EvalResearchBench: Can AI Agents Build Their Own Feedback for Recursive Self-Improvement? Paper • 2610.04184 • Published 10 days ago • 22
🤏 Smol-Data Collection Tried and tested mixes for strong pretraining. Inspired by https://huggingface.co/blog/codelion/optimal-dataset-mixing • 14 items • Updated Mar 2 • 21
When Does Multi-Agent RL Improve LLM Workflows? Workflow, Scale, and Policy-Sharing Tradeoffs Paper • 2605.24202 • Published May 22 • 19
MetaAgent-X : Breaking the Ceiling of Automatic Multi-Agent Systems via End-to-End Reinforcement Learning Paper • 2605.14212 • Published May 14 • 20
Video Generation Models as World Models: Efficient Paradigms, Architectures and Algorithms Paper • 2603.28489 • Published Mar 30 • 28
Density-aware Soft Context Compression with Semi-Dynamic Compression Ratio Paper • 2603.25926 • Published Mar 26 • 6
Qualcomm NPU Collection Latest SOTA models supported on Qualcomm NPU. • 32 items • Updated Mar 2 • 15
Accelerate Parallelizable Reasoning via Parallel Decoding within One Sequence Paper • 2503.20533 • Published Mar 26, 2025 • 12
OpenCSG Chinese Corpus: A Series of High-quality Chinese Datasets for LLM Training Paper • 2501.08197 • Published Jan 14, 2025 • 9
high-quality Chinese training datasets Collection a suite of high-quality Chinese datasets, used for pretraining, fine-tuning or preference alignment. And the models trained on these datasets. • 13 items • Updated May 22, 2025 • 24
Patience Is The Key to Large Language Model Reasoning Paper • 2411.13082 • Published Nov 20, 2024 • 7
Hyper-multi-step: The Truth Behind Difficult Long-context Tasks Paper • 2410.04422 • Published Oct 6, 2024 • 7
MAmmoTH Collection The datasets and models for the MAmmoTH project • 9 items • Updated Apr 19, 2024 • 3