Research Papers
Scaling Laws Suggest Encoder-Free Multimodal Models Can Catch Up at 10^22 FLOPs
A new study compares scaling laws for encoder-free and encoder-based multimodal large language models, finding that the visual pri...
VisionHOPE Introduces Self-Modifying Visual Backbones
A new paper proposes VisionHOPE, a general-purpose visual backbone built on Nested Learning's self-referential construction, where...
CoWindow Attention Cuts Long-Context Training Latency Up to 8.6x While Matching Full Attention
Hugging Face researchers introduce CoWA, a structured attention design in which heads collectively cover the full causal history i...
Hugging Face Paper: MALA Lets Attention Allocate Its Own Compute
A new fused attention primitive, MassAlloc Attention (MALA), preserves full causal QK scoring but uses normalized softmax contribu...
Duplex-MPE Benchmark Tests When Voice Assistants Should Stay Silent in Group Chats
Hugging Face researchers introduce Duplex-MPE, a 2,000-scenario benchmark that evaluates full-duplex speech assistants on selectiv...
Xiaomi's GAGAR Rewrites Code Agent RL by Grading Solution Quality, Not Just Test Passes
A new framework from Xiaomi and Hugging Face uses a groupwise agentic grader to redistribute advantage among test-passing trajecto...
Hugging Face Paper: Domain-Normalized Distillation Fixes Multi-Teacher Imbalance
A new paper introduces Domain-Normalized Multi-Teacher On-Policy Distillation (DN-MOPD), which rescales each specialist's feedback...
Hugging Face Paper: Post-Training Leaves 'Behavioral Shadows' That Transfer Skills
A new paper introduces Active Taskless Distillation (ATD), showing that a language model can learn coding, science, and reasoning...
CompoWorld Composes Reusable Services to Train More Capable General Agents
A new Hugging Face paper introduces Compositional Environment Scaling, which builds agent training tasks by composing a library of...
EmbodiedMemory-Bench Tests Whether Embodied Agents Can Actually Remember
A new benchmark of 2,554 interactive episodes probes four memory weaknesses in long-horizon embodied agents, alongside a structure...
Adaptive Looped Transformers Boost Test-Time Scaling by 53% on AIME
A new paper introduces TaH2, a post-training method that directs extra loop iterations only to tokens that benefit from them, impr...
Hugging Face Paper Proposes 'Physical Coding' to Make Robots Learn Like Software Agents
A new paper argues that representing robot task state and execution as code can overcome the brittleness of vision-language-action...