Fetching the paper…
Reading the bibliography…
The ability to communicate uncertainty, risk, and limitation is crucial for the safety of large language models.
Interpretation of uncertainty expressions
G Richard Chesley. 1986 · 1986
Earlier work this paper cites.
Decisions based on numerically and verbally expressed uncertainties
David V Budescu, Shalva Weinberg, and Thomas S Wallsten. 1988 · 1988
Earlier work this paper cites.
The psychology of everyday things
Donald A Norman. 1988 · 1988
Earlier work this paper cites.
Verbal uncertainty expressions: Literature review
Marek J Druzdzel. 1989 · 1989
Earlier work this paper cites.
Measuring psychological uncertainty: Verbal versus numeric methods
Paul D Windschitl and Gary L Wells. 1996 · 1996
Earlier work this paper cites.
On defining “reliance” and “trust”: Purposes, conditions of adequacy, and new definitions
Karl de Fine Licht and Bengt Brülde. 2021 · 2001
Earlier work this paper cites.
Interpretation of uncertainty expressions: a cross-national study
Timothy S. Doupnik and Martin Richter. 2003 · 2003
Earlier work this paper cites.
Establishing and maintaining long-term human-computer relationships
Timothy W Bickmore and Rosalind W Picard. 2005 · 2005
Earlier work this paper cites.
Games with a purpose
Luis Von Ahn. 2006 · 2006
Earlier work this paper cites.
The dynamics of warmth and competence judgments, and their outcomes in organizations
Amy JC Cuddy, Peter Glick, and Anna Beninger. 2011 · 2011
Earlier work this paper cites.
Quality through flow and immersion: gamifying crowdsourced relevance assessments
Carsten Eickhoff, Christopher G Harris, Arjen P de Vries, and Padmini Srinivasan. 2012 · 2012
Earlier work this paper cites.
Tell me more? the effects of mental model soundness on personalizing an intelligent agent
Todd Kulesza, Simone Stumpf, Margaret Burnett, and Irwin Kwan. 2012 · 2012
Earlier work this paper cites.
Crowdsourcing quality-of-experience assessments
Tobias Hossfeld, Christian Keimel, and Christian Timmerer. 2014 · 2014
Earlier work this paper cites.
To play or not to play: Interactions between response quality and task complexity in games and paid crowdsourcing
Markus Krause and René Kizilcec. 2015 · 2015
Earlier work this paper cites.
Curiosity killed the cat, but makes crowdwork better
Edith Law, Ming Yin, Joslin Goh, Kevin Chen, Michael A Terry, and Krzysztof Z Gajos. 2016 · 2016
Earlier work this paper cites.
Living up to the chatbot hype: The influence of anthropomorphic design cues and communicative agency framing on conversational agent and company perceptions
Theo Araujo. 2018 · 2018
Earlier work this paper cites.
Beyond Accuracy: The Role of Mental Models in Human-AI Team Performance
Gagan Bansal, Besmira Nushi, Ece Kamar, Walter S Lasecki, Daniel S Weld, and Eric Horvitz. 2019 · 2019
Earlier work this paper cites.
Using pre-training can improve model robustness and uncertainty
Dan Hendrycks, Kimin Lee, and Mantas Mazeika. 2019 · 2019
Earlier work this paper cites.
I know what you’re probably going to say: Listener adaptation to variable use of uncertainty expressions
Sebastian Schuster and Judith Degen. 2019 · 2019
Earlier work this paper cites.
Is it human? the role of anthropomorphism as a driver for the successful acceptance of digital voice assistants
Katja Wagner, Frederic Nimmermann, and Hanna Schramm-Klein. 2019 · 2019
Earlier work this paper cites.
Calibration of pre-trained transformers
Shrey Desai and Greg Durrett. 2020 · 2020
Cited alongside, same era.
Mental models of ai agents in a cooperative game setting
Katy Ilonka Gero, Zahra Ashktorab, Casey Dugan, Qian Pan, James Johnson, Werner Geyer, Maria Ruiz, Sarah Miller, David R. Millen, Murray Campbell, Sadhana Kumaravel, and Wei Zhang. 2020 · 2020
Cited alongside, same era.
Selective question answering under domain shift
Amita Kamath, Robin Jia, and Percy Liang. 2020 · 2020
Cited alongside, same era.
Calibrated language model fine-tuning for in- and out-of-distribution data
Lingkai Kong, Haoming Jiang, Yuchen Zhuang, Jie Lyu, Tuo Zhao, and Chao Zhang. 2020 · 2020
Cited alongside, same era.
Alexa, Google, Siri: What are your pronouns? gender and anthropomorphism in the design and perception of conversational assistants
Gavin Abercrombie, Amanda Cercas Curry, Mugdha Pandya, and Verena Rieser. 2021 · 2021
Cited alongside, same era.
Quantifying uncertainty in natural language explanations of large language models
Sree Harsha Tanneru, Chirag Agarwal, and Himabindu Lakkaraju. 2023 · 2023
Later among the works it cites.
Just ask for calibration: Strategies for eliciting calibrated confidence scores from language models fine-tuned with human feedback
Katherine Tian, Eric Mitchell, Allan Zhou, Archit Sharma, Rafael Rafailov, Huaxiu Yao, Chelsea Finn, and Christopher Manning. 2023 · 2023
Later among the works it cites.
Explanations can reduce overreliance on ai systems during decision-making
Helena Vasconcelos, Matthew Jörke, Madeleine Grunde-McLaughlin, Tobias Gerstenberg, Michael S Bernstein, and Ranjay Krishna. 2023 · 2023
Later among the works it cites.
