Paper

  • Can Graph Learning Improve Planning in LLM-based Agents?

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Can Graph Learning Improve Planning in LLM-based Agents?

    Wei Chen, Hong Cheng, Jiarui Feng, Dongsheng Li, Caihua Shan, Yifei Shen, Kaitao Song, Siwei Wang, Xixi Wu, Yun Xiong, Bohang Zhang p5338-5383 from Advances in Neural Information Processing Systems 37
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  • Can Graph Neural Networks Expose Training Data Properties? An Efficient Risk Assessment Approach

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Can Graph Neural Networks Expose Training Data Properties? An Efficient Risk Assessment Approach

    Renhong Huang, Mingli Song, Chunping Wang, Jiarong Xu, Yang Yang, Hanyang Yuan p69361-69385 from Advances in Neural Information Processing Systems 37
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  • Can Green Digital Infrastructure Promote Sustainable Business Growth? Evidence from China

    Aussino Academic Publishing House (AAPH)

    Can Green Digital Infrastructure Promote Sustainable Business Growth? Evidence from China

    Long XIN, Yuyao WANG, Chanyuan LIU p313-319 from 13th International Symposium on Project Management (ISPM2025)
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  • Can it Take the Heat: Analyzing the Behavior and Performance of Composite Repair Systems in Elevated Temperature Environments

    Clarion Technical Conferences

    Can it Take the Heat: Analyzing the Behavior and Performance of Composite Repair Systems in Elevated Temperature Environments

    Chris Alexander, Russell Giudici, Travis Greenstreet p461-474 from 37th International Pipeline Pigging and Integrity Management Conference (PPIM 2025)
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  • Can Language Models Learn to Skip Steps?

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Can Language Models Learn to Skip Steps?

    Qipeng Guo, Xiangkun Hu, Cheng Jiayang, Tengxiao Liu, Xipeng Qiu, Yue Zhang, Zheng Zhang p45359-45385 from Advances in Neural Information Processing Systems 37
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  • Can Language Models Perform Robust Reasoning in Chain-of-thought Prompting with Noisy Rationales?

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Can Language Models Perform Robust Reasoning in Chain-of-thought Prompting with Noisy Rationales?

    Bo Han, Yiwen Luo, Rong Tao, Zengmao Wang, Zhanke Zhou, Jianing Zhu p123846-123910 from Advances in Neural Information Processing Systems 37
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  • Can Large Language Model Agents Simulate Human Trust Behavior?

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Can Large Language Model Agents Simulate Human Trust Behavior?

    Adel Bibi, Canyu Chen, James Evans, Bernard Ghanem, Jindong Gu, Ziniu Hu, Feiran Jia, David Jurgens, Shiyang Lai, Guohao Li, Kai Shu, Philip Torr, Chengxing Xie, Ziyu Ye p15674-15729 from Advances in Neural Information Processing Systems 37
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  • Can Large Language Models Analyze Graphs like Professionals? A Benchmark, Datasets and Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Can Large Language Models Analyze Graphs like Professionals? A Benchmark, Datasets and Models

    Weize Chen, Qizhi Chu, Haopeng Li, Ran Li, Xin Li, Zhiyuan Liu, Chen Qian, Chuan Shi, Maosong Sun, Zhaojun Sun, Yiwei Wei, Cheng Yang p141045-141070 from Advances in Neural Information Processing Systems 37
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  • Can large language models explore in-context?

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Can large language models explore in-context?

    Dylan Foster, Keegan Harris, Akshay Krishnamurthy, Aleksandrs Slivkins, Cyril Zhang p120124-120158 from Advances in Neural Information Processing Systems 37
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  • Can Leadership in the Growth Stage Predict the Future Leader of the Organization? Evidence from China Family Panel Study 2020

    Aussino Academic Publishing House (AAPH)

    Can Leadership in the Growth Stage Predict the Future Leader of the Organization? Evidence from China Family Panel Study 2020

    Dong Wu, Xun Ye p1611-1619 from 11th International Symposium on Project Management (ISPM2023)
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  • Can Learned Optimization Make Reinforcement Learning Less Difficult?

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Can Learned Optimization Make Reinforcement Learning Less Difficult?

    Jakob Foerster, Alexander Goldie, Matthew Jackson, Chris Lu, Shimon Whiteson p5454-5497 from Advances in Neural Information Processing Systems 37
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  • Can LLMs Implicitly Learn Numeric Parameter Constraints in Data Science APIs?

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Can LLMs Implicitly Learn Numeric Parameter Constraints in Data Science APIs?

    Zhezhen Cao, Yinlin Deng, Meiziniu Li, Chunqiu Xia, Lingming Zhang p54205-54238 from Advances in Neural Information Processing Systems 37
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