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Large Language Models (LLMs) are regularly updated to enhance performance, typically through changes in data or architecture.
Bertscore: Evaluating text generation with bert
Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q Weinberger, and Yoav Artzi. 2019 · 1904
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PIQA: reasoning about physical commonsense in natural language
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Model compression
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Superglue: A stickier benchmark for general-purpose language understanding systems
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Jeff Rasley, Samyam Rajbhandari, Olatunji Ruwase, and Yuxiong He. 2020 · 2020
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Towards backward-compatible representation learning
Yantao Shen, Yuanjun Xiong, Wei Xia, and Stefano Soatto. 2020 · 2020
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An empirical analysis of backward compatibility in machine learning systems
Megha Srivastava, Besmira Nushi, Ece Kamar, Shital Shah, and Eric Horvitz. 2020 · 2020
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Training verifiers to solve math word problems
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Lora: Low-rank adaptation of large language models
Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen. 2021 · 2021
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Backward-compatible prediction updates: A probabilistic approach
Frederik Träuble, Julius Von Kügelgen, Matthäus Kleindessner, Francesco Locatello, Bernhard Schölkopf, and Peter Gehler. 2021 · 2021
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Yuqing Xie, Yi-An Lai, Yuanjun Xiong, Yi Zhang, and Stefano Soatto. 2021 · 2021
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Phi-2: The surprising power of small language models
Mojan Javaheripi, Sébastien Bubeck, Marah Abdin, Jyoti Aneja, Sebastien Bubeck, Caio César Teodoro Mendes, Weizhu Chen, Allie Del Giorno, Ronen Eldan, Sivakanth Gopi, et al. 2023 · 2023
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Improving prediction backward-compatiblility in nlp model upgrade with gated fusion
Yi-An Lai, Elman Mansimov, Yuqing Xie, and Yi Zhang. 2023 · 2023
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Sijie Yan, Yuanjun Xiong, Kaustav Kundu, Shuo Yang, Siqi Deng, Meng Wang, Wei Xia, and Stefano Soatto. 2021 · 2021
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Hot-refresh model upgrades with regression-free compatible training in image retrieval
Binjie Zhang, Yixiao Ge, Yantao Shen, Yu Li, Chun Yuan, Xuyuan Xu, Yexin Wang, and Ying Shan. 2021 · 2021
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Measuring and reducing model update regression in structured prediction for nlp
Deng Cai, Elman Mansimov, Yi-An Lai, Yixuan Su, Lei Shu, and Yi Zhang. 2022 · 2022
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Elle: Efficient lifelong pre-training for emerging data
Yujia Qin, Jiajie Zhang, Yankai Lin, Zhiyuan Liu, Peng Li, Maosong Sun, and Jie Zhou. 2022 · 2022
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Forward compatible training for large-scale embedding retrieval systems
Vivek Ramanujan, Pavan Kumar Anasosalu Vasu, Ali Farhadi, Oncel Tuzel, and Hadi Pouransari. 2022 · 2022
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A generalized backward compatibility metric
Tomoya Sakai. 2022 · 2022
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Contrastive representation distillation
Yonglong Tian, Dilip Krishnan, and Phillip Isola. 2022 · 2022
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Elodi: Ensemble logit difference inhibition for positive-congruent training
Yue Zhao, Yantao Shen, Yuanjun Xiong, Shuo Yang, Wei Xia, Zhuowen Tu, Bernt Schiele, and Stefano Soatto. 2022 · 2022
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Lightweight approaches to dnn regression error reduction: An uncertainty alignment perspective
Zenan Li, Maorun Zhang, Jingwei Xu, Yuan Yao, Chun Cao, Taolue Chen, Xiaoxing Ma, and Jian Lü. 2023b · 2023
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(why) is my prompt getting worse? rethinking regression testing for evolving llm apis
Wanqin Ma, Chenyang Yang, and Christian Kästner. 2023 · 2023
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A robust backward compatibility metric for model retraining
Ryuta Matsuno and Keita Sakuma. 2023 · 2023
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Recyclable tuning for continual pre-training
Yujia Qin, Cheng Qian, Xu Han, Yankai Lin, Huadong Wang, Ruobing Xie, Zhiyuan Liu, Maosong Sun, and Jie Zhou. 2023 · 2023
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X-adapter: Adding universal compatibility of plugins for upgraded diffusion model
Lingmin Ran, Xiaodong Cun, Jia-Wei Liu, Rui Zhao, Song Zijie, Xintao Wang, Jussi Keppo, and Mike Zheng Shou. 2023 · 2023
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Backward compatibility during data updates by weight interpolation
Raphael Schumann, Elman Mansimov, Yi-An Lai, Nikolaos Pappas, Xibin Gao, and Yi Zhang. 2023 · 2023
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Llama 3 model card
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Judging llm-as-a-judge with mt-bench and chatbot arena
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