On LLM-Based Scientific Inductive Reasoning Beyond Equations
Brian S. Lin, Jiaxin Yuan, Zihan Zhou, Shouli Wang, Shuo Wang, Cunliang Kong, Qi Shi, Yuxuan Li, Liner Yang, Zhiyuan Liu, Maosong Sun
机构
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Dept. of Comp. Sci. & Tech., Institute for AI, BNRist Center, Tsinghua University(计算机科学与技术系,人工智能研究院,BNRist中心,清华大学)
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Jiangsu Collaborative Innovation Center for Language Ability, Jiangsu Normal University(江苏语言能力协同创新中心,江苏师范大学)
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Beijing Language and Culture University(北京语言文化大学)
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Xiamen University(厦门大学)
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Harbin Institute of Technology(哈尔滨工业大学)
Do Large Language Models Truly Grasp Mathematics? An Empirical Exploration From Cognitive Psychology
Wei Xie, Shuoyoucheng Ma, Zhenhua Wang, Enze Wang, Kai Chen, Xiaobing Sun, Baosheng Wang
机构
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College of Computer Science and Technology, National University of Defense Technology(国防科技大学计算机科学与技术学院)
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Institute of High Performance Computing, Agency for Science, Technology and Research (A*STAR)(科学、技术和研究局高性能计算研究所)
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Institute of Information Engineering, Chinese Academy of Sciences(中国科学院信息工程研究所)
CommentsThank you for your attention. This paper was accepted by the CogSci 2025 conference in April and published in August. The location in the proceedings is: https://escholarship.org/uc/item/24x9t7s1
SQLForge: Synthesizing Reliable and Diverse Data to Enhance Text-to-SQL Reasoning in LLMs
Yu Guo, Dong Jin, Shenghao Ye, Shuangwu Chen, Jian Yang, Xiaobin Tan
机构
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University of Science and Technology of China(中国科学技术大学)
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Institute of Artificial Intelligence, Hefei Comprehensive National Science Center(合肥综合性国家科学中心人工智能研究院)
专题命中
逻辑推理
:reasoning(title,abstract);分类 cs.CL
Comments12 pages, 7 figures, accepted to ACL Findings 2025
Journal refSQLForge: Synthesizing Reliable and Diverse Data to Enhance Text-to-SQL Reasoning in LLMs (Guo et al., Findings 2025)
机构
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SKL-MAIS, Institute of Automation, Chinese Academy of Sciences, Beijing, China(中国科学院自动化研究所SKL-MAIS部门,北京)
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School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China(中国科学院大学人工智能学院,北京)
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EACON, Fujian, China(福建EACON机构,中国)
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School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, China(北京科技大学自动化与电气工程学院)
LLaVul: A Multimodal LLM for Interpretable Vulnerability Reasoning about Source Code
Ala Jararweh, Michael Adams, Avinash Sahu, Abdullah Mueen, Afsah Anwar
机构
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Department of Computer Science, The University of New Mexico(计算机科学系,新墨西哥大学)
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Comprehensive Cancer Center, The University of New Mexico(综合癌症中心,新墨西哥大学)
Journal refA. Jararweh, M. Adams, A. Sahu, A. Mueen and A. Anwar, "LLaVul: A Multimodal LLM for Interpretable Vulnerability Reasoning about Source Code," 2025 5th Intelligent Cybersecurity Conference (ICSC), Tampa, FL, USA, 2025, pp. 232-241