Latest stories
Hugging Face Unveils NeoMME: Efficient Multimodal Encoders for Visual Document Retrieval
NeoMME introduces a family of 260M and 800M parameter multimodal encoders that process text and images in a single bidirectional t...
KBMR: Entity-Aligned Retrieval Boosts Knowledge-Based Visual QA
A new Hugging Face paper introduces KBMR, the first MLLM-based retriever for knowledge-based visual question answering, which alig...
S3Gym: New Benchmark Tests Whether LLMs Can Truly Self-Improve
Hugging Face researchers introduce S3Gym, an interactive benchmark that evaluates whether LLM agents can self-test, self-judge, an...
WHALE: A Simple Alternating Recipe for Joint Model-Harness Optimization in AI Agents
Researchers propose WHALE, a method that alternates between updating model weights and searching for better harness code, improvin...
New Benchmark Tests Whether LLMs Can Self-Evolve from Vague Goals
Researchers introduce ASPIRE, a benchmark for self-evolving LLM agents that start with only vague natural-language goals, revealin...
HarnessDev: Benchmarking LLMs on Building and Evolving Their Own Agent Harnesses
A new benchmark shifts evaluation from task outputs to the execution infrastructure agents build themselves, revealing wide variab...
OpenAI Unveils GPT-6 Astra, First Model to Reach 'Critical' Cybersecurity Level
OpenAI has introduced GPT-6 Astra, its most capable broadly deployed model, which is also the first to achieve the Critical cybers...
Pixel Linguist II: New Design Principles for Robust Pixel Text Representation Learning
Hugging Face researchers introduce Pixel Linguist II, a vision encoder that learns to read and compress text directly from pixels....
Hugging Face Researchers Unveil Declarative Attention: Letting LLMs Skip Irrelevant Context
A new paper from Hugging Face introduces Declarative Attention, a protocol that lets language models declare which parts of the co...
Hugging Face Researchers Unveil CoGR: Co-Evolving Generative Retrieval with Reinforcement Learning
A new paper from Hugging Face introduces CoGR, a framework that trains LLMs to generate keywords for both queries and items, enabl...
EarlyEval: Cutting Agent Evaluation Costs with Early Outcome Prediction
Hugging Face researchers introduce EarlyEval, a framework that predicts agent success or failure early in a run, reducing evaluati...
Hugging Face Unveils SolarWM: Open Framework for Long-Horizon Video World Models
SolarWM provides a fully open framework and unified training recipe for building interactive video world models, enabling real-tim...