S1-Omni: A Unified Multimodal Reasoning Model for Scientific Understanding, Prediction, and Generation Paper • 2607.15686 • Published 11 days ago • 16
Skip a Layer or Loop It? Learning Program-of-Layers in LLMs Paper • 2606.06574 • Published Jun 4 • 25
OmniVideo-100K: A Dataset for Audio-Visual Reasoning through Structured Scripts and Evidence Chains Paper • 2606.14702 • Published Jun 12 • 31
Text-to-Image Models Need Less from Text Encoders Than You Think Paper • 2606.03715 • Published Jun 2 • 11
World Model Self-Distillation: Training World Models to Solve General Tasks Paper • 2606.12072 • Published Jun 10 • 15
i1: A Simple and Fully Open Recipe for Strong Text-to-Image Models Paper • 2606.11289 • Published Jun 9 • 18
Which Pretraining Paradigm Better Serves Spatial Intelligence? An Empirical Comparison of Vision-Language and Video Generation Models Paper • 2605.28132 • Published May 27 • 25
Negligible in Size, Significant in Effect: On Scale Vectors in Large Language Models Paper • 2605.26895 • Published May 26 • 23
view article Article Towards Speed-of-Light Text Generation with Nemotron-Labs Diffusion Language Models nvidia • May 23 • 35
Continual Harness: Online Adaptation for Self-Improving Foundation Agents Paper • 2605.09998 • Published May 11 • 19
Learning Adaptive Reasoning Paths for Efficient Visual Reasoning Paper • 2604.14568 • Published Apr 16 • 10
From Context to Skills: Can Language Models Learn from Context Skillfully? Paper • 2604.27660 • Published May 3 • 171
Maximal Brain Damage Without Data or Optimization: Disrupting Neural Networks via Sign-Bit Flips Paper • 2502.07408 • Published Apr 16 • 59
MARS: Enabling Autoregressive Models Multi-Token Generation Paper • 2604.07023 • Published Apr 8 • 38