitudes with Numerical Unitarity


Carbohydrate NMR chemical shift predictions using E(3) equivariant graph neural networks


Carbon Aware Transformers Through Joint Model-Hardware Optimization


Carbon Explorer: A Holistic Approach for Designing Carbon Aware Datacenters


Carbon Market Simulation with Adaptive Mechanism Design


Carbon Neutral Greenhouse: Economic Model Predictive Control Framework for Education


Carbon monoxide emission lines reveal an inverted atmosphere in the ultra hot Jupiter WASP-33 b consistent with an eastward hot spot


Carbon stars as standard candles: I. The luminosity function of carbon stars in the Magellanic Clouds


Carbon- and Precedence-Aware Scheduling for Data Processing Clusters


Carbon-Oxygen Phase Separation in MESA White Dwarf Models


CarbonScaler: Leveraging Cloud Workload Elasticity for Optimizing Carbon-Efficiency


Carbonic anhydrase II simulated with a universal neural network potential


Carbontracker: Tracking and Predicting the Carbon Footprint of Training Deep Learning Models


CardiSort: a convolutional neural network for cross vendor automated sorting of cardiac MR images


Cardiac Complication Risk Profiling for Cancer Survivors via Multi-View Multi-Task Learning


Cardiac Digital Twins at Scale from MRI: Open Tools and Representative Models from ~55000 UK Biobank Participants


Cardiac MRI Orientation Recognition and Standardization using Deep Neural Networks


Cardiac Reentry Modeled by Spatiotemporal Chaos in a Coupled Map Lattice


Cardiac and Respiratory Self-Gating in Radial MRI using an Adapted Singular Spectrum Analysis (SSA-FARY)


CardiacGen: A Hierarchical Deep Generative Model for Cardiac Signals


Cardinality Constraints in Single-Leader-Multi-Follower games


Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation


Cardinality Estimation in a Virtualized Network Device Using Online Machine Learning


Cardinality Estimation over Knowledge Graphs with Embeddings and Graph Neural Networks


Cardinality constrained submodular maximization for random streams


CardioGenAI: A Machine Learning-Based Framework for Re-Engineering Drugs for Reduced hERG Liability


CardioLearn: A Cloud Deep Learning Service for Cardiac Disease Detection from Electrocardiogram


CardioSpectrum: Comprehensive Myocardium Motion Analysis with 3D Deep Learning and Geometric Insights


Cardioformer: Advancing AI in ECG Analysis with Multi-Granularity Patching and ResNet


Cardiovascular Disease Detection from Multi-View Chest X-rays with BI-Mamba


Cards Against AI: Predicting Humor in a Fill-in-the-blank Party Game


Care3D: An Active 3D Object Detection Dataset of Real Robotic-Care Environments


Career Transitions and Trajectories: A Case Study in Computing


Carefree multiple testing with e-processes


Careful About What App Promotion Ads Recommend! Detecting and Explaining Malware Promotion via App Promotion Graph


Careful What You Wish For: on the Extraction of Adversarially Trained Models


Carefully Blending Adversarial Training, Purification, and Aggregation Improves Adversarial Robustness


Carefully Structured Compression: Efficiently Managing StarCraft II Data


Caregiver Talk Shapes Toddler Vision: A Computational Study of Dyadic Play


Careless Whisper: Speech-to-Text Hallucination Harms


Carleman linearization approach for chemical kinetics integration toward quantum computation


Carlo.jl: A general framework for Monte Carlo simulations in Julia


Carnegie Supernova Project-I and -II: Measurements of $H_0$ using Cepheid, TRGB, and SBF Distance Calibration to Type Ia Supernovae


Carotid artery wall segmentation in ultrasound image sequences using a deep convolutional neural network


Carousel Memory: Rethinking the Design of Episodic Memory for Continual Learning


Carousel Personalization in Music Streaming Apps with Contextual Bandits


Carpe Diem: On the Evaluation of World Knowledge in Lifelong Language Models


Carrying out CNN Channel Pruning in a White Box


Cars Can't Fly up in the Sky: Improving Urban-Scene Segmentation via Height-driven Attention Networks


Cartan images and $\ell$-torsion points of elliptic curves with rational $j$-invariant


Cartan moving frames and the data manifolds


Cartesian atomic moment machine learning interatomic potentials


Cartesian dictionary-based native T1 and T2 mapping of the myocardium


Cartesian lattice counting by the vertical 2-sum


CartesianMoE: Boosting Knowledge Sharing among Experts via Cartesian Product Routing in Mixture-of-Experts


CartiMorph: a framework for automated knee articular cartilage morphometrics


Carton dataset synthesis method for domain shift based on foreground texture decoupling and replacement


Cartoon Explanations of Image Classifiers


Cartoon Face Recognition: A Benchmark Dataset


CarveMix: A Simple Data Augmentation Method for Brain Lesion Segmentation


Carving Out the Inner Edge of the Period Ratio Distribution through Giant Impacts


Carving out the low surface brightness universe with NoiseChisel


CasCIFF: A Cross-Domain Information Fusion Framework Tailored for Cascade Prediction in Social Networks


CasCalib: Cascaded Calibration for Motion Capture from Sparse Unsynchronized Cameras


CasDyF-Net: Image Dehazing via Cascaded Dynamic Filters


CasEE: A Joint Learning Framework with Cascade Decoding for Overlapping Event Extraction


CasFusionNet: A Cascaded Network for Point Cloud Semantic Scene Completion by Dense Feature Fusion


CasNet: Investigating Channel Robustness for Speech Separation


CasSeqGCN: Combining Network Structure and Temporal Sequence to Predict Information Cascades