Finetuning language models to emit linguistic expressions of uncertainty
Arslan Chaudhry, Sridhar Thiagarajan, and Dilan Gorur. 2024 · 2024
Closest in time.
AnthroScore: A computational linguistic measure of anthropomorphism
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
To trust or to think: Cognitive forcing functions can reduce overreliance on ai in ai-assisted decision-making
Zana Buçinca, Maja Barbara Malaya, and Krzysztof Z. Gajos. 2021 · 2021
Cited alongside, same era.
Measuring massive multitask language understanding
Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt. 2021 · 2021
Cited alongside, same era.
How can we know when language models know? on the calibration of language models for question answering
Zhengbao Jiang, Jun Araki, Haibo Ding, and Graham Neubig. 2021 · 2021
Cited alongside, same era.
Training a helpful and harmless assistant with reinforcement learning from human feedback
Yuntao Bai, Andy Jones, Kamal Ndousse, Amanda Askell, Anna Chen, Nova DasSarma, Dawn Drain, Stanislav Fort, Deep Ganguli, Tom Henighan, Nicholas Joseph, Saurav Kadavath, Jackson Kernion, Tom Conerly, Sheer El-Showk, Nelson Elhage, Zac Hatfield-Dodds, Danny Hernandez, Tristan Hume, Scott Johnston, Shauna Kravec, Liane Lovitt, Neel Nanda, Catherine Olsson, Dario Amodei, Tom Brown, Jack Clark, Sam McCandlish, Chris Olah, Ben Mann, and Jared Kaplan. 2022 · 2022
Cited alongside, same era.
Human vs. ai: Understanding the impact of anthropomorphism on consumer response to chatbots from the perspective of trust and relationship norms
Xusen Cheng, Xiaoping Zhang, Jason Cohen, and Jian Mou. 2022 · 2022
Cited alongside, same era.
Language models (mostly) know what they know
Saurav Kadavath, Tom Conerly, Amanda Askell, Tom Henighan, Dawn Drain, Ethan Perez, Nicholas Schiefer, Zac Hatfield Dodds, Nova DasSarma, Eli Tran-Johnson, et al. 2022 · 2022
Cited alongside, same era.
Teaching models to express their uncertainty in words
Stephanie C. Lin, Jacob Hilton, and Owain Evans. 2022 · 2022
Cited alongside, same era.
Myra Cheng, Kristina Gligoric, Tiziano Piccardi, and Dan Jurafsky. 2024 · 2024
Closest in time.
Believing anthropomorphism: Examining the role of anthropomorphic cues on trust in large language models
Michelle Cohn, Mahima Pushkarna, Gbolahan O Olanubi, Joseph M Moran, Daniel Padgett, Zion Mengesha, and Courtney Heldreth. 2024 · 2024
Closest in time.
Folk psychological attributions of consciousness to large language models
Clara Colombatto and Stephen M Fleming. 2024 · 2024
Closest in time.
Are language models rational? the case of coherence norms and belief revision
Thomas Hofweber, Peter Hase, Elias Stengel-Eskin, and Mohit Bansal. 2024 · 2024
Closest in time.
From "ai" to probabilistic automation: How does anthropomorphization of technical systems descriptions influence trust?
Nanna Inie, Stefania Druga, Peter Zukerman, and Emily M. Bender. 2024 · 2024
Closest in time.
" i’m not sure, but…": Examining the impact of large language models’ uncertainty expression on user reliance and trust
Sunnie SY Kim, Q Vera Liao, Mihaela Vorvoreanu, Stephanie Ballard, and Jennifer Wortman Vaughan. 2024 · 2024
Closest in time.
Warmth and competence in human-agent cooperation
Kevin R McKee, Xuechunzi Bai, and Susan T Fiske. 2024 · 2024
Closest in time.
Explaining the unexplainable: The impact of misleading explanations on trust in unreliable predictions for hardly assessable tasks
Mersedeh Sadeghi, Daniel Pöttgen, Patrick Ebel, and Andreas Vogelsang. 2024 · 2024
Closest in time.
Explanations, fairness, and appropriate reliance in human-ai decision-making
Jakob Schoeffer, Maria De-Arteaga, and Niklas Kühl. 2024 · 2024
Closest in time.
Lacie: Listener-aware finetuning for confidence calibration in large language models
Elias Stengel-Eskin, Peter Hase, and Mohit Bansal. 2024 · 2024
Closest in time.
Understanding user experience in large language model interactions
Jiayin Wang, Weizhi Ma, Peijie Sun, Min Zhang, and Jian-Yun Nie. 2024 · 2024
Closest in time.
Can LLMs express their uncertainty? an empirical evaluation of confidence elicitation in LLMs
Miao Xiong, Zhiyuan Hu, Xinyang Lu, YIFEI LI, Jie Fu, Junxian He, and Bryan Hooi. 2024 · 2024
Closest in time.
Wildchat: 1m chatgpt interaction logs in the wild
Wenting Zhao, Xiang Ren, Jack Hessel, Claire Cardie, Yejin Choi, and Yuntian Deng. 2024 · 2024
Closest in time.
Relying on the unreliable: The impact of language models’ reluctance to express uncertainty
Kaitlyn Zhou, Jena D. Hwang, Xiang Ren, and Maarten Sap. 2024 · 2024
Closest in time.
Calibrating structured output predictors for natural language processing
Abhyuday Jagannatha and Hong Yu. 2020 · 2092
Closest in time.