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Automatic prompt optimization is an important approach to improving the performance of large language models (LLMs).
Towards Unified Conversational Recommender Systems via Knowledge-Enhanced Prompt Learning
Wang, X.; Zhou, K.; Wen, J.; and Zhao, W. X. 2022a · 1937
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The Winograd Schema Challenge
Levesque, H. J.; Davis, E.; and Morgenstern, L. 2012 · 2012
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On the importance of initialization and momentum in deep learning
Sutskever, I.; Martens, J.; Dahl, G. E.; and Hinton, G. E. 2013 · 2013
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Convex Optimization
Boyd, S. P.; and Vandenberghe, L. 2014 · 2014
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Solving General Arithmetic Word Problems
Roy, S.; and Roth, D. 2016 · 2016
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Creating Training Corpora for NLG Micro-Planners
Gardent, C.; Shimorina, A.; Narayan, S.; and Perez-Beltrachini, L. 2017 · 2017
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Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour
Goyal, P.; Dollár, P.; Girshick, R. B.; Noordhuis, P.; Wesolowski, L.; Kyrola, A.; Tulloch, A.; Jia, Y.; and He, K. 2017 · 2017
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Program Induction by Rationale Generation: Learning to Solve and Explain Algebraic Word Problems
Ling, W.; Yogatama, D.; Dyer, C.; and Blunsom, P. 2017 · 2017
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Averaging Weights Leads to Wider Optima and Better Generalization
Izmailov, P.; Podoprikhin, D.; Garipov, T.; Vetrov, D. P.; and Wilson, A. G. 2018 · 2018
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A Closer Look at Deep Learning Heuristics: Learning rate restarts, Warmup and Distillation
Gotmare, A.; Keskar, N. S.; Xiong, C.; and Socher, R. 2019 · 2019
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A Survey of Optimization Methods From a Machine Learning Perspective
Sun, S.; Cao, Z.; Zhu, H.; and Zhao, J. 2020 · 2020
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Training Verifiers to Solve Math Word Problems
Cobbe, K.; Kosaraju, V.; Bavarian, M.; Chen, M.; Jun, H.; Kaiser, L.; Plappert, M.; Tworek, J.; Hilton, J.; Nakano, R.; Hesse, C.; and Schulman, J. 2021 · 2021
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Measuring Massive Multitask Language Understanding
Hendrycks, D.; Burns, C.; Basart, S.; Zou, A.; Mazeika, M.; Song, D.; and Steinhardt, J. 2021 · 2021
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Prefix-Tuning: Optimizing Continuous Prompts for Generation
Li, X. L.; and Liang, P. 2021 · 2021
Earlier work this paper cites.
RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learning
Deng, M.; Wang, J.; Hsieh, C.; Wang, Y.; Guo, H.; Shu, T.; Song, M.; Xing, E. P.; and Hu, Z. 2022 · 2022
Cited alongside, same era.
Large Language Models are Zero-Shot Reasoners
Kojima, T.; Gu, S. S.; Reid, M.; Matsuo, Y.; and Iwasawa, Y. 2022 · 2022
Cited alongside, same era.
Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity
Lu, Y.; Bartolo, M.; Moore, A.; Riedel, S.; and Stenetorp, P. 2022 · 2022
Cited alongside, same era.
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models
Srivastava, A.; Rastogi, A.; Rao, A.; Shoeb, A. A. M.; Abid, A.; Fisch, A.; Brown, A. R.; Santoro, A.; Gupta, A.; Garriga-Alonso, A.; Kluska, A.; Lewkowycz, A.; Agarwal, A.; Power, A.; Ray, A.; Warstadt, A.; Kocurek, A. W.; Safaya, A.; Tazarv, A.; Xiang, A.; Parrish, A.; Nie, A.; Hussain, A.; Askell, A.; Dsouza, A.; Rahane, A.; Iyer, A. S.; Andreassen, A.; Santilli, A.; Stuhlmüller, A.; Dai, A. M.; La, A.; Lampinen, A. K.; Zou, A.; Jiang, A.; Chen, A.; Vuong, A.; Gupta, A.; Gottardi, A.; Norelli, A.; Venkatesh, A.; Gholamidavoodi, A.; Tabassum, A.; Menezes, A.; Kirubarajan, A.; Mullokandov, A.; Sabharwal, A.; Herrick, A.; Efrat, A.; Erdem, A.; Karakas, A.; and et al. 2022 · 2022
Cited alongside, same era.
