Know Your Limits: A Survey of Abstention in Large Language Models

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Proximal policy optimization algorithms

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Shrey Desai and Greg Durrett. 2020 · 2020

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RealToxicityPrompts: Evaluating neural toxic degeneration in language models

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Latent hatred: A benchmark for understanding implicit hate speech

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How can we know when language models know? on the calibration of language models for question answering

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Simple entity-centric questions challenge dense retrievers

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The art of abstention: Selective prediction and error regularization for natural language processing

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Detoxifying language models risks marginalizing minority voices

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Palm: Scaling language modeling with pathways

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ToxiGen: A large-scale machine-generated dataset for adversarial and implicit hate speech detection

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Training compute-optimal large language models

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LoRA: Low-rank adaptation of large language models

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Language models (mostly) know what they know

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Training language models to follow instructions with human feedback

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MuSiQue: Multihop questions via single-hop question composition

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Uncertainty quantification with pre-trained language models: A large-scale empirical analysis

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Yuxin Xiao, Paul Pu Liang, Umang Bhatt, Willie Neiswanger, Ruslan Salakhutdinov, and Louis-Philippe Morency. 2022 · 2022

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Calibrating sequence likelihood improves conditional language generation

Yao Zhao, Mikhail Khalman, Rishabh Joshi, Shashi Narayan, Mohammad Saleh, and Peter J Liu. 2022 · 2022

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GPT-4 technical report

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Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al. 2023 · 2023

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Knowledge of knowledge: Exploring known-unknowns uncertainty with large language models

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Alfonso Amayuelas, Liangming Pan, Wenhu Chen, and William Wang. 2023 · 2023

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Introducing claude

Anthropic. 2023 · 2023

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The internal state of an LLM knows when it’s lying

Amos Azaria and Tom Mitchell. 2023 · 2023

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Defending against alignment-breaking attacks via robustly aligned LLM

Original

Bochuan Cao, Yuanpu Cao, Lu Lin, and Jinghui Chen. 2023 · 2023

Cited alongside, same era.

Jailbreaking black box large language models in twenty queries

Original

Patrick Chao, Alexander Robey, Edgar Dobriban, Hamed Hassani, George J Pappas, and Eric Wong. 2023 · 2023

Cited alongside, same era.

Adaptation with self-evaluation to improve selective prediction in LLMs

Jiefeng Chen, Jinsung Yoon, Sayna Ebrahimi, Sercan Arik, Tomas Pfister, and Somesh Jha. 2023b · 2023

Cited alongside, same era.

Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality

Wei-Lin Chiang, Zhuohan Li, Zi Lin, Ying Sheng, Zhanghao Wu, Hao Zhang, Lianmin Zheng, Siyuan Zhuang, Yonghao Zhuang, Joseph E. Gonzalez, Ion Stoica, and Eric P. Xing. 2023 · 2023

The art of saying no: Contextual noncompliance in language models

Original

Faeze Brahman, Sachin Kumar, Vidhisha Balachandran, Pradeep Dasigi, Valentina Pyatkin, Abhilasha Ravichander, Sarah Wiegreffe, Nouha Dziri, Khyathi Chandu, Jack Hessel, et al. 2024 · 2024

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Learn to refuse: Making large language models more controllable and reliable through knowledge scope limitation and refusal mechanism

Lang Cao. 2024 · 2024

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Jailbreakbench: An open robustness benchmark for jailbreaking large language models

Original

Patrick Chao, Edoardo Debenedetti, Alexander Robey, Maksym Andriushchenko, Francesco Croce, Vikash Sehwag, Edgar Dobriban, Nicolas Flammarion, George J Pappas, Florian Tramer, et al. 2024 · 2024

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INSIDE: LLMs’ internal states retain the power of hallucination detection

Chao Chen, Kai Liu, Ze Chen, Yi Gu, Yue Wu, Mingyuan Tao, Zhihang Fu, and Jieping Ye. 2024 · 2024

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Can AI assistants know what they don’t know?