{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T04:29:05Z","timestamp":1780633745651,"version":"3.54.1"},"publisher-location":"New York, NY, USA","reference-count":61,"publisher":"ACM","license":[{"start":{"date-parts":[[2025,4,25]],"date-time":"2025-04-25T00:00:00Z","timestamp":1745539200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,4,26]]},"DOI":"10.1145\/3706599.3720249","type":"proceedings-article","created":{"date-parts":[[2025,4,23]],"date-time":"2025-04-23T20:15:12Z","timestamp":1745439312000},"page":"1-13","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["Fact or Fiction? Exploring Explanations to Identify Factual Confabulations in RAG-Based LLM Systems"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3207-666X","authenticated-orcid":false,"given":"Philipp","family":"Reinhard","sequence":"first","affiliation":[{"name":"Information Systems, University of Kassel, Kassel, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7171-9130","authenticated-orcid":false,"given":"Mahei Manhai","family":"Li","sequence":"additional","affiliation":[{"name":"Information Systems, University of Kassel, Kassel, Germany and Institute of Information Systems and Digital Business, University of St.Gallen, St.Gallen, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-5426-8911","authenticated-orcid":false,"given":"Matteo","family":"Fina","sequence":"additional","affiliation":[{"name":"Quantitative Marketing, Goethe University Frankfurt, Frankfurt, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1990-2894","authenticated-orcid":false,"given":"Jan Marco","family":"Leimeister","sequence":"additional","affiliation":[{"name":"Information Systems, University of Kassel, Kassel, Germany and Institute of Information Systems and Digital Business, University of St.Gallen, St.Gallen, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2025,4,25]]},"reference":[{"key":"e_1_3_3_1_2_2","doi-asserted-by":"crossref","unstructured":"Amina Adadi and Mohammed Berrada. 2018. Peeking inside the black-box: a survey on explainable artificial intelligence (XAI). IEEE Access 6 (2018) 52138\u201352160.","DOI":"10.1109\/ACCESS.2018.2870052"},{"key":"e_1_3_3_1_3_2","doi-asserted-by":"publisher","DOI":"10.1145\/3290605.3300484"},{"key":"e_1_3_3_1_4_2","doi-asserted-by":"crossref","unstructured":"Yejin Bang Samuel Cahyawijaya Nayeon Lee Wenliang Dai Dan Su Bryan Wilie Holy Lovenia Ziwei Ji Tiezheng Yu Willy Chung et\u00a0al. 2023. A multitask multilingual multimodal evaluation of chatgpt on reasoning hallucination and interactivity. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2302.04023 (2023).","DOI":"10.18653\/v1\/2023.ijcnlp-main.45"},{"key":"e_1_3_3_1_5_2","doi-asserted-by":"publisher","unstructured":"Kevin Bauer Moritz von Zahn and Oliver Hinz. 2023. Expl(AI)ned: The Impact of Explainable Artificial Intelligence on Users\u2019 Information Processing. Information Systems Research (2023) isre.2023.1199. 10.1287\/isre.2023.1199","DOI":"10.1287\/isre.2023.1199"},{"key":"e_1_3_3_1_6_2","volume-title":"Language models are few-shot learners","author":"Brown Tom","year":"2020","unstructured":"Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, and Amanda Askell (Eds.). 2020. Language models are few-shot learners. Vol.\u00a033. Larochelle H., Ranzato M., Hadsell R., Balcan M. F., and Lin H."},{"key":"e_1_3_3_1_7_2","doi-asserted-by":"crossref","unstructured":"Erik Brynjolfsson Danielle Li and Lindsey Raymond. 2025. Generative AI at work. The Quarterly Journal of Economics (2025).","DOI":"10.1093\/qje\/qjae044"},{"key":"e_1_3_3_1_8_2","volume-title":"Interactive Analysis of LLMs using Meaningful Counterfactuals","author":"Cheng Furui","year":"2024","unstructured":"Furui Cheng, Vil\u00e9m Zouhar, Robin Shing\u00a0Moon Chan, Daniel F\u00fcrst, Hendrik Strobelt, and Mennatallah El-Assady. 