C-Pack: Packaged Resources To Advance General Chinese Embedding
Xiao, S.; Liu, Z.; Zhang, P.; and Muennighof, N. 2023 · 2023
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Large Language Models as Optimizers
Yang, C.; Wang, X.; Lu, Y.; Liu, H.; Le, Q. V.; Zhou, D.; and Chen, X. 2023 · 2023
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InstOptima: Evolutionary Multi-objective Instruction Optimization via Large Language Model-based Instruction Operators
Yang, H.; and Li, K. 2023 · 2023
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Prompt Engineering a Prompt Engineer
Ye, Q.; Axmed, M.; Pryzant, R.; and Khani, F. 2023 · 2023
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TEMPERA: Test-Time Prompt Editing via Reinforcement Learning
Zhang, T.; Wang, X.; Zhou, D.; Schuurmans, D.; and Gonzalez, J. E. 2023 · 2023
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GPS: Genetic Prompt Search for Efficient Few-Shot Learning
Xu, H.; Chen, Y.; Du, Y.; Shao, N.; Wang, Y.; Li, H.; and Yang, Z. 2022 · 2022
Cited alongside, same era.
InstructZero: Efficient Instruction Optimization for Black-Box Large Language Models
Chen, L.; Chen, J.; Goldstein, T.; Huang, H.; and Zhou, T. 2023 · 2023
Cited alongside, same era.
Agent Instructs Large Language Models to be General Zero-Shot Reasoners
Crispino, N.; Montgomery, K.; Zeng, F.; Song, D.; and Wang, C. 2023 · 2023
Cited alongside, same era.
Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution
Fernando, C.; Banarse, D.; Michalewski, H.; Osindero, S.; and Rocktäschel, T. 2023 · 2023
Cited alongside, same era.
Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers
Guo, Q.; Wang, R.; Guo, J.; Li, B.; Song, K.; Tan, X.; Liu, G.; Bian, J.; and Yang, Y. 2023 · 2023
Cited alongside, same era.
Large Language Models Cannot Self-Correct Reasoning Yet
Huang, J.; Chen, X.; Mishra, S.; Zheng, H. S.; Yu, A. W.; Song, X.; and Zhou, D. 2023 · 2023
Cited alongside, same era.
GrIPS: Gradient-free, Edit-based Instruction Search for Prompting Large Language Models
Prasad, A.; Hase, P.; Zhou, X.; and Bansal, M. 2023 · 2023
Cited alongside, same era.
Automatic Prompt Optimization with ”Gradient Descent” and Beam Search
Pryzant, R.; Iter, D.; Li, J.; Lee, Y. T.; Zhu, C.; and Zeng, M. 2023 · 2023
Cited alongside, same era.
Later among the works it cites.
A Survey of Large Language Models
Zhao, W. X.; Zhou, K.; Li, J.; Tang, T.; Wang, X.; Hou, Y.; Min, Y.; Zhang, B.; Zhang, J.; Dong, Z.; Du, Y.; Yang, C.; Chen, Y.; Chen, Z.; Jiang, J.; Ren, R.; Li, Y.; Tang, X.; Liu, Z.; Liu, P.; Nie, J.; and Wen, J. 2023 · 2023
Later among the works it cites.
Large Language Models are Human-Level Prompt Engineers
Zhou, Y.; Muresanu, A. I.; Han, Z.; Paster, K.; Pitis, S.; Chan, H.; and Ba, J. 2023 · 2023
Later among the works it cites.
Prompt Design and Engineering: Introduction and Advanced Methods
Amatriain, X. 2024 · 2024
Closest in time.
Dubey, A.; Jauhri, A.; Pandey, A.; Kadian, A.; Al-Dahle, A.; Letman, A.; Mathur, A.; Schelten, A.; Yang, A.; Fan, A.; et al. 2024 · 2024
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The Importance of Directional Feedback for LLM-based Optimizers
Nie, A.; Cheng, C.; Kolobov, A.; and Swaminathan, A. 2024 · 2024
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Prompts As Programs: A Structure-Aware Approach to Efficient Compile-Time Prompt Optimization
Schnabel, T.; and Neville, J. 2024 · 2024
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DAWN-ICL: Strategic Planning of Problem-solving Trajectories for Zero-Shot In-Context Learning
Tang, X.; Wang, X.; Zhao, W. X.; and Wen, J. 2024 · 2024
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REAR: A Relevance-Aware Retrieval-Augmented Framework for Open-Domain Question Answering
Wang, Y.; Ren, R.; Li, J.; Zhao, X.; Liu, J.; and Wen, J. 2024 · 2024
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Over-parameterized Student Model via Tensor Decomposition Boosted Knowledge Distillation
Zhan, Y.-L.; Lu, Z.-Y.; Sun, H.; and Gao, Z.-F. 2024 · 2024
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