From the 1 of 17 linked papers with an AI index.
17 papers
ParaTempo: Efficient Parallel Reasoning via Temporal Confidence
Xuteng Zhang, Wenhao Zeng, Xiaodong Gu +5
Parallel reasoning improves the accuracy and robustness of large reasoning models by exploring multiple solution paths, but its computational cost grows with reasoning depth and br…
Know Before Fix: QA-Driven Repository Knowledge Acquisition for Software Issue Resolution
Haotian Lin, Silin Chen, Xiaodong Gu +8
The paper introduces ACQUIRE, a QA-driven framework that lets a language model ask targeted questions about a code repository to acquire explicit knowledge before generating patche…
Rethinking Code Complexity Through the Lens of Large Language Models
Chen Xie, Xiaodong Gu, Yuling Shi +1
Code complexity metrics such as cyclomatic complexity have long been used to assess software quality and maintainability. With the rapid advancement of large language models (LLMs)…
In Line with Context: Repository-Level Code Generation via Context Inlining
Chao Hu, Wenhao Zeng, Yuling Shi +2
Repository-level code generation has attracted growing attention in recent years. Unlike function-level code generation, it requires the model to understand the entire repository,…
GlimpRouter: Efficient Collaborative Inference by Glimpsing One Token of Thoughts
Wenhao Zeng, Xuteng Zhang, Yuling Shi +4
Large Reasoning Models (LRMs) achieve remarkable performance by explicitly generating multi-step chains of thought, but this capability incurs substantial inference latency and com…
SWE-QA: Can Language Models Answer Repository-level Code Questions?
Weihan Peng, Yuling Shi, Yuhang Wang +3
Understanding and reasoning about entire software repositories is an essential capability for intelligent software engineering tools. While existing benchmarks such as CoSQA and Co…