2024. Interactive Analysis of LLMs using Meaningful Counterfactuals."},{"key":"e_1_3_3_1_9_2","unstructured":"Zheng Chu Jingchang Chen Qianglong Chen Weijiang Yu Tao He Haotian Wang Weihua Peng Ming Liu Bing Qin and Ting Liu. 2023. A survey of chain of thought reasoning: Advances frontiers and future. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2309.15402 (2023)."},{"key":"e_1_3_3_1_10_2","doi-asserted-by":"publisher","unstructured":"Henriette Cramer Vanessa Evers Satyan Ramlal Maarten van Someren Lloyd Rutledge Natalia Stash Lora Aroyo and Bob Wielinga. 2008. The effects of transparency on trust in and acceptance of a content-based art recommender. User Modeling and User-Adapted Interaction 18 5 (2008) 455\u2013496. 10.1007\/s11257-008-9051-3","DOI":"10.1007\/s11257-008-9051-3"},{"key":"e_1_3_3_1_11_2","doi-asserted-by":"publisher","DOI":"10.1145\/3544548.3581263"},{"key":"e_1_3_3_1_12_2","doi-asserted-by":"publisher","unstructured":"Murat Dikmen and Catherine Burns. 2022. The effects of domain knowledge on trust in explainable AI and task performance: A case of peer-to-peer lending. International Journal of Human-Computer Studies 162 (2022) 102792. 10.1016\/j.ijhcs.2022.102792","DOI":"10.1016\/j.ijhcs.2022.102792"},{"key":"e_1_3_3_1_13_2","unstructured":"Hyo\u00a0Jin Do Rachel Ostrand Justin\u00a0D. Weisz Casey Dugan Prasanna Sattigeri Dennis Wei Keerthiram Murugesan and Werner Geyer. 30.0. Facilitating Human-LLM Collaboration through Factuality Scores and Source Attributions. http:\/\/arxiv.org\/pdf\/2405.20434"},{"key":"e_1_3_3_1_14_2","doi-asserted-by":"publisher","unstructured":"Jonathan Dodge Q.\u00a0Vera Liao Yunfeng Zhang Rachel K.\u00a0E. Bellamy and Casey Dugan. 2019. Explaining Models: An Empirical Study of How Explanations Impact Fairness Judgment. (2019). 10.48550\/ARXIV.1901.07694","DOI":"10.48550\/ARXIV.1901.07694"},{"key":"e_1_3_3_1_15_2","doi-asserted-by":"publisher","unstructured":"Nouha Dziri Ehsan Kamalloo Sivan Milton Osmar Zaiane Mo Yu Edoardo\u00a0M. Ponti and Siva Reddy. 2022. FaithDial : A Faithful Benchmark for Information-Seeking Dialogue. Transactions of the Association for Computational Linguistics 10 (2022) 1473\u20131490. 10.1162\/tacl_a_00529","DOI":"10.1162\/tacl_a_00529"},{"key":"e_1_3_3_1_16_2","volume-title":"A Survey of AI Reliance","author":"Eckhardt Sven","year":"2024","unstructured":"Sven Eckhardt, Niklas K\u00fchl, Mateusz Dolata, and Gerhard Schwabe. 2024. A Survey of AI Reliance."},{"key":"e_1_3_3_1_17_2","unstructured":"Shahul Es Jithin James Luis Espinosa-Anke and Steven Schockaert. 2023. Ragas: Automated evaluation of retrieval augmented generation. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2309.15217 (2023)."},{"key":"e_1_3_3_1_18_2","doi-asserted-by":"publisher","unstructured":"Shirley Gregor and Izak Benbasat. 1999. Explanations from Intelligent Systems: Theoretical Foundations and Implications for Practice. MIS Quarterly 23 4 (1999) 497. 10.2307\/249487","DOI":"10.2307\/249487"},{"key":"e_1_3_3_1_19_2","doi-asserted-by":"publisher","DOI":"10.1145\/3491102.3517650"},{"key":"e_1_3_3_1_20_2","doi-asserted-by":"publisher","unstructured":"Maurice Jakesch Jeffrey\u00a0T. Hancock and Mor Naaman. 2023. Human heuristics for AI-generated language are flawed. Proceedings of the National Academy of Sciences of the United States of America 120 11 (2023) e2208839120. 