Research Papers
Context-Matched Distillation Aligns Teacher Supervision for Autoregressive Video Generation
A new method, Context-Matched Distillation (CMD), aligns teacher supervision with causal generation context in few-step autoregres...
Gambit: Thought-Level Beam Search Boosts Reasoning Efficiency by Up to 68.5%
Hugging Face researchers introduce Gambit, an inference algorithm that uses thought-level beam search to dynamically allocate comp...
LiveAnimate: Real-Time Long-Form Human Animation with 14B Diffusion Transformer
Hugging Face researchers introduce LiveAnimate, the first system to combine real-time streaming with stable long-form human animat...
UniSwap: First Streaming Framework for Joint Audio-Visual Identity Swap in Talking Videos
Hugging Face researchers introduce UniSwap, a unified streaming audio-visual diffusion transformer that simultaneously transfers a...
Massive Activations in Hybrid Linear Attention LLMs: New Study Reveals Pre-Attention Spikes and Inter-Spike Plateaus
A new study from Hugging Face provides the first systematic analysis of massive activations in hybrid linear-attention LLMs, uncov...
PlayWorld Benchmark Puts World Models to the Test with Agent Players
Hugging Face researchers introduce PlayWorld, a benchmark that uses multimodal agent players to evaluate interactive video world m...
Rhetoric Can Hack AI Peer Review: New Study Reveals Structured Sensitivity
A new study from Hugging Face shows that rhetorical framing biases AI review scores in structured ways, with evidence framing and...
Hugging Face Unveils Evoke: An Interactive World Model with Persistent Memory for Endless Video Generation
Evoke, a new interactive world model from Hugging Face, uses external persistent memory and a redesigned long-horizon teacher to e...
Hugging Face Unveils Spatial Memory Agent: Self-Evolving Spatial Reasoning for Frozen VLMs
A new framework from Hugging Face enables frozen vision-language models to improve spatial reasoning through self-evolution, witho...
AutoDesign: Meta-Harness Optimization Boosts Long-Horizon Agentic Design
Hugging Face researchers introduce AutoDesign, a framework that uses a meta-harness optimizer to recursively improve a code agent...
DarwinX: Evolving Agent Harnesses via Natural Selection Boosts Benchmarks
Hugging Face researchers introduce DarwinX, a method that evolves agent harnesses through population selection with frozen models,...
Hugging Face Unveils Intern-S2-Preview: A Scientific Agentic Foundation Model Series
Intern-S2-Preview integrates multimodal pre-training, multi-task reinforcement learning, and memory-augmented extensions to suppor...