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

    Xinyi Wang, Wanrong Zhu, Michael Saxon, Mark Steyvers, William Yang Wang 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

    Danyang Zhang, Lu Chen, Situo Zhang, Hongshen Xu, Zihan Zhao, Kai Yu 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, Bo Li, Sheng Shen, Jingkang Yang, Chunyuan Li, Kurt Keutzer, Trevor Darrell, Ziwei Liu 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

    Takeshi Kojima, Shixiang (Shane) Gu, Machel Reid, Yutaka Matsuo, Yusuke Iwasawa 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

    Nate Gruver, Marc Finzi, 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

    Zirui Zhao, Wee Sun Lee, David Hsu 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

    Jiawei Wang, Renhe Jiang, Chuang Yang, Zengqing Wu, Makoto Onizuka, Ryosuke Shibasaki, Noboru Koshizuka, Chuan Xiao 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, Logan Walls, Richard L Lewis, Satinder Singh 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, Samuel Müller, Frank Hutter 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.

    Eghbal Hosseini, Evelina Fedorenko 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

    Sanyam Kapoor, Nate Gruver, Manley Roberts, Katherine Collins, Arka Pal, Umang Bhatt, Adrian Weller, Samuel Dooley, Micah Goldblum, 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, Jinman Zhao, Samson Tan, Renato Negrinho, Leonard Lausen, Sheng Zha, George Karypis p41386-41412 from Advances in Neural Information Processing Systems 36
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