CasTGAN: Cascaded Generative Adversarial Network for Realistic Tabular Data Synthesis


CascadER: Cross-Modal Cascading for Knowledge Graph Link Prediction


Cascade Adversarial Machine Learning Regularized with a Unified Embedding


Cascade Attention Guided Residue Learning GAN for Cross-Modal Translation


Cascade Bagging for Accuracy Prediction with Few Training Samples


Cascade Graph Neural Networks for RGB-D Salient Object Detection


Cascade Network with Guided Loss and Hybrid Attention for Finding Good Correspondences


Cascade Prompt Learning for Vision-Language Model Adaptation


Cascade R-CNN: High Quality Object Detection and Instance Segmentation


Cascade RPN: Delving into High-Quality Region Proposal Network with Adaptive Convolution


Cascade Residual Learning: A Two-stage Convolutional Neural Network for Stereo Matching


Cascade Reward Sampling for Efficient Decoding-Time Alignment


Cascade Speculative Drafting for Even Faster LLM Inference


Cascade Transformers for End-to-End Person Search


Cascade-BGNN: Toward Efficient Self-supervised Representation Learning on Large-scale Bipartite Graphs


Cascade-CLIP: Cascaded Vision-Language Embeddings Alignment for Zero-Shot Semantic Segmentation


Cascade-DETR: Delving into High-Quality Universal Object Detection


CascadeBERT: Accelerating Inference of Pre-trained Language Models via Calibrated Complete Models Cascade


CascadePSP: Toward Class-Agnostic and Very High-Resolution Segmentation via Global and Local Refinement


CascadeV-Det: Cascade Point Voting for 3D Object Detection


Cascaded Classifier for Pareto-Optimal Accuracy-Cost Trade-Off Using off-the-Shelf ANNs


Cascaded Cross MLP-Mixer GANs for Cross-View Image Translation


Cascaded Cross-Modal Transformer for Audio-Textual Classification


Cascaded Debiasing: Studying the Cumulative Effect of Multiple Fairness-Enhancing Interventions


Cascaded Deep Video Deblurring Using Temporal Sharpness Prior


Cascaded Diffusion Models for 2D and 3D Microscopy Image Synthesis to Enhance Cell Segmentation


Cascaded Human-Object Interaction Recognition


Cascaded LSTMs based Deep Reinforcement Learning for Goal-driven Dialogue


Cascaded Local Implicit Transformer for Arbitrary-Scale Super-Resolution


Cascaded Multi-Scale Attention for Enhanced Multi-Scale Feature Extraction and Interaction with Low-Resolution Images


Cascaded Mutual Modulation for Visual Reasoning


Cascaded Parallel Filtering for Memory-Efficient Image-Based Localization


Cascaded Partial Decoder for Fast and Accurate Salient Object Detection


Cascaded Revision Network for Novel Object Captioning


Cascaded Span Extraction and Response Generation for Document-Grounded Dialog


Cascaded Sparse Feature Propagation Network for Interactive Segmentation


Cascaded Temporal Updating Network for Efficient Video Super-Resolution


Cascaded Text Generation with Markov Transformers


Cascaded Zoom-in Detector for High Resolution Aerial Images


Cascaded deep monocular 3D human pose estimation with evolutionary training data


Cascaded multitask U-Net using topological loss for vessel segmentation and centerline extraction


CascadedGaze: Efficiency in Global Context Extraction for Image Restoration


Cascading Adaptors to Leverage English Data to Improve Performance of Question Answering for Low-Resource Languages


Cascading Biases: Investigating the Effect of Heuristic Annotation Strategies on Data and Models


Cascading CMA-ES Instances for Generating Input-diverse Solution Batches


Cascading Feature Extraction for Fast Point Cloud Registration


Cascading Large Language Models for Salient Event Graph Generation


Cascading Losses in Reinsurance Networks


Cascading Residual Graph Convolutional Network for Multi-Behavior Recommendation


Cascading and Direct Approaches to Unsupervised Constituency Parsing on Spoken Sentences


Cascading upper bounds for triangle soup Pompeiu-Hausdorff distance


Case Study: Neural Network Malware Detection Verification for Feature and Image Datasets


Case Study: Using AI-Assisted Code Generation In Mobile Teams


Case studies of development of verified programs with Dafny for accessibility assessment


Case studies on pre-eruptive X-class flares using R-value in the lower solar atmosphere


Case study: Mapping potential informal settlements areas in Tegucigalpa with machine learning to plan ground survey


Case-Base Neural Networks: survival analysis with time-varying, higher-order interactions


Case-Based Inverse Reinforcement Learning Using Temporal Coherence


Case-Based or Rule-Based: How Do Transformers Do the Math?


Case-Enhanced Vision Transformer: Improving Explanations of Image Similarity with a ViT-based Similarity Metric


Case-level Breast Cancer Prediction for Real Hospital Settings


Case2Code: Learning Inductive Reasoning with Synthetic Data


CaseGen: A Benchmark for Multi-Stage Legal Case Documents Generation


CaseLink: Inductive Graph Learning for Legal Case Retrieval


Caseformer: Pre-training for Legal Case Retrieval Based on Inter-Case Distinctions


Casevo: A Cognitive Agents and Social Evolution Simulator


Cash or Comfort? How LLMs Value Your Inconvenience


Casper: Debugging Null Dereferences with Dynamic Causality Traces


Cast vote records: A database of ballots from the 2020 U.S. Election


Casting Multiple Shadows: High-Dimensional Interactive Data Visualisation with Tours and Embeddings


Castor: Competing shapelets for fast and accurate time series classification


CasualHDRSplat: Robust High Dynamic Range 3D Gaussian Splatting from Casually Captured Videos


