5 papers
Enhancing LLM Metacognition via Cognitive Pairwise Training
Weitao Li, Hao Zhou, Xuanyu Lei +11
Reinforcement learning with verifiable rewards (RLVR) has become central to LLM reasoning, but its outcome-level rewards can make models more willing to give confident answers when…
UR: Unify RAG and Reasoning through Reinforcement Learning
Weitao Li, Boran Xiang, Xiaolong Wang +5
Large Language Models (LLMs) have shown strong capabilities through two complementary paradigms: Retrieval-Augmented Generation (RAG) for knowledge grounding and Reinforcement Lear…
CodeRepoQA: A Large-scale Benchmark for Software Engineering Question Answering
Ruida Hu, Chao Peng, Jingyi Ren +6
In this work, we introduce CodeRepoQA, a large-scale benchmark specifically designed for evaluating repository-level question-answering capabilities in the field of software engine…
DialogAgent: An Auto-engagement Agent for Code Question Answering Data Production
Xiaoyun Liang, Jingyi Ren, Jiayi Qi +2
Large Language Models (LLMs) have become increasingly integral to enhancing developer productivity, particularly in code generation, comprehension, and repair tasks. However, fine-…
A Real-World Benchmark for Evaluating Fine-Grained Issue Solving Capabilities of Large Language Models
Ruida Hu, Chao Peng, Jingyi Ren +6
Automatically resolving software issues is crucial for software development in practice, impacting the software quality and user experience. The process of resolving real-world iss…