Paper

  • Large Language Models Are Latent Variable Models: Explaining and Finding Good Demonstrations for In-Context Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Large Language Models Are Latent Variable Models: Explaining and Finding Good Demonstrations for In-Context Learning

    Michael Saxon, Mark Steyvers, William Yang Wang, Xinyi Wang, Wanrong Zhu p15614-15638 from Advances in Neural Information Processing Systems 36
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  • Large Language Models Are Semi-Parametric Reinforcement Learning Agents

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Large Language Models Are Semi-Parametric Reinforcement Learning Agents

    Lu Chen, Hongshen Xu, Kai Yu, Danyang Zhang, Situo Zhang, Zihan Zhao p78227-78239 from Advances in Neural Information Processing Systems 36
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  • Large Language Models are Visual Reasoning Coordinators

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Large Language Models are Visual Reasoning Coordinators

    Liangyu Chen, Trevor Darrell, Kurt Keutzer, Bo Li, Chunyuan Li, Ziwei Liu, Sheng Shen, Jingkang Yang p70115-70140 from Advances in Neural Information Processing Systems 36
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  • Large Language Models Are Zero-Shot Reasoners

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Large Language Models Are Zero-Shot Reasoners

    Shixiang Shane Gu, Yusuke Iwasawa, Takeshi Kojima, Yutaka Matsuo, Machel Reid p22199-22213 from Advances in Neural Information Processing Systems 35
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  • Large Language Models Are Zero-Shot Time Series Forecasters

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Large Language Models Are Zero-Shot Time Series Forecasters

    Marc Finzi, Nate Gruver, Shikai Qiu, Andrew Wilson p19622-19635 from Advances in Neural Information Processing Systems 36
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  • Large Language Models as Commonsense Knowledge for Large-Scale Task Planning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Large Language Models as Commonsense Knowledge for Large-Scale Task Planning

    David Hsu, Wee Sun Lee, Zirui Zhao p31967-31987 from Advances in Neural Information Processing Systems 36
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  • Large Language Models as Urban Residents: An LLM Agent Framework for Personal Mobility Generation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Large Language Models as Urban Residents: An LLM Agent Framework for Personal Mobility Generation

    Renhe Jiang, Noboru Koshizuka, Makoto Onizuka, Ryosuke Shibasaki, Jiawei Wang, Zengqing Wu, Chuan Xiao, Chuang Yang p124547-124574 from Advances in Neural Information Processing Systems 37
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  • Large Language Models can Implement Policy Iteration

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Large Language Models can Implement Policy Iteration

    Ethan Brooks, Richard L Lewis, Satinder Singh, Logan Walls p30349-30366 from Advances in Neural Information Processing Systems 36
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  • Large Language Models for Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature Engineering

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Large Language Models for Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature Engineering

    Noah Hollmann, Frank Hutter, Samuel Müller p44753-44775 from Advances in Neural Information Processing Systems 36
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  • Large language models implicitly learn to straighten neural sentence trajectories to construct a predictive representation of natural language.

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Large language models implicitly learn to straighten neural sentence trajectories to construct a predictive representation of natural language.

    Evelina Fedorenko, Eghbal Hosseini p43918-43930 from Advances in Neural Information Processing Systems 36
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  • Large Language Models Must Be Taught to Know What They Don’t Know

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Large Language Models Must Be Taught to Know What They Don’t Know

    Umang Bhatt, Katherine Collins, Samuel Dooley, Micah Goldblum, Nate Gruver, Sanyam Kapoor, Arka Pal, Manley Roberts, Adrian Weller, Andrew Wilson p85932-85972 from Advances in Neural Information Processing Systems 37
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  • Large Language Models of Code Fail at Completing Code with Potential Bugs

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Large Language Models of Code Fail at Completing Code with Potential Bugs

    Tuan Dinh, George Karypis, Leonard Lausen, Renato Negrinho, Samson Tan, Sheng Zha, Jinman Zhao p41386-41412 from Advances in Neural Information Processing Systems 36
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