CatBoost model with synthetic features in application to loan risk assessment of small businesses


CatBoostLSS -- An extension of CatBoost to probabilistic forecasting


CatGAN: Category-aware Generative Adversarial Networks with Hierarchical Evolutionary Learning for Category Text Generation


CatGCN: Graph Convolutional Networks with Categorical Node Features


CatIss: An Intelligent Tool for Categorizing Issues Reports using Transformers


CatMADS: Mesh Adaptive Direct Search for constrained blackbox optimization with categorical variables


CatNet: Class Incremental 3D ConvNets for Lifelong Egocentric Gesture Recognition


CatV2TON: Taming Diffusion Transformers for Vision-Based Virtual Try-On with Temporal Concatenation


CatVRNN: Generating Category Texts via Multi-task Learning


CatVTON: Concatenation Is All You Need for Virtual Try-On with Diffusion Models


CataNet: Predicting remaining cataract surgery duration


Catala: A Programming Language for the Law


Catalog of Formalized Application Integration Patterns


Catalog of X-ray Detected Be Stars (XDBS)


Catalog of quasars from the Kilo-Degree Survey Data Release 3


Cataloging Dependency Injection Anti-Patterns in Software Systems


Catalogue of model star clusters in the Milky Way and M31 galaxies


Catalogue of phonon modes in several cuprate high-temperature superconductors from density functional theory


Catalyst Property Prediction with CatBERTa: Unveiling Feature Exploration Strategies through Large Language Models


Catalytic entanglement transformations with noisy hardware


Catapults in SGD: spikes in the training loss and their impact on generalization through feature learning


CataractBot: An LLM-Powered Expert-in-the-Loop Chatbot for Cataract Patients


Catastrophe Risk in a Stochastic Multi-Population Mortality Model


Catastrophic Cyber Capabilities Benchmark (3CB): Robustly Evaluating LLM Agent Cyber Offense Capabilities


Catastrophic Failure of LLM Unlearning via Quantization


Catastrophic Goodhart: regularizing RLHF with KL divergence does not mitigate heavy-tailed reward misspecification


Catastrophic Interference in Reinforcement Learning: A Solution Based on Context Division and Knowledge Distillation


Catastrophic overfitting can be induced with discriminative non-robust features


Catastrophic-risk-aware reinforcement learning with extreme-value-theory-based policy gradients


Catch Causal Signals from Edges for Label Imbalance in Graph Classification


Catch Me If You Hear Me: Audio-Visual Navigation in Complex Unmapped Environments with Moving Sounds


Catch Me if You Search: When Contextual Web Search Results Affect the Detection of Hallucinations


Catch Missing Details: Image Reconstruction with Frequency Augmented Variational Autoencoder


Catch me if you can: Signal localization with knockoff e-values


Catch-A-Waveform: Learning to Generate Audio from a Single Short Example


Catch-Up Distillation: You Only Need to Train Once for Accelerating Sampling


Catching Attention with Automatic Pull Quote Selection


Catching Both Gray and Black Swans: Open-set Supervised Anomaly Detection


Catching Stray Balls: Football, fandom, and the impact on digital discourse


Catching the wisps: Stellar mass-loss limits from low-frequency radio observations


CateNorm: Categorical Normalization for Robust Medical Image Segmentation


Categorical Co-Frequency Analysis: Clustering Diagnosis Codes to Predict Hospital Readmissions


Categorical Data Integration for Computational Science


Categorical Depth Distribution Network for Monocular 3D Object Detection


Categorical Distributions of Maximum Entropy under Marginal Constraints


Categorical Flow Matching on Statistical Manifolds


Categorical Metadata Representation for Customized Text Classification


Categorical Normalizing Flows via Continuous Transformations


Categorical Perception: A Groundwork for Deep Learning


Categorical Relation-Preserving Contrastive Knowledge Distillation for Medical Image Classification


Categorical Stochastic Processes and Likelihood


Categorical data clustering: 25 years beyond K-modes


Categorization of two-loop Feynman diagrams in the $\mathcal O(α^2)$ correction to $e^+e^- \rightarrow ZH$


Categorizing models using Self-Organizing Maps: an application to modified gravity theories probed by cosmic shear


Categorizing the Content of GitHub README Files


Category Adaptation Meets Projected Distillation in Generalized Continual Category Discovery


Category Anchor-Guided Unsupervised Domain Adaptation for Semantic Segmentation


Category Aware Explainable Conversational Recommendation


Category Contrast for Unsupervised Domain Adaptation in Visual Tasks


Category Feature Transformer for Semantic Segmentation


Category Guided Attention Network for Brain Tumor Segmentation in MRI


Category Query Learning for Human-Object Interaction Classification


Category Theory for Quantum Natural Language Processing


Category-Extensible Out-of-Distribution Detection via Hierarchical Context Descriptions


Category-Level 6D Object Pose and Size Estimation using Self-Supervised Deep Prior Deformation Networks


Category-Level Pose Retrieval with Contrastive Features Learnt with Occlusion Augmentation


Category-Prompt Refined Feature Learning for Long-Tailed Multi-Label Image Classification


Category-level Neural Field for Reconstruction of Partially Observed Objects in Indoor Environment


Category-orthogonal object features guide information processing in recurrent neural networks trained for object categorization


Caterpillar: A Pure-MLP Architecture with Shifted-Pillars-Concatenation


Cats and Captions vs. Creators and the Clock: Comparing Multimodal Content to Context in Predicting Relative Popularity


Cats vs. Spectre: An Axiomatic Approach to Modeling Speculative Execution Attacks


Cattle Identification Using Muzzle Images and Deep Learning Techniques


CattleEyeView: A Multi-task Top-down View Cattle Dataset for Smarter Precision Livestock Farming


CattleFace-RGBT: RGB-T Cattle Facial Landmark Benchmark


Catwalk: A Unified Language Model Evaluation Framework for Many Datasets


Catwoman: A transit modelling Python package for asymmetric light curves


Cauchy Random Features for Operator Learning in Sobolev Space


Cauchy noise loss for stochastic optimization of random matrix models via free deterministic equivalents


Cauchy-Schwarz Divergence Information Bottleneck for Regression


Caught in the Web of Words: Do LLMs Fall for Spin in Medical Literature?


