代码大模型 / AI 编程

AR$^2$: Adversarial Reinforcement Learning for Abstract Reasoning in Large Language Models

Cheng-Kai Yeh, Hsing-Wang Lee, Chung-Hung Kuo, Hen-Hsen Huang

机构 * Department of Mathematical Sciences National Chengchi University Taipei Taiwan（数学科学系 国立政治大学 台北 台湾） ； Department of Computer Science National Chengchi University Taipei Taiwan（计算机科学系 国立政治大学 台北 台湾） ； Institute of Information Science Academia Sinica Taipei Taiwan（信息科学研究所 中国学术院 台北 台湾） ； National Chengchi University（国立政治大学） 纠错

专题命中 代码生成 ：code generation(abstract)；分类 cs.CL、cs.AI、cs.LG

Comments 7 pages, accepted by CIKM 2025 as a short paper

A Comprehensive Survey on Trustworthiness in Reasoning with Large Language Models

Yanbo Wang, Yongcan Yu, Jian Liang, Ran He

机构 * School of Artificial Intelligence, University of Chinese Academy of Sciences（人工智能学院，中国科学院大学） ； NLPR & MAIS, Institute of Automation, Chinese Academy of Sciences（神经语言处理与机器智能中心，中国科学院自动化研究所） 纠错

专题命中 代码生成 ：code generation(abstract)；分类 cs.CL、cs.AI

Comments 38 pages. This survey considers papers published up to June 30, 2025. Work in progress

Synthesizing Optimal Object Selection Predicates for Image Editing using Lattices

Yang He, Xiaoyu Liu, Yuepeng Wang

专题命中 代码生成 ：program synthesis(abstract)；分类 cs.PL

Comments We identified issues in the experimental results and want to withdraw the paper. We plan to submit an updated version once these issues have been resolved