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Large language models (LLMs) often fail to ask effective questions under uncertainty, making them unreliable in domains where proactive information-gathering is essential for decision-making.
Pubmedqa: A dataset for biomedical research question answering, 2019
Qiao Jin, Bhuwan Dhingra, Zhengping Liu, William W. Cohen, and Xinghua Lu · 1909
Earlier work this paper cites.
Speech Acts: An Essay in the Philosophy of Language
John R. Searle · 1969
Earlier work this paper cites.
Routine complications: Troubles with talk between doctors and patients
Candace West · 1984
Earlier work this paper cites.
Studies of doctor-patient interaction
Debra L. Roter and Judith A. Hall · 1987
Earlier work this paper cites.
The form and function of questions in informal dyadic conversation
Alice F. Freed · 1994
Earlier work this paper cites.
Doctors talking with patients—patients talking with doctors: improving communication in medical visits, 1995
JA Hall, DL Roter, and Barbara Junghans · 1995
Earlier work this paper cites.
Doctor-patient communication: a review of the literature
Lucille ML Ong, Johanna CJM De Haes, Alaysia M Hoos, and Frits B Lammes · 1995
Earlier work this paper cites.
The well-built clinical question: a key to evidence-based decisions
W Scott Richardson, Mark C Wilson, Jim Nishikawa, and Robert S Hayward · 1995
Earlier work this paper cites.
Communication in Medical Care: Interactions between Primary Care Physicians and Patients
John Heritage and Douglas W. Maynard (eds.) · 2006
Earlier work this paper cites.
Children’s questions: A mechanism for cognitive development
Michelle M. Chouinard · 2007
Earlier work this paper cites.
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Tanya Stivers and Asifa Majid · 2007
Earlier work this paper cites.
Discerning the division of cognitive labor: An emerging understanding of how knowledge is clustered in other minds
Frank C Keil, Courtney Stein, Lisa Webb, Van Dyke Billings, and Leonid Rozenblit · 2008
Earlier work this paper cites.
Questioning in medicine
John Heritage · 2010
Earlier work this paper cites.
Reconstructing constructivism: causal models, bayesian learning mechanisms, and the theory theory
Alison Gopnik and Henry M Wellman · 2012
Earlier work this paper cites.
Interrogative intimations: On a possible social economics of interrogatives
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Earlier work this paper cites.
Evidence and clinical decisions: asking the right questions to obtain clinically useful answers
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Sudha Rao and Hal Daumé III · 2018
Earlier work this paper cites.
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Samuel Ronfard, Imac M Zambrana, Tone K Hermansen, and Deborah Kelemen · 2018
Earlier work this paper cites.
What disease does this patient have
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Earlier work this paper cites.
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Patrick Lewis, Myle Ott, Jingfei Du, and Veselin Stoyanov · 2020
Earlier work this paper cites.
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Earlier work this paper cites.
Cross-replication reliability - an empirical approach to interpreting inter-rater reliability
Ka Wong, Praveen Paritosh, and Lora Aroyo · 2021
Earlier work this paper cites.
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Yuntao Bai, Andy Jones, Kamal Ndousse, Amanda Askell, Anna Chen, Nova DasSarma, Dawn Drain, Stanislav Fort, Deep Ganguli, Tom Henighan, et al · 2022
Earlier work this paper cites.
Readability of patient discharge instructions
Shohei T Burns, Nwamaka Amobi, Joshua Vic Chen, Meghan O’Brien, and Lawrence A Haber · 2022
Earlier work this paper cites.
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Arsene Fansi Tchango, Rishab Goel, Zhi Wen, Julien Martel, and Joumana Ghosn · 2022
Earlier work this paper cites.
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Ankit Pal, Logesh Kumar Umapathi, and Malaikannan Sankarasubbu · 2022
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T \ \backslash " ulu 3: Pushing frontiers in open language model post-training
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Mediq: Question-asking llms and a benchmark for reliable interactive clinical reasoning
Shuyue Stella Li, Vidhisha Balachandran, Shangbin Feng, Jonathan S Ilgen, Emma Pierson, Pang Wei Koh, and Yulia Tsvetkov · 2024
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