5 papers · 1 filter
Kernel-Smith: A Unified Recipe for Evolutionary Kernel Optimization
He Du, Qiming Ge, Jiakai Hu +18
We present Kernel-Smith, a framework for high-performance GPU kernel and operator generation that combines a stable evaluation-driven evolutionary agent with an evolution-oriented…
How to Fine-Tune a Reasoning Model? A Teacher-Student Cooperation Framework to Synthesize Student-Consistent SFT Data
Zixian Huang, Kaichen Yang, Xu Huang +6
A widely adopted strategy for model enhancement is to use synthetic data generated by a stronger model for supervised fine-tuning (SFT). However, for emerging reasoning models like…
SWE-Fixer: Training Open-Source LLMs for Effective and Efficient GitHub Issue Resolution
Chengxing Xie, Bowen Li, Chang Gao +4
Large Language Models (LLMs) have demonstrated remarkable proficiency across a variety of complex tasks. One significant application of LLMs is in tackling software engineering cha…
Large Language Models Meet Symbolic Provers for Logical Reasoning Evaluation
Chengwen Qi, Ren Ma, Bowen Li +5
First-order logic (FOL) reasoning, which involves sequential deduction, is pivotal for intelligent systems and serves as a valuable task for evaluating reasoning capabilities, part…
Prompting Large Language Models to Tackle the Full Software Development Lifecycle: A Case Study
Bowen Li, Wenhan Wu, Ziwei Tang +13
Recent advancements in large language models (LLMs) have significantly enhanced their coding capabilities. However, existing benchmarks predominantly focused on simplified or isola…