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Large language models (LLMs) have made impressive progress in natural language processing.
Recursive deep models for semantic compositionality over a sentiment treebank
Socher, R · 2013
Earlier work this paper cites.
GLUE: A multi-task benchmark and analysis platform for natural language understanding
Wang, A · 2019
Earlier work this paper cites.
Robust encodings: A framework for combating adversarial typos
Jones, E · 2020
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BioBERTpt - a Portuguese neural language model for clinical named entity recognition
Schneider, E. T. R · 2020
Earlier work this paper cites.
AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts
Shin, T · 2020
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Evaluating large language models trained on code
Chen, M · 2021
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Prompt programming for large language models: Beyond the few-shot paradigm
Reynolds, L · 2021
Earlier work this paper cites.
Instruction induction: From few examples to natural language task descriptions
Honovich, O · 2022
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Lora: Low-rank adaptation of large language models
Hu, E. J · 2022
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Towards reasoning in large language models: A survey
Huang, J · 2022
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Large language models are zero-shot reasoners
Kojima, T · 2022
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What makes good in-context examples for GPT-3?
Liu, J · 2022
Cited alongside, same era.
Rethinking the role of demonstrations: What makes in-context learning work?
Min, S · 2022
Cited alongside, same era.
Training language models to follow instructions with human feedback
Ouyang, L · 2022
Cited alongside, same era.
Automatic generation of programming exercises and code explanations using large language models
Sarsa, S · 2022
Cited alongside, same era.
Challenging big-bench tasks and whether chain-of-thought can solve them
Suzgun, M · 2022
Cited alongside, same era.
Self-consistency improves chain of thought reasoning in language models
Wang, X · 2022
Sparks of artificial general intelligence: Early experiments with gpt-4
Bubeck, S · 2023
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Qlora: Efficient finetuning of quantized llms
Dettmers, T · 2023
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Guiding pretraining in reinforcement learning with large language models
Du, Y · 2023
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Pal: Program-aided language models
Gao, L · 2023
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Repository-level prompt generation for large language models of code
Shrivastava, D · 2023
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Large language models in medicine
Thirunavukarasu, A. J · 2023
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Cited alongside, same era.
Finetuned language models are zero-shot learners
Wei, J · 2022
Cited alongside, same era.
An explanation of in-context learning as implicit bayesian inference
Xie, S. M · 2022
Cited alongside, same era.
Ground-truth labels matter: A deeper look into input-label demonstrations
Yoo, K. M · 2022
Cited alongside, same era.
Large language models are human-level prompt engineers
Zhou, Y · 2022
Cited alongside, same era.
Emergent abilities of large language models
Wei, J
Cited in the paper.
Chain-of-thought prompting elicits reasoning in large language models
Wei, J
Cited in the paper.
On the robustness of chatgpt: An adversarial and out-of-distribution perspective
Wang, J · 2023
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A prompt pattern catalog to enhance prompt engineering with chatgpt
White, J · 2023
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Prompting large language model for machine translation: A case study
Zhang, B · 2023
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Deeptagger: Knowledge enhanced named entity recognition for web-based ads queries
Zuo, S · 2023
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