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Large language models (LLMs) demonstrate outstanding capabilities, but challenges remain regarding their ability to solve complex reasoning tasks, as well as their transparency, robustness, truthfulness, and ethical alignment.
Explainable artificial intelligence: a systematic review
G. Vilone and L. Longo · 2006
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The Art of Asking Essential Questions: Based on Critical Thinking Concepts and Socratic Principles
L. Elder and R. Paul · 2019
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The global landscape of AI ethics guidelines
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A critical perspective on guidelines for responsible and trustworthy artificial intelligence
B. Buruk, P. E. Ekmekci, and B. Arda · 2020
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Towards faithfully interpretable NLP systems: how should we define and evaluate faithfulness?
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OECD · 2020
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E. Commission · 2021
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Truthful AI: Developing and governing AI that does not lie
O. Evans, O. Cotton-Barratt, L. Finnveden, A. Bales, A. Balwit, P. Wills, L. Righetti, and W. Saunders · 2021
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Unsolved problems in ML safety
D. Hendrycks, N. Carlini, J. Schulman, and J. Steinhardt · 2021
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Self-diagnosis and self-debiasing: A proposal for reducing corpus-based bias in NLP
T. Schick, S. Udupa, and H. Schütze · 2021
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Reframing human-AI collaboration for generating free-text explanations
S. Wiegreffe, J. Hessel, S. Swayamdipta, M. Riedl, and Y. Choi · 2021
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Scaling instruction-finetuned language models
H. W. Chung, L. Hou, S. Longpre, B. Zoph, Y. Tay, W. Fedus, E. Li, X. Wang, M. Dehghani, S. Brahma, A. Webson, S. S. Gu, Z. Dai, M. Suzgun, X. Chen, A. Chowdhery, S. Narang, G. Mishra, A. Yu, V. Zhao, Y. Huang, A. Dai, H. Yu, S. Petrov, E. H. Chi, J. Dean, J. Devlin, A. Roberts, D. Zhou, Q. V. Le, and J. Wei · 2022
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Faithful reasoning using large language models
A. Creswell and M. Shanahan · 2022
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Successive prompting for decomposing complex questions
D. Dua, S. Gupta, S. Singh, and M. Gardner · 2022
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D. Ganguli, L. Lovitt, J. Kernion, A. Askell, Y. Bai, S. Kadavath, B. Mann, E. Perez, N. Schiefer, K. Ndousse, A. Jones, S. Bowman, A. Chen, T. Conerly, N. DasSarma, D. Drain, N. Elhage, S. El-Showk, S. Fort, Z. Hatfield-Dodds, T. Henighan, D. Hernandez, T. Hume, J. Jacobson, S. Johnston, S. Kravec, C. Olsson, S. Ringer, E. Tran-Johnson, D. Amodei, T. Brown, N. Joseph, S. McCandlish, C. Olah, J. Kaplan, and J. Clark · 2022
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ROSCOE: A suite of metrics for scoring step-by-step reasoning
O. Golovneva, M. Chen, S. Poff, M. Corredor, L. Zettlemoyer, M. Fazel-Zarandi, and A. Celikyilmaz · 2022
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Capturing failures of large language models via human cognitive biases
E. Jones and J. Steinhardt · 2022
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Maieutic prompting: Logically consistent reasoning with recursive explanations
J. Jung, L. Qin, S. Welleck, F. Brahman, C. Bhagavatula, R. L. Bras, and Y. Choi · 2022
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X. Ye and G. Durrett · 2022
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Least-to-most prompting enables complex reasoning in large language models
D. Zhou, N. Schärli, L. Hou, J. Wei, N. Scales, X. Wang, D. Schuurmans, O. Bousquet, Q. Le, and E. Chi · 2022
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Language models can solve computer tasks
G. Kim, P. Baldi, and S. McAleer · 2023
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Performance of ChatGPT on USMLE: Potential for AI-assisted medical education using large language models
