Research Papers
Hugging Face Study Unveils 'Physics' of Multimodal Pretraining, Cuts Compute by 95%
A new Hugging Face paper systematically explores multimodal pretraining, revealing four key insights into knowledge flow, modality...
Study: LLMs Fabricate User Profiles in 41.6% of Claims; Self-Monitoring Misleads
A new benchmark, MirageBench, reveals that all 12 tested LLMs over-infer user attributes in 35-49% of claims, and that self-report...
ToolArtist: A Fully Agentic Multimodal Model for Open-World Image Generation
Hugging Face researchers introduce ToolArtist, a unified multimodal model that orchestrates reasoning, external tool use, and nati...
MiniWorld: A Lightweight, Reproducible Framework for Training Video World Models from Scratch
Hugging Face researchers introduce MiniWorld, a reproducible framework for training streaming video world models from scratch on a...
GROVE: A Training-Free Memory Framework for Wearable AI Assistants
Hugging Face researchers introduce GROVE, a training-free framework that grows a single temporally stratified memory from streamin...
TurnSight: A New Framework for Fine-Grained Credit Assignment in Tool-Integrated Reasoning
Hugging Face researchers introduce TurnSight, a turn-level hindsight self-distillation framework that improves reinforcement learn...
Hugging Face Unveils UniWorld-Design: Layer-Native Image Generation
UniWorld-Design redefines image generation by using semantic RGBA layers as atomic units, enabling structured composition and inst...
SkillJack: New Attack Turns Self-Evolving Agents' Learning into Persistent Backdoors
Researchers unveil SkillJack, the first attack targeting the experience-to-skill pipeline of self-evolving agents, implanting mali...
CAPEval: New Benchmark Decouples Caption Quality into Coverage and Precision
Researchers introduce CAPEval, a benchmark that separates caption quality into Coverage and Precision, revealing that Coverage pre...
Any-OPD: New Framework Enables On-Policy Distillation Between Any Flow-Matching Models
Researchers introduce Any-OPD, the first framework for on-policy distillation between arbitrary pairs of latent flow-matching gene...
OmniPack: Training-Free Token Compression Boosts Omni-Modal LLM Efficiency
A new training-free framework, OmniPack, coordinates structural and semantic token compression to cut computational costs in omni-...
Hugging Face Unveils LLaDA MoE v2: Scaling Laws for Diffusion Language Models
A new paper from Hugging Face introduces LLaDA MoE v2, a 30B-A3B diffusion language model trained on 23.5T tokens, and reveals sca...