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Original Paper: https://arxiv.org/abs/2311.18231 By: Hantao Yao, Rui Zhang, Changsheng Xu Abstract: Prompt tuning represents a valuable technique for adapting pre-trained visual-language models (VLM) to various downstream tasks. Recent advancements in CoOp-based methods propose a set of learnable domain-shared or image-conditional textual tokens to facilitate the
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Original Paper: https://arxiv.org/abs/2305.13860 By: Yi Liu, Gelei Deng, Zhengzi Xu, Yuekang Li, Yaowen Zheng, Ying Zhang, Lida Zhao, Tianwei Zhang, Kailong Wang, Yang Liu Abstract: Large Language Models (LLMs), like ChatGPT, have demonstrated vast potential but also introduce challenges related to content constraints and potential
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Original Paper: https://arxiv.org/abs/2403.05313 By: Zihao Wang, Anji Liu, Haowei Lin, Jiaqi Li, Xiaojian Ma, Yitao Liang Abstract: We explore how iterative revising a chain of thoughts with the help of information retrieval significantly improves large language models' reasoning and generation ability in long-horizon generation
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Original Paper: https://arxiv.org/abs/2312.14197 By: Jingwei Yi, Yueqi Xie, Bin Zhu, Emre Kiciman, Guangzhong Sun, Xing Xie, Fangzhao Wu Abstract: The integration of large language models (LLMs) with external content has enabled more up-to-date and wide-ranging applications of LLMs, such as Microsoft Copilot. However, this integration
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Original Paper: https://arxiv.org/abs/2309.06553 By: Hao Sun, Alihan Hüyük, Mihaela van der Schaar Abstract: In this study, we aim to enhance the arithmetic reasoning ability of Large Language Models (LLMs) through zero-shot prompt optimization. We identify a previously overlooked objective of query dependency in such optimization
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Original Paper: https://arxiv.org/abs/2403.04123 By: Devjeet Roy, Xuchao Zhang, Rashi Bhave, Chetan Bansal, Pedro Las-Casas, Rodrigo Fonseca, Saravan Rajmohan Abstract: The growing complexity of cloud based software systems has resulted in incident management becoming an integral part of the software development lifecycle. Root cause analysis (RCA)
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Original Paper: https://arxiv.org/abs/2403.04121 By: Subbarao Kambhampati Abstract While humans sometimes do show the capability of correcting their own erroneous guesses with self-critiquing, there seems to be no basis for that assumption in the case of LLMs. Summary Notes Figure: An informal account of viewing LLM
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Original Paper: https://arxiv.org/abs/2403.02610 By: Pittawat Taveekitworachai, Febri Abdullah, Mury F. Dewantoro, Yi Xia, Pratch Suntichaikul, Ruck Thawonmas, Julian Togelius, Jochen Renz Abstract: This paper presents the second ChatGPT4PCG competition at the 2024 IEEE Conference on Games. In this edition of the competition, we follow the
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Original Paper: https://arxiv.org/abs/2306.04735 By: Jacob-Junqi Tian, David Emerson, Sevil Zanjani Miyandoab, Deval Pandya, Laleh Seyyed-Kalantari, Faiza Khan Khattak Abstract: Prompting large language models has gained immense popularity in recent years due to the advantage of producing good results even without the need for labelled data.
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Original Paper: https://arxiv.org/abs/2305.13655 By: Long Lian, Boyi Li, Adam Yala, Trevor Darrell Abstract: Recent advancements in text-to-image diffusion models have yielded impressive results in generating realistic and diverse images. However, these models still struggle with complex prompts, such as those that involve numeracy and spatial
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Original Paper: https://arxiv.org/abs/2303.08774 By: OpenAI, Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, Red Avila, Igor Babuschkin, Suchir Balaji, Valerie Balcom, Paul Baltescu, Haiming Bao, Mohammad Bavarian, Jeff Belgum, Irwan Bello, Jake
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Original Paper: https://arxiv.org/abs/2311.16119 By: Sander Schulhoff, Jeremy Pinto, Anaum Khan, Louis-François Bouchard, Chenglei Si, Svetlina Anati, Valen Tagliabue, Anson Liu Kost, Christopher Carnahan, Jordan Boyd-Graber Abstract: Large Language Models (LLMs) are deployed in interactive contexts with direct user engagement, such as chatbots and writing assistants.