CausAdv: A Causal-based Framework for Detecting Adversarial Examples


CausE: Towards Causal Knowledge Graph Embedding


CausIL: Causal Graph for Instance Level Microservice Data


CausNet : Generational orderings based search for optimal Bayesian networks via dynamic programming with parent set constraints


CausPref: Causal Preference Learning for Out-of-Distribution Recommendation


Causal Abstraction Learning based on the Semantic Embedding Principle


Causal Action Influence Aware Counterfactual Data Augmentation


Causal Agent based on Large Language Model


Causal Analysis of Customer Churn Using Deep Learning


Causal Analysis of Syntactic Agreement Mechanisms in Neural Language Models


Causal Analysis of Syntactic Agreement Neurons in Multilingual Language Models


Causal Attention for Interpretable and Generalizable Graph Classification


Causal Attention for Unbiased Visual Recognition


Causal Bandits for Linear Structural Equation Models


Causal Campbell-Goodhart's law and Reinforcement Learning


Causal Cartographer: From Mapping to Reasoning Over Counterfactual Worlds


Causal Change Point Detection and Localization


Causal Context Adjustment Loss for Learned Image Compression


Causal Context Connects Counterfactual Fairness to Robust Prediction and Group Fairness


Causal Contextual Bandits with Adaptive Context


Causal Customer Churn Analysis with Low-rank Tensor Block Hazard Model


Causal Deepsets for Off-policy Evaluation under Spatial or Spatio-temporal Interferences


Causal Diffusion Autoencoders: Toward Counterfactual Generation via Diffusion Probabilistic Models


Causal Diffusion Transformers for Generative Modeling


Causal Direction of Data Collection Matters: Implications of Causal and Anticausal Learning for NLP


Causal Discovery and Classification Using Lempel-Ziv Complexity


Causal Discovery and Knowledge Injection for Contestable Neural Networks (with Appendices)


Causal Discovery and Optimal Experimental Design for Genome-Scale Biological Network Recovery


Causal Discovery from Time-Series Data with Short-Term Invariance-Based Convolutional Neural Networks


Causal Discovery in Astrophysics: Unraveling Supermassive Black Hole and Galaxy Coevolution


Causal Discovery in Heterogeneous Environments Under the Sparse Mechanism Shift Hypothesis


Causal Discovery in Knowledge Graphs by Exploiting Asymmetric Properties of Non-Gaussian Distributions


Causal Discovery in Linear Latent Variable Models Subject to Measurement Error


Causal Discovery in Linear Structural Causal Models with Deterministic Relations


Causal Discovery in Semi-Stationary Time Series


Causal Discovery in the Presence of Missing Data


Causal Discovery of Linear Non-Gaussian Causal Models with Unobserved Confounding


Causal Discovery of Macroeconomic State-Space Models


Causal Discovery over High-Dimensional Structured Hypothesis Spaces with Causal Graph Partitioning


Causal Discovery under Off-Target Interventions


Causal Discovery using Compression-Complexity Measures


Causal Discovery using Model Invariance through Knockoff Interventions


Causal Discovery via Bayesian Optimization


Causal Discovery with Fewer Conditional Independence Tests


Causal Discovery with Language Models as Imperfect Experts


Causal Discovery with Unobserved Confounding and non-Gaussian Data


Causal Disentangled Recommendation Against User Preference Shifts


Causal Domain Adaptation with Copula Entropy based Conditional Independence Test


Causal Dynamics Learning for Task-Independent State Abstraction


Causal Effect Estimation Using Random Hyperplane Tessellations


Causal Effect Estimation and Optimal Dose Suggestions in Mobile Health


Causal Effect Estimation from Observational and Interventional Data Through Matrix Weighted Linear Estimators


Causal Effect Estimation using Variational Information Bottleneck


Causal Effect Identification in LiNGAM Models with Latent Confounders


Causal Effect Identification in lvLiNGAM from Higher-Order Cumulants


Causal Effect Identification with Context-specific Independence Relations of Control Variables


Causal Estimation of Exposure Shifts with Neural Networks


Causal Estimation of Memorisation Profiles


Causal Explanations for Image Classifiers


Causal Explanations for Sequential Decision-Making in Multi-Agent Systems


Causal Feature Learning in the Social Sciences


Causal Forecasting:Generalization Bounds for Autoregressive Models


Causal Graphical Models for Vision-Language Compositional Understanding


Causal Graphs Meet Thoughts: Enhancing Complex Reasoning in Graph-Augmented LLMs


Causal Image Modeling for Efficient Visual Understanding


Causal Imitation Learning under Temporally Correlated Noise


Causal Imitative Model for Autonomous Driving


Causal Imputation via Synthetic Interventions


Causal Incremental Graph Convolution for Recommender System Retraining


Causal Inference Through the Structural Causal Marginal Problem


Causal Inference With Outcome-Dependent Missingness And Self-Censoring


Causal Inference and Mechanism Clustering of A Mixture of Additive Noise Models


Causal Inference for Continuous Multiple Time Point Interventions


Causal Inference for Knowledge Graph based Recommendation


Causal Inference for Qualitative Outcomes


Causal Inference from Observational Studies with Clustered Interference


Causal Inference from Text: Unveiling Interactions between Variables


Causal Inference in Counterbalanced Within-Subjects Designs


Causal Inference in Genetic Trio Studies


Causal Inference in Possibly Nonlinear Factor Models


Causal Inference in Recommender Systems: A Survey and Future Directions


Causal Inference in high dimensions: A marriage between Bayesian modeling and good frequentist properties


