Research Papers
PAST-Bench: New Benchmark Tests Whether Personal AI Agents Really Improve from Experience
Researchers introduce PAST-Bench, a benchmark with 26 scenarios and 204 episodes to isolate whether personal AI agents improve fro...
Hugging Face Paper Proposes Agent-Centric World Proxies to Rethink World Modeling
A new Hugging Face paper introduces Agent-Centric Interactive World Proxies, shifting world modeling from physical state predictio...
Hugging Face Unveils Video-DeepResearch: A Multimodal Agent That Watches Before It Searches
Hugging Face introduces Video-DeepResearch, a framework that extends multimodal agents from static images to continuous video stre...
Hugging Face Researchers Propose PCSD to Boost Agentic RL with Persistent Consistency Self-Distillation
A new method, Persistent Consistency Self-Distillation (PCSD), improves reinforcement learning for LLM agents by providing dense,...
Hugging Face Paper: Knowledge-Geometry Decoupling Boosts Streaming Recommendations by 4-12%
A new paper from Hugging Face introduces Knowledge-Geometry Decoupling (KGD), a method that improves streaming recommendation syst...
MerchantBench: New Benchmark Reveals LLM Agents Struggle with Long-Term E-Commerce Operations
Hugging Face researchers introduce MerchantBench, a 365-day e-commerce simulation that tests LLM agents' long-term coherence. The...
Hunyuan3D-Buffalo 1.0: Unified Multimodal Model for Scalable 3D Generation and Editing
Tencent's Hunyuan3D-Buffalo 1.0 introduces a unified framework for 3D understanding, generation, editing, and part generation, tra...
AURORA-LM: A New Continuous-Latent Diffusion Language Model Outperforms Discrete Token Models
Researchers introduce AURORA-LM, a continuous-latent diffusion language model that preserves high-capacity text latents and learns...
Hugging Face Unveils JoyAI-Video-Edit: Real-Time 720p Video Editing at 30 FPS
JoyAI-Video-Edit, a 16B-parameter autoregressive diffusion model, enables real-time, open-ended video editing without future frame...
LLMs Struggle to Delete Code: New Study Reveals 'Deletion Avoidance' in AI Code Editing
A new study from Hugging Face researchers identifies 'deletion avoidance' in LLM code editing, showing that even top models often...
MemSFT: External Parametric Memory Cuts Alignment Tax in Domain Fine-Tuning
Hugging Face researchers propose MemSFT, a method that uses an external parametric memory to adapt LLMs to specialized domains wit...
Hugging Face Paper: New Framework Transfers Motion Across Morphologically Different Objects
Researchers propose Motion Beyond Morphology (MBM), a two-stage framework that transfers motion between objects with substantially...