10.1073\/pnas.2208839120","DOI":"10.1073\/pnas.2208839120"},{"key":"e_1_3_3_1_21_2","doi-asserted-by":"publisher","unstructured":"Ziwei Ji Nayeon Lee Rita Frieske Tiezheng Yu Dan Su Yan Xu Etsuko Ishii Ye\u00a0Jin Bang Andrea Madotto and Pascale Fung. 2023. Survey of Hallucination in Natural Language Generation. Comput. Surveys 55 12 (2023) 1\u201338. 10.1145\/3571730","DOI":"10.1145\/3571730"},{"key":"e_1_3_3_1_22_2","doi-asserted-by":"publisher","unstructured":"Jinglu Jiang Surinder Kahai and Ming Yang. 2022. Who needs explanation and when? Juggling explainable AI and user epistemic uncertainty. International Journal of Human-Computer Studies 165 (2022) 102839. 10.1016\/j.ijhcs.2022.102839","DOI":"10.1016\/j.ijhcs.2022.102839"},{"key":"e_1_3_3_1_23_2","unstructured":"Saurav Kadavath Tom Conerly Amanda Askell Tom Henighan Dawn Drain Ethan Perez Nicholas Schiefer Zac Hatfield-Dodds Nova DasSarma Eli Tran-Johnson et\u00a0al. 2022. Language models (mostly) know what they know. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2207.05221 (2022)."},{"key":"e_1_3_3_1_24_2","doi-asserted-by":"publisher","DOI":"10.1145\/3290605.3300717"},{"key":"e_1_3_3_1_25_2","doi-asserted-by":"publisher","DOI":"10.1145\/3491102.3501999"},{"key":"e_1_3_3_1_26_2","doi-asserted-by":"publisher","DOI":"10.1145\/3313831.3376873"},{"key":"e_1_3_3_1_27_2","doi-asserted-by":"publisher","DOI":"10.1145\/3287560.3287590"},{"key":"e_1_3_3_1_28_2","doi-asserted-by":"publisher","DOI":"10.1145\/3610218"},{"key":"e_1_3_3_1_29_2","doi-asserted-by":"publisher","unstructured":"Benedikt Leichtmann Christina Humer Andreas Hinterreiter Marc Streit and Martina Mara. 2023. Effects of Explainable Artificial Intelligence on trust and human behavior in a high-risk decision task. Computers in Human Behavior 139 (2023) 107539. 10.1016\/j.chb.2022.107539","DOI":"10.1016\/j.chb.2022.107539"},{"key":"e_1_3_3_1_30_2","doi-asserted-by":"publisher","DOI":"10.1145\/3603555.3603565"},{"key":"e_1_3_3_1_31_2","doi-asserted-by":"publisher","DOI":"10.1145\/3613904.3642428"},{"key":"e_1_3_3_1_32_2","unstructured":"Patrick Lewis Ethan Perez Aleksandra Piktus Fabio Petroni Vladimir Karpukhin Naman Goyal Heinrich K\u00fcttler Mike Lewis Wen-tau Yih Tim Rockt\u00e4schel et\u00a0al. 2020. Retrieval-augmented generation for knowledge-intensive nlp tasks. Advances in Neural Information Processing Systems 33 (2020) 9459\u20139474."},{"key":"e_1_3_3_1_33_2","doi-asserted-by":"publisher","DOI":"10.1145\/3313831.3376590"},{"key":"e_1_3_3_1_34_2","unstructured":"Pan Lu Swaroop Mishra Tanglin Xia Liang Qiu Kai-Wei Chang Song-Chun Zhu Oyvind Tafjord Peter Clark and Ashwin Kalyan. 2022. Learn to explain: Multimodal reasoning via thought chains for science question answering. Advances in Neural Information Processing Systems 35 (2022) 2507\u20132521."},{"key":"e_1_3_3_1_35_2","doi-asserted-by":"publisher","unstructured":"Tian Lu and Yingjie Zhang. 2024. 1 + 1 > 2? Information Humans and Machines. Information Systems Research (2024). 10.1287\/isre.2023.0305","DOI":"10.1287\/isre.2023.0305"},{"key":"e_1_3_3_1_36_2","volume-title":"SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models","author":"Manakul Potsawee","year":"2023","unstructured":"Potsawee Manakul, Adian Liusie, and Mark J.\u00a0F. Gales. 2023. SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models."},{"key":"e_1_3_3_1_37_2","doi-asserted-by":"publisher","unstructured":"Ji-Ye Mao and Izak Benbasat. 2001. The effects of contextualized access to knowledge on judgement. International Journal of Human-Computer Studies 55 5 (2001) 787\u2013814. 10.1006\/ijhc.2001.0507","DOI":"10.1006\/ijhc.2001.0507"},{"key":"e_1_3_3_1_38_2","doi-asserted-by":"crossref","unstructured":"Tim Miller. 