2 citations · 2 across the 15 of their papers we have counts for
7 papers · 1 filter
MaP: A Unified Framework for Reliable Evaluation of Pre-training Dynamics
Jiapeng Wang, Changxin Tian, Kunlong Chen +5
Reliable evaluation is fundamental to the progress of Large Language Models (LLMs), yet the evaluation process during pre-training is plagued by significant instability that obscur…
CodeChemist: Test-Time Scaling for Low-Resource Code Generation via Functional Knowledge Transfer
Kaixin Wang, Tianlin Li, Xiaoyu Zhang +6
Code Large Language Models (CodeLLMs) have been widely adopted for Natural Language to Programming Language code generation, powering applications with large user bases. Their perf…
Arrows of Math Reasoning Data Synthesis for Large Language Models: Diversity, Complexity and Correctness
Sirui Chen, Changxin Tian, Binbin Hu +4
Enhancing the mathematical reasoning of large language models (LLMs) demands high-quality training data, yet conventional methods face critical challenges in scalability, cost, and…
WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training
Changxin Tian, Jiapeng Wang, Qian Zhao +7
Recent advances in learning rate (LR) scheduling have demonstrated the effectiveness of decay-free approaches that eliminate the traditional decay phase while maintaining competiti…
Enhancing Cross-task Transfer of Large Language Models via Activation Steering
Xinyu Tang, Zhihao Lv, Xiaoxue Cheng +5
Large language models (LLMs) have shown impressive abilities in leveraging pretrained knowledge through prompting, but they often struggle with unseen tasks, particularly in data-s…
POLYRAG: Integrating Polyviews into Retrieval-Augmented Generation for Medical Applications
Chunjing Gan, Dan Yang, Binbin Hu +5
Large language models (LLMs) have become a disruptive force in the industry, introducing unprecedented capabilities in natural language processing, logical reasoning and so on. How…
RV-Syn: Rational and Verifiable Mathematical Reasoning Data Synthesis based on Structured Function Library
Jiapeng Wang, Jinhao Jiang, Zhiqiang Zhang +2
The advancement of reasoning capabilities in Large Language Models (LLMs) requires substantial amounts of high-quality reasoning data, particularly in mathematics. Existing data sy…