Causal Inference on Missing Exposure via Robust Estimation


Causal Inference under Network Interference with Noise


Causal Inference via Style Transfer for Out-of-distribution Generalisation


Causal Inference with Noisy and Missing Covariates via Matrix Factorization


Causal Inference with the Instrumental Variable Approach and Bayesian Nonparametric Machine Learning


Causal Inference-Based Root Cause Analysis for Online Service Systems with Intervention Recognition


Causal Influence Detection for Improving Efficiency in Reinforcement Learning


Causal Interaction Trees: Tree-Based Subgroup Identification for Observational Data


Causal Intersectionality and Dual Form of Gradient Descent for Multimodal Analysis: a Case Study on Hateful Memes


Causal Intervention for Leveraging Popularity Bias in Recommendation


Causal Knowledge Guided Societal Event Forecasting


Causal Language Modeling Can Elicit Search and Reasoning Capabilities on Logic Puzzles


Causal Learner: A Toolbox for Causal Structure and Markov Blanket Learning


Causal Learning in Biomedical Applications: A Benchmark


Causal Learning via Manifold Regularization


Causal Machine Learning for Cost-Effective Allocation of Development Aid


Causal Mediation Analysis for Interpreting Neural NLP: The Case of Gender Bias


Causal Mediation Analysis with Multiple Mediators: A Simulation Approach


Causal Meta-Mediation Analysis: Inferring Dose-Response Function From Summary Statistics of Many Randomized Experiments


Causal Mode Multiplexer: A Novel Framework for Unbiased Multispectral Pedestrian Detection


Causal Modeling for Fairness in Dynamical Systems


Causal Modeling of Twitter Activity During COVID-19


Causal Modeling with Stationary Diffusions


Causal Modelling of Heavy-Tailed Variables and Confounders with Application to River Flow


Causal Navigation by Continuous-time Neural Networks


Causal Network Motifs: Identifying Heterogeneous Spillover Effects in A/B Tests


Causal Optimal Transport of Abstractions


Causal Parrots: Large Language Models May Talk Causality But Are Not Causal


Causal Patterns: Extraction of multiple causal relationships by Mixture of Probabilistic Partial Canonical Correlation Analysis


Causal Prompt Calibration Guided Segment Anything Model for Open-Vocabulary Multi-Entity Segmentation


Causal Proxy Models for Concept-Based Model Explanations


Causal Queries from Observational Data in Biological Systems via Bayesian Networks: An Empirical Study in Small Networks


Causal Question Answering with Reinforcement Learning


Causal Reasoning and Large Language Models: Opening a New Frontier for Causality


Causal Reasoning of Entities and Events in Procedural Texts


Causal Recurrent Variational Autoencoder for Medical Time Series Generation


Causal Reinforcement Learning using Observational and Interventional Data


Causal Representation Learning Made Identifiable by Grouping of Observational Variables


Causal Representation Learning in Temporal Data via Single-Parent Decoding


Causal Responsibility Attribution for Human-AI Collaboration


Causal Rule Ensemble: Interpretable Discovery and Inference of Heterogeneous Treatment Effects


Causal SAR ATR with Limited Data via Dual Invariance


Causal Shapley Values: Exploiting Causal Knowledge to Explain Individual Predictions of Complex Models


Causal State Distillation for Explainable Reinforcement Learning


Causal Structure Learning Supervised by Large Language Model


Causal Structure Learning by Using Intersection of Markov Blankets


Causal Structure Representation Learning of Confounders in Latent Space for Recommendation


Causal Support: Modeling Causal Inferences with Visualizations


Causal Temporal Representation Learning with Nonstationary Sparse Transition


Causal Transformer for Fusion and Pose Estimation in Deep Visual Inertial Odometry


Causal Transportability for Visual Recognition


Causal Triplet: An Open Challenge for Intervention-centric Causal Representation Learning


Causal Walk: Debiasing Multi-Hop Fact Verification with Front-Door Adjustment


Causal affect prediction model using a facial image sequence


Causal and Local Correlations Based Network for Multivariate Time Series Classification


Causal conditional hidden Markov model for multimodal traffic prediction


Causal coupling inference from multivariate time series based on ordinal partition transition networks


Causal de Finetti: On the Identification of Invariant Causal Structure in Exchangeable Data


Causal discovery for observational sciences using supervised machine learning


Causal discovery for time series with constraint-based model and PMIME measure


Causal discovery under a confounder blanket


Causal effect of chemotherapy received dose intensity on survival outcome: a retrospective study in osteosarcoma


Causal effect on a target population: a sensitivity analysis to handle missing covariates


Causal effects on non-terminal event time with application to antibiotic usage and future resistance


Causal fault localisation in dataflow systems


Causal health impacts of power plant emission controls under modeled and uncertain physical process interference


Causal inference and machine learning approaches for evaluation of the health impacts of large-scale air quality regulations


Causal inference for multiple continuous exposures via the multivariate generalized propensity score


Causal inference for process understanding in Earth sciences


Causal inference for social network data


Causal inference from treatment-control studies having an additional factor with unknown assignment mechanism