2019. Explanation in artificial intelligence: Insights from the social sciences. Artificial intelligence 267 (2019) 1\u201338.","DOI":"10.1016\/j.artint.2018.07.007"},{"key":"e_1_3_3_1_39_2","volume-title":"Fakes of Varying Shades: How Warning Affects Human Perception and Engagement Regarding LLM Hallucinations","author":"Nahar Mahjabin","year":"2024","unstructured":"Mahjabin Nahar, Haeseung Seo, Eun-Ju Lee, Aiping Xiong, and Dongwon Lee. 2024. Fakes of Varying Shades: How Warning Affects Human Perception and Engagement Regarding LLM Hallucinations."},{"key":"e_1_3_3_1_40_2","doi-asserted-by":"publisher","unstructured":"Mohammad Naiseh Dena Al-Thani Nan Jiang and Raian Ali. 2023. How the different explanation classes impact trust calibration: The case of clinical decision support systems. International Journal of Human-Computer Studies 169 (2023) 102941. 10.1016\/j.ijhcs.2022.102941","DOI":"10.1016\/j.ijhcs.2022.102941"},{"key":"e_1_3_3_1_41_2","doi-asserted-by":"publisher","DOI":"10.1145\/3613904.3642934"},{"key":"e_1_3_3_1_42_2","doi-asserted-by":"publisher","DOI":"10.1145\/3613904.3642785"},{"key":"e_1_3_3_1_43_2","volume-title":"Check Your Facts and Try Again: Improving Large Language Models with External Knowledge and Automated Feedback","author":"Peng Baolin","year":"2023","unstructured":"Baolin Peng, Michel Galley, Pengcheng He, Hao Cheng, Yujia Xie, Yu Hu, Qiuyuan Huang, Lars Liden, Zhou Yu, Weizhu Chen, and Jianfeng Gao. 2023. Check Your Facts and Try Again: Improving Large Language Models with External Knowledge and Automated Feedback."},{"key":"e_1_3_3_1_44_2","doi-asserted-by":"publisher","DOI":"10.1145\/3411764.3445315"},{"key":"e_1_3_3_1_45_2","doi-asserted-by":"publisher","DOI":"10.1145\/3173574.3173677"},{"key":"e_1_3_3_1_46_2","volume-title":"Language models are unsupervised multitask learners","author":"Radford A.","year":"2019","unstructured":"A. Radford, J. Wu, R. Child, D. Luan, D. Amodei, and I. Sutskever. 2019. Language models are unsupervised multitask learners. https:\/\/life-extension.github.io\/2020\/05\/27\/gpt%e6%8a%80%e6%9c%af%e5%88%9d%e6%8e%a2\/language-models.pdf"},{"key":"e_1_3_3_1_47_2","doi-asserted-by":"publisher","DOI":"10.1145\/3613905.3650919"},{"key":"e_1_3_3_1_48_2","unstructured":"Vipula Rawte Swagata Chakraborty Agnibh Pathak Anubhav Sarkar S.\u00a0M. Towhidul\u00a0Islam Tonmoy Aman Chadha Amit\u00a0P. Sheth and Amitava Das. 08.1. The Troubling Emergence of Hallucination in Large Language Models \u2013 An Extensive Definition Quantification and Prescriptive Remediations. http:\/\/arxiv.org\/pdf\/2310.04988"},{"key":"e_1_3_3_1_49_2","unstructured":"Reuters. 29.08.2024. OpenAI says ChatGPT\u2019s weekly users have grown to 200 million. Reuters Media (29.08.2024). https:\/\/www.reuters.com\/technology\/artificial-intelligence\/openai-says-chatgpts-weekly-users-have-grown-200-million-2024-08-29\/"},{"key":"e_1_3_3_1_50_2","doi-asserted-by":"crossref","unstructured":"Johannes Schneider. 2024. Explainable generative ai (genxai): A survey conceptualization and research agenda. Artificial Intelligence Review 57 11 (2024) 289.","DOI":"10.1007\/s10462-024-10916-x"},{"key":"e_1_3_3_1_51_2","doi-asserted-by":"publisher","unstructured":"Andrew Silva Mariah Schrum Erin Hedlund-Botti Nakul Gopalan and Matthew Gombolay. 2023. Explainable Artificial Intelligence: Evaluating the Objective and Subjective Impacts of xAI on Human-Agent Interaction. International Journal of Human\u2013Computer Interaction 39 7 (2023) 1390\u20131404. 10.1080\/10447318.2022.2101698","DOI":"10.1080\/10447318.2022.2101698"},{"key":"e_1_3_3_1_52_2","doi-asserted-by":"publisher","unstructured":"Venkatesh Sivaraman Leigh\u00a0A. Bukowski Joel Levin Jeremy\u00a0M. Kahn and Adam Perer. 