1 citations · 2 across the 28 of their papers we have counts for
7 papers · 1 filter
CuraWeb: Joint Optimization of Quality, Redundancy, and Diversity for Web-Scale Pretraining Data
Peiguang Li, Yongwei Zhou, Juncheng Diao +12
Open-web corpora curated via highly selective filters, such as FineWeb-Edu and DCLM, constitute the core of LLM pretraining data and have significantly advanced LLM performance. Ho…
HIPIF: Hierarchical Planning and Information Folding for Long-Horizon LLM Agent Learning
Juncheng Diao, Zhicong Lu, Peiguang Li +6
While Large Language Models (LLMs) have demonstrated strong capabilities as autonomous agents across a wide range of tasks, their performance often degrades in multi-turn long-hori…
BAPO: Boundary-Aware Policy Optimization for Reliable Agentic Search
Shiyu Liu, Yongjing Yin, Jianhao Yan +7
RL-based agentic search enables LLMs to solve complex questions via dynamic planning and external search. While this approach significantly enhances accuracy with agent policies op…
Autoformalizer with Tool Feedback
Qi Guo, Jianing Wang, Jianfei Zhang +8
Autoformalization addresses the scarcity of data for Automated Theorem Proving (ATP) by translating mathematical problems from natural language into formal statements. Efforts in r…
AdaR: A Framework for Equipping LLMs with Adaptive Reasoning
Zhejian Lai, Xiang Geng, Zhijun Wang +7
Mathematical reasoning is a primary indicator of large language models (LLMs) intelligence. However, existing LLMs exhibit failures in robustness and generalization. This paper att…
Expanding Reasoning Potential in Foundation Model by Learning Diverse Chains of Thought Patterns
Xuemiao Zhang, Can Ren, Chengying Tu +5
Recent progress in large reasoning models for challenging mathematical reasoning has been driven by reinforcement learning (RL). Incorporating long chain-of-thought (CoT) data duri…