Causal inference in survival analysis using longitudinal observational data: Sequential trials and marginal structural models


Causal inference in the context of an error prone exposure: air pollution and mortality


Causal inference targeting a concentration index for studies of health inequalities


Causal inference with limited resources: proportionally-representative interventions


Causal inference with multiple versions of treatment and application to personalized medicine


Causal integration of chemical structures improves representations of microscopy images for morphological profiling


Causal interventions expose implicit situation models for commonsense language understanding


Causal isotonic calibration for heterogeneous treatment effects


Causal mediation analysis: From simple to more robust strategies for estimation of marginal natural (in)direct effects


Causal prediction models for medication safety monitoring: The diagnosis of vancomycin-induced acute kidney injury


Causal predictive inference and target trial emulation


Causal quartets: Different ways to attain the same average treatment effect


Causal schema induction for knowledge discovery


Causal structure based root cause analysis of outliers


Causal structure learning from time series: Large regression coefficients may predict causal links better in practice than small p-values


Causal structure learning with momentum: Sampling distributions over Markov Equivalence Classes of DAGs


Causal survival analysis under competing risks using longitudinal modified treatment policies


Causal thinking for decision making on Electronic Health Records: why and how


Causal, stable first-order viscous relativistic hydrodynamics with ideal gas microphysics


Causal-DFQ: Causality Guided Data-free Network Quantization


Causal-Guided Active Learning for Debiasing Large Language Models


Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models


Causal-StoNet: Causal Inference for High-Dimensional Complex Data


Causal-aware Large Language Models: Enhancing Decision-Making Through Learning, Adapting and Acting


Causal-aware Safe Policy Improvement for Task-oriented dialogue


Causal-discovery-based root-cause analysis and its application in time-series prediction error diagnosis


CausalAdv: Adversarial Robustness through the Lens of Causality


CausalAgents: A Robustness Benchmark for Motion Forecasting using Causal Relationships


CausalBench: A Large-scale Benchmark for Network Inference from Single-cell Perturbation Data


CausalCLIPSeg: Unlocking CLIP's Potential in Referring Medical Image Segmentation with Causal Intervention


CausalChaos! Dataset for Comprehensive Causal Action Question Answering Over Longer Causal Chains Grounded in Dynamic Visual Scenes


CausalCite: A Causal Formulation of Paper Citations


CausalConceptTS: Causal Attributions for Time Series Classification using High Fidelity Diffusion Models


CausalDeepCENT: Deep Learning for Causal Prediction of Individual Event Times


CausalDialogue: Modeling Utterance-level Causality in Conversations


CausalDiff: Causality-Inspired Disentanglement via Diffusion Model for Adversarial Defense


CausalDynamics: A large-scale benchmark for structural discovery of dynamical causal models


CausalEGM: a general causal inference framework by encoding generative modeling


CausalFormer: An Interpretable Transformer for Temporal Causal Discovery


CausalGAN: Learning Causal Implicit Generative Models with Adversarial Training


CausalGPS: An R Package for Causal Inference With Continuous Exposures


CausalGraph2LLM: Evaluating LLMs for Causal Queries


CausalGym: Benchmarking causal interpretability methods on linguistic tasks


CausalLM is not optimal for in-context learning


CausalLP: Learning causal relations with weighted knowledge graph link prediction


CausalMed: Causality-Based Personalized Medication Recommendation Centered on Patient health state


CausalMob: Causal Human Mobility Prediction with LLMs-derived Human Intentions toward Public Events


CausalPFN: Amortized Causal Effect Estimation via In-Context Learning


CausalPlayground: Addressing Data-Generation Requirements in Cutting-Edge Causality Research


CausalRec: Causal Inference for Visual Debiasing in Visually-Aware Recommendation


CausalSR: Structural Causal Model-Driven Super-Resolution with Counterfactual Inference


CausalSim: A Causal Framework for Unbiased Trace-Driven Simulation


CausalVQA: A Physically Grounded Causal Reasoning Benchmark for Video Models


Causality Analysis for Evaluating the Security of Large Language Models


Causality Detection using Multiple Annotation Decisions


Causality Extraction based on Self-Attentive BiLSTM-CRF with Transferred Embeddings


Causality Guided Disentanglement for Cross-Platform Hate Speech Detection


Causality Inspired Representation Learning for Domain Generalization


Causality Pursuit from Heterogeneous Environments via Neural Adversarial Invariance Learning


Causality analysis of large-scale structures in the flow around a wall-mounted square cylinder


Causality and Independence Enhancement for Biased Node Classification


Causality and independence in perfectly adapted dynamical systems


Causality for Inherently Explainable Transformers: CAT-XPLAIN


Causality in Configurable Software Systems


Causality indices for bivariate time series data: a comparative review of performance


Causality-Aware Local Interpretable Model-Agnostic Explanations


Causality-Enhanced Behavior Sequence Modeling in LLMs for Personalized Recommendation


Causality-Inspired Fair Representation Learning for Multimodal Recommendation


Causality-aware Concept Extraction based on Knowledge-guided Prompting


Causality-based Counterfactual Explanation for Classification Models


Causality-based Feature Selection: Methods and Evaluations


Causality-inspired Single-source Domain Generalization for Medical Image Segmentation


Causality-oriented robustness: exploiting general noise interventions


Causally Aware Generative Adversarial Networks for Light Pollution Control


Causally Denoise Word Embeddings Using Half-Sibling Regression


Causally Disentangled Generative Variational AutoEncoder


Causally Inspired Regularization Enables Domain General Representations


Causally Sound Priors for Binary Experiments


Causally Steered Diffusion for Automated Video Counterfactual Generation


Causally Testing Gender Bias in LLMs: A Case Study on Occupational Bias


Causally motivated Shortcut Removal Using Auxiliary Labels


Causally-informed deep learning to improve climate models and projections


Causalvis: Visualizations for Causal Inference


Caution for the Environment: Multimodal Agents are Susceptible to Environmental Distractions