2023. Ignore Trust or Negotiate: Understanding Clinician Acceptance of AI-Based Treatment Recommendations in Health Care. (2023). 10.48550\/ARXIV.2302.00096","DOI":"10.48550\/ARXIV.2302.00096"},{"key":"e_1_3_3_1_53_2","unstructured":"S.\u00a0M. Tonmoy S.\u00a0M. Zaman Vinija Jain Anku Rani Vipula Rawte Aman Chadha and Amitava Das. 2024. A comprehensive survey of hallucination mitigation techniques in large language models. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2401.01313 (2024)."},{"key":"e_1_3_3_1_54_2","doi-asserted-by":"publisher","DOI":"10.1145\/3411764.3445101"},{"key":"e_1_3_3_1_55_2","unstructured":"Ashish Vaswani Noam Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan\u00a0N. Gomez \u0141ukasz Kaiser and Illia Polosukhin. 2017. Attention is All you Need. Advances in Neural Information Processing Systems 30 (2017). https:\/\/proceedings.neurips.cc\/paper\/7181-attention-is-all"},{"key":"e_1_3_3_1_56_2","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.2208.11408"},{"key":"e_1_3_3_1_57_2","doi-asserted-by":"publisher","unstructured":"Daricia Wilkinson \u00d6znur Alkan Q.\u00a0Vera Liao Massimiliano Mattetti Inge Vejsbjerg Bart\u00a0P. Knijnenburg and Elizabeth Daly. 2021. Why or Why Not? The Effect of Justification Styles on Chatbot Recommendations. ACM Transactions on Information Systems 39 4 (2021) 1\u201321. 10.1145\/3441715","DOI":"10.1145\/3441715"},{"key":"e_1_3_3_1_58_2","doi-asserted-by":"crossref","unstructured":"Kem Z.\u00a0K. Zhang Sesia\u00a0J. Zhao Christy M.\u00a0K. Cheung and Matthew K.\u00a0O. Lee. 2014. Examining the influence of online reviews on consumers\u2019 decision-making: A heuristic\u2013systematic model. Decision Support Systems 67 (2014) 78\u201389.","DOI":"10.1016\/j.dss.2014.08.005"},{"key":"e_1_3_3_1_59_2","doi-asserted-by":"crossref","unstructured":"Shunyuan Zhang Param\u00a0Vir Singh and Anindya Ghose. 2019. A structural analysis of the role of superstars in crowdsourcing contests. Information Systems Research 30 1 (2019) 15\u201333.","DOI":"10.1287\/isre.2017.0767"},{"key":"e_1_3_3_1_60_2","doi-asserted-by":"publisher","unstructured":"Tong Zhang X.\u00a0Jessie Yang and Boyang Li. 2023. May I Ask a Follow-up Question? Understanding the Benefits of Conversations in Neural Network Explainability. (2023). 10.48550\/ARXIV.2309.13965","DOI":"10.48550\/ARXIV.2309.13965"},{"key":"e_1_3_3_1_61_2","doi-asserted-by":"publisher","DOI":"10.1145\/3351095.3372852"},{"key":"e_1_3_3_1_62_2","doi-asserted-by":"crossref","unstructured":"Zexuan Zhong Dan Friedman and Danqi Chen. 2021. Factual probing is [mask]: Learning vs. learning to recall. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2104.05240 (2021).","DOI":"10.18653\/v1\/2021.naacl-main.398"}],"event":{"name":"CHI EA '25: Extended Abstracts of the CHI Conference on Human Factors in Computing Systems","location":"Yokohama Japan","acronym":"CHI EA '25","sponsor":["SIGCHI ACM Special Interest Group on Computer-Human Interaction"]},"container-title":["Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3706599.3720249","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3706599.3720249","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T01:18:51Z","timestamp":1750295931000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3706599.3720249"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4,25]]},"references-count":61,"alternative-id":["10.1145\/3706599.3720249","10.1145\/3706599"],"URL":"https:\/\/doi.org\/10.1145\/3706599.3720249","relation":{},"subject":[],"published":{"date-parts":[[2025,4,25]]},"assertion":[{"value":"2025-04-25","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}