T. H. Kung, M. Cheatham, A. Medenilla, C. Sillos, L. De Leon, C. Elepaño, M. Madriaga, R. Aggabao, G. Diaz-Candido, J. Maningo, and V. Tseng · 2023
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CAMEL: Communicative agents for "mind" exploration of large scale language model society
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T. Kojima, S. S. Gu, M. Reid, Y. Matsuo, and Y. Iwasawa · 2022
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CLAM: Selective clarification for ambiguous questions with large language models
L. Kuhn, Y. Gal, and S. Farquhar · 2022
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Holistic evaluation of language models
P. Liang, R. Bommasani, T. Lee, D. Tsipras, D. Soylu, M. Yasunaga, Y. Zhang, D. Narayanan, Y. Wu, A. Kumar, B. Newman, B. Yuan, B. Yan, C. Zhang, C. Cosgrove, C. D. Manning, C. Ré, D. Acosta-Navas, D. A. Hudson, E. Zelikman, E. Durmus, F. Ladhak, F. Rong, H. Ren, H. Yao, J. Wang, K. Santhanam, L. Orr, L. Zheng, M. Yuksekgonul, M. Suzgun, N. Kim, N. Guha, N. Chatterji, O. Khattab, P. Henderson, Q. Huang, R. Chi, S. M. Xie, S. Santurkar, S. Ganguli, T. Hashimoto, T. Icard, T. Zhang, V. Chaudhary, W. Wang, X. Li, Y. Mai, Y. Zhang, and Y. Koreeda · 2022
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Can large language models reason about medical questions?
V. Liévin, C. E. Hother, and O. Winther · 2022
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Red teaming language models with language models
E. Perez, S. Huang, F. Song, T. Cai, R. Ring, J. Aslanides, A. Glaese, N. McAleese, and G. Irving · 2022
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Measuring and narrowing the compositionality gap in language models
O. Press, M. Zhang, S. Min, L. Schmidt, N. A. Smith, and M. Lewis · 2022
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Large language models are not zero-shot communicators
L. Ruis, A. Khan, S. Biderman, S. Hooker, T. Rocktäschel, and E. Grefenstette · 2022
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Interleaving retrieval with chain-of-thought reasoning for knowledge-intensive multi-step questions
H. Trivedi, N. Balasubramanian, T. Khot, and A. Sabharwal · 2022
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G. Li, H. A. A. K. Hammoud, H. Itani, D. Khizbullin, and B. Ghanem · 2023
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DERA: Enhancing large language model completions with dialog-enabled resolving agents
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OpenAI · 2023
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ThoughtSource: A central hub for large language model reasoning data
S. Ott, K. Hebenstreit, V. Liévin, C. E. Hother, M. Moradi, M. Mayrhauser, R. Praas, O. Winther, and M. Samwald · 2023
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ART: Automatic multi-step reasoning and tool-use for large language models
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Large language models (GPT) struggle to answer multiple-choice questions about code
J. Savelka, A. Agarwal, C. Bogart, and M. Sakr · 2023
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Reflexion: an autonomous agent with dynamic memory and self-reflection
N. Shinn, B. Labash, and A. Gopinath · 2023
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Large language models encode clinical knowledge
K. Singhal, S. Azizi, T. Tu, S. S. Mahdavi, J. Wei, H. W. Chung, N. Scales, A. Tanwani, H. Cole-Lewis, S. Pfohl, P. Payne, M. Seneviratne, P. Gamble, C. Kelly, A. Babiker, N. Schärli, A. Chowdhery, P. Mansfield, D. Demner-Fushman, B. Agüera Y Arcas, D. Webster, G. S. Corrado, Y. Matias, K. Chou, J. Gottweis, N. Tomasev, Y. Liu, A. Rajkomar, J. Barral, C. Semturs, A. Karthikesalingam, and V. Natarajan · 2023
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Principle-driven self-alignment of language models from scratch with minimal human supervision
Z. Sun, Y. Shen, Q. Zhou, H. Zhang, Z. Chen, D. Cox, Y. Yang, and C. Gan · 2023
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Fundamental limitations of alignment in large language models
Y. Wolf, N. Wies, Y. Levine, and A. Shashua · 2023
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