Cautious Bayesian Optimization for Efficient and Scalable Policy Search


Cautious Calibration in Binary Classification


Cautious Optimizers: Improving Training with One Line of Code


Cautiously-Optimistic Knowledge Sharing for Cooperative Multi-Agent Reinforcement Learning


Caveats for information bottleneck in deterministic scenarios


Caviar: An E-graph Based TRS for Automatic Code Optimization


Cavity Light-Matter Entanglement through Quantum Fluctuations


Cavity engineering of Hubbard $U$ via phonon polaritons


Cavity-modified unimolecular dissociation reactions via intramolecular vibrational energy redistribution


CaΣoS: A nonlinear sum-of-squares optimization suite


CeBed: A Benchmark for Deep Data-Driven OFDM Channel Estimation


CeCNN: Copula-enhanced convolutional neural networks in joint prediction of refraction error and axial length based on ultra-widefield fundus images


CeFlow: A Robust and Efficient Counterfactual Explanation Framework for Tabular Data using Normalizing Flows


CeViT: Copula-Enhanced Vision Transformer in multi-task learning and bi-group image covariates with an application to myopia screening


CebuaNER: A New Baseline Cebuano Named Entity Recognition Model


Cedille: A large autoregressive French language model


Cefdet: Cognitive Effectiveness Network Based on Fuzzy Inference for Action Detection


Celcomen: spatial causal disentanglement for single-cell and tissue perturbation modeling


Celeb-DF: A Large-scale Challenging Dataset for DeepFake Forensics


CelebV-Text: A Large-Scale Facial Text-Video Dataset


Celeganser: Automated Analysis of Nematode Morphology and Age


Celestial: Virtual Software System Testbeds for the LEO Edge


Cell Detection from Imperfect Annotation by Pseudo Label Selection Using P-classification


Cell Detection in Domain Shift Problem Using Pseudo-Cell-Position Heatmap


Cell Morphology-Guided Small Molecule Generation with GFlowNets


Cell Segmentation and Tracking using CNN-Based Distance Predictions and a Graph-Based Matching Strategy


Cell Tracking according to Biological Needs -- Strong Mitosis-aware Multi-Hypothesis Tracker with Aleatoric Uncertainty


Cell Tracking via Proposal Generation and Selection


Cell Tracking-by-detection using Elliptical Bounding Boxes


Cell abundance aware deep learning for cell detection on highly imbalanced pathological data


Cell identification in whole-brain multiview images of neural activation


Cell image classification: a comparative overview


Cell reprogramming design by transfer learning of functional transcriptional networks


Cell tracking for live-cell microscopy using an activity-prioritized assignment strategy


Cell-Free ISAC MIMO Systems: Joint Sensing and Communication Beamforming


Cell-Free Massive MIMO Meets OTFS Modulation


Cell-Free Massive MIMO for URLLC: A Finite-Blocklength Analysis


Cell-Free Massive MIMO in O-RAN: Energy-Aware Joint Orchestration of Cloud, Fronthaul, and Radio Resources


Cell-Free Multi-User MIMO Equalization via In-Context Learning


Cell-o1: Training LLMs to Solve Single-Cell Reasoning Puzzles with Reinforcement Learning


Cell-to-cell information at a feedback-induced bifurcation point


Cell-veto Monte Carlo algorithm for long-range systems


CellCLAT: Preserving Topology and Trimming Redundancy in Self-Supervised Cellular Contrastive Learning


CellGAN: Conditional Cervical Cell Synthesis for Augmenting Cytopathological Image Classification


CellMix: A General Instance Relationship based Method for Data Augmentation Towards Pathology Image Classification


CellSeg1: Robust Cell Segmentation with One Training Image


CellTypeAgent: Trustworthy cell type annotation with Large Language Models


CellVTA: Enhancing Vision Foundation Models for Accurate Cell Segmentation and Classification


CellViT++: Energy-Efficient and Adaptive Cell Segmentation and Classification Using Foundation Models


CellViT: Vision Transformers for Precise Cell Segmentation and Classification


Celler:A Genomic Language Model for Long-Tailed Single-Cell Annotation


Cellpose+, a morphological analysis tool for feature extraction of stained cell images


Cellular Traffic Prediction via Byzantine-robust Asynchronous Federated Learning


Cellular memory enhances bacterial chemotactic navigation in rugged environments


Cellular reproduction number, generation time and growth rate differ between human- and avian-adapted influenza strains


Cellular-X: An LLM-empowered Cellular Agent for Efficient Base Station Operations


Cellular-enabled Collaborative Robots Planning and Operations for Search-and-Rescue Scenarios


Cellulyzer - Automated analysis and interactive visualization/simulation of select cellular processes


Cellwise outlier detection in heterogeneous populations


CemiFace: Center-based Semi-hard Synthetic Face Generation for Face Recognition


Censor-aware Semi-supervised Learning for Survival Time Prediction from Medical Images


Censored Quantile Regression Neural Networks for Distribution-Free Survival Analysis


Censored Sampling of Diffusion Models Using 3 Minutes of Human Feedback


Censored Semi-Bandits: A Framework for Resource Allocation with Censored Feedback


Censoring chemical data to mitigate dual use risk


Census TopDown: The Impacts of Differential Privacy on Redistricting


Centaur: a foundation model of human cognition


Centennial-scale variability of the Atlantic Meridional Circulation in CMIP6 models shaped by Arctic-North Atlantic interactions and sea ice biases


Center Focusing Network for Real-Time LiDAR Panoptic Segmentation


Center Smoothing: Certified Robustness for Networks with Structured Outputs


Center-Based Relaxed Learning Against Membership Inference Attacks


Center-Outward R-Estimation for Semiparametric VARMA Models


Center-aware Residual Anomaly Synthesis for Multi-class Industrial Anomaly Detection


CenterArt: Joint Shape Reconstruction and 6-DoF Grasp Estimation of Articulated Objects


CenterCLIP: Token Clustering for Efficient Text-Video Retrieval


CenterDisks: Real-time instance segmentation with disk covering


CenterFormer: Center-based Transformer for 3D Object Detection


CenterNet3D: An Anchor Free Object Detector for Point Cloud


CenterPoly: real-time instance segmentation using bounding polygons


Centered Masking for Language-Image Pre-Training


Centered Partition Process: Informative Priors for Clustering


Centered plug-in estimation of Wasserstein distances


Centerline Boundary Dice Loss for Vascular Segmentation


Central Limit Theorems via Analytic Combinatorics in Several Variables


Central Server Free Federated Learning over Single-sided Trust Social Networks


Central Similarity Quantization for Efficient Image and Video Retrieval


Central object segmentation by deep learning for fruits and other roundish objects


Central schemes for networked scalar conservation laws


Centrality Graph Shift Operators for Graph Neural Networks


Centrality and Consistency: Two-Stage Clean Samples Identification for Learning with Instance-Dependent Noisy Labels


Centrality of nodes in Federated Byzantine Agreement Systems


Centralized Cooperative Exploration Policy for Continuous Control Tasks


Centralized Model and Exploration Policy for Multi-Agent RL


Centralized Reward Agent for Knowledge Sharing and Transfer in Multi-Task Reinforcement Learning


Centralized Selection with Preferences in the Presence of Biases


Centralized Training with Hybrid Execution in Multi-Agent Reinforcement Learning


Centralized and Decentralized Control in Modular Robots and Their Effect on Morphology


Centralized and Federated Heart Disease Classification Models Using UCI Dataset and their Shapley-value Based Interpretability


Centralized and distributed online learning for sparse time-varying optimization


Centralized control for multi-agent RL in a complex Real-Time-Strategy game


Centre Stage: Centricity-based Audio-Visual Temporal Action Detection


CentripetalNet: Pursuing High-quality Keypoint Pairs for Object Detection


CentripetalText: An Efficient Text Instance Representation for Scene Text Detection


Centroid Based Concept Learning for RGB-D Indoor Scene Classification


Centroid Distance Distillation for Effective Rehearsal in Continual Learning


Centroid Distance Keypoint Detector for Colored Point Clouds


Centroid-UNet: Detecting Centroids in Aerial Images


Centroid-aware feature recalibration for cancer grading in pathology images


Centroid-centered Modeling for Efficient Vision Transformer Pre-training


Centroids Matching: an efficient Continual Learning approach operating in the embedding space


Cephalometric Landmark Detection across Ages with Prototypical Network


Cephalometric Landmark Detection by AttentiveFeature Pyramid Fusion and Regression-Voting


Cerbero-7B: A Leap Forward in Language-Specific LLMs Through Enhanced Chat Corpus Generation and Evaluation


Cerberus Transformer: Joint Semantic, Affordance and Attribute Parsing


Cerberus: A Formal Approach to Secure and Efficient Enclave Memory Sharing


Cerberus: Low-Drift Visual-Inertial-Leg Odometry For Agile Locomotion


CerberusDet: Unified Multi-Dataset Object Detection


Cerebro: Static Subsuming Mutant Selection


CerraData-4MM: A multimodal benchmark dataset on Cerrado for land use and land cover classification


Cert-SSB: Toward Certified Sample-Specific Backdoor Defense


CertDW: Towards Certified Dataset Ownership Verification via Conformal Prediction


CertViT: Certified Robustness of Pre-Trained Vision Transformers


Certain properties and applications of shallow bosonic circuits


CertainSync: Rateless Set Reconciliation with Certainty


Certainty Equivalent Perception-Based Control


Certainty Volume Prediction for Unsupervised Domain Adaptation


Certifiable Black-Box Attacks with Randomized Adversarial Examples: Breaking Defenses with Provable Confidence


Certifiable Machine Unlearning for Linear Models


Certifiable Robustness to Graph Perturbations


Certifiably Byzantine-Robust Federated Conformal Prediction


Certificates of quantum many-body properties assisted by machine learning


Certification of Deep Learning Models for Medical Image Segmentation


Certification of Iterative Predictions in Bayesian Neural Networks


Certification of Speaker Recognition Models to Additive Perturbations


Certification of genuine multipartite entanglement in spin ensembles with measurements of total angular momentum


Certification of non-classicality in all links of a photonic star network without assuming quantum mechanics


Certified Adversarial Robustness Within Multiple Perturbation Bounds


Certified Adversarial Robustness with Additive Noise


Certified Approximate Reachability (CARe): Formal Error Bounds on Deep Learning of Reachable Sets


Certified Compilation of Financial Contracts


Certified Data Removal Under High-dimensional Settings


Certified Data Removal from Machine Learning Models


Certified Defense on the Fairness of Graph Neural Networks


Certified Defense to Image Transformations via Randomized Smoothing


Certified Defenses against Adversarial Examples


Certified Error Control of Candidate Set Pruning for Two-Stage Relevance Ranking


Certified Graph View Maintenance with Regular Datalog


Certified Knowledge Compilation with Application to Formally Verified Model Counting