{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,28]],"date-time":"2026-03-28T16:51:00Z","timestamp":1774716660489,"version":"3.50.1"},"reference-count":66,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"1","license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Artif. Intell."],"published-print":{"date-parts":[[2025,1]]},"DOI":"10.1109\/tai.2024.3440248","type":"journal-article","created":{"date-parts":[[2024,8,8]],"date-time":"2024-08-08T14:55:18Z","timestamp":1723128918000},"page":"14-24","source":"Crossref","is-referenced-by-count":19,"title":["Silver Lining in the Fake News Cloud: Can Large Language Models Help Detect Misinformation?"],"prefix":"10.1109","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9488-3099","authenticated-orcid":false,"given":"Raghvendra","family":"Kumar","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, Indian Institute of Technology, Patna, India"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-5371-2639","authenticated-orcid":false,"given":"Bhargav","family":"Goddu","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Indian Institute of Technology, Patna, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5494-9391","authenticated-orcid":false,"given":"Sriparna","family":"Saha","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Indian Institute of Technology, Patna, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7235-0665","authenticated-orcid":false,"given":"Adam","family":"Jatowt","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Innsbruck, Innsbruck, Austria"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"crossref","DOI":"10.31234\/osf.io\/v4mfz","article-title":"What label should be applied to content produced by generative AI?","author":"Epstein","year":"2023"},{"key":"ref2","article-title":"Generative language models and automated influence operations: Emerging threats potential mitigations","author":"Goldstein","year":"2023"},{"key":"ref3","doi-asserted-by":"crossref","first-page":"1389","DOI":"10.18653\/v1\/2023.findings-emnlp.97","article-title":"On the risk of misinformation pollution with large language models","volume-title":"Findings Association for Computational. Linguistics: EMNLP","author":"Pan","year":"2023"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/3544548.3581318"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/3395046"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/3137597.3137600"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipm.2019.03.004"},{"key":"ref8","article-title":"Learning reporting dynamics during breaking news for rumour detection in social media","author":"Zubiaga"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2019.05.035"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/3289600.3290994"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N19-1163"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2018.05.019"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-67217-5_8"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/access.2024.3406644"},{"key":"ref15","first-page":"675","article-title":"A multitask, multilingual, multimodal evaluation of ChatGPT on reasoning, hallucination, and interactivity","volume-title":"Proc. 13th Int. Joint Conf. Natural Lang. Process. 3rd Conf. Asia-Pacific Chapter Assoc. Comput. Linguistics","volume":"1","author":"Bang","year":"2023"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1145\/3589335.3641256"},{"issue":"20","key":"ref17","first-page":"22105","article-title":"Bad actor, good advisor: Exploring the role of large language models in fake news detection","volume-title":"Proc. AAAI Conf. Artif. Intell.","volume":"38","author":"Hu","year":"2024"},{"key":"ref18","article-title":"Analysis of disinformation and fake news detection using fine-tuned large language model","author":"Pavlyshenko"},{"key":"ref19","article-title":"Generative AI text classification using ensemble LLM approaches","author":"Abburi"},{"key":"ref20","article-title":"Med-MMHL: A multi-modal dataset for detecting human- and LLM-generated misinformation in the medical domain","author":"Sun"},{"key":"ref21","first-page":"14279","article-title":"Fighting fire with fire: The dual role of LLMs in crafting and detecting elusive disinformation","volume-title":"Proc. Conf. Empirical Methods Natural Lang. Process.","author":"Lucas","year":"2023"},{"key":"ref22","first-page":"996","article-title":"Towards LLM-based fact verification on news claims with a hierarchical step-by-step prompting method","volume-title":"Proc. 13th Int. Joint Conf. Natural Lang. Process. 3rd Conf. Asia-Pacific Chapter Assoc. Comput. Linguistics","volume":"1","author":"Zhang","year":"2023"},{"key":"ref23","article-title":"Can LLM-generated misinformation be detected?","volume-title":"Proc. 12th Int. Conf. Learn. Representations","author":"Chen","year":"2023"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611978032.50"},{"key":"ref25","first-page":"6399","article-title":"Towards reliable misinformation mitigation: Generalization, uncertainty, and GPT-4","volume-title":"Proc. Conf. Empirical Methods Natural Lang. Process.","author":"Pelrine","year":"2023"},{"key":"ref26","first-page":"6981","article-title":"Fact-checking complex claims with program-guided reasoning","volume-title":"Proc. 61st Annu. Meeting Assoc. Comput. Linguistics","volume":"1","author":"Pan","year":"2023"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1002\/aaai.12188"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1145\/3589335.3651910"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.3390\/electronics10111348"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.compeleceng.2022.107967"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-50423-6_49"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2019.8683170"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1080\/21670811.2017.1345645"},{"key":"ref34","first-page":"65","article-title":"Detecting fake news through emotion analysis","volume-title":"Proc. 13th Int. Conf. Inf., Process, Knowl. Manage.","author":"Mackey","year":"2021"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.2139\/ssrn.4755964"},{"key":"ref36","article-title":"Exploring the relationship between LLM hallucinations and prompt linguistic nuances: Readability, formality, and concreteness","author":"Rawte"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1145\/3544548.3580817"},{"key":"ref38","article-title":"GPT-NER: Named entity recognition via large language models","author":"Wang"},{"key":"ref39","article-title":"Studying large language model generalization with influence functions","author":"Grosse"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2024\/873"},{"key":"ref41","article-title":"Learning reporting dynamics during breaking news for rumour detection in social media","author":"Zubiaga","year":"2016"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1089\/big.2020.0062"},{"key":"ref43","first-page":"7717","article-title":"Where are the facts? Searching for fact-checked information to alleviate the spread of fake news","volume-title":"Proc. Conf. Empirical Methods Natural Lang. Process. (EMNLP)","author":"Vo","year":"2020"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1007\/s40747-021-00552-1"},{"key":"ref45","article-title":"ESOC COVID-19 misinformation dataset","author":"Shapiro","year":"2024"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1609\/icwsm.v8i1.14550"},{"key":"ref47","article-title":"Emotion English distilroberta-base","author":"Hartmann","year":"2024"},{"issue":"16","key":"ref48","article-title":"Twitter sentiment analysis using natural language toolkit and VADER sentiment","volume-title":"Proc. Int. Multiconference Eng. Comput. Sci.","volume":"122","author":"Elbagir","year":"2019"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2020.113746"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/ICSC.2018.00052"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1016\/j.irfa.2024.103769"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1093\/comjnl\/bxac153"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1002\/0470013494.ch3"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2934529"},{"issue":"4","key":"ref55","doi-asserted-by":"crossref","DOI":"10.3390\/s21041322","article-title":"Emotion detection for social robots based on NLP transformers and an emotion ontology","volume":"21","author":"Graterol","year":"2021","journal-title":"Sensors"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1088\/1757-899X\/1110\/1\/012009"},{"key":"ref57","first-page":"1877","article-title":"Language models are few-shot learners","volume":"33","author":"Brown","year":"2020","journal-title":"Proc. Adv. Neural Inf. Process. Syst."},{"key":"ref58","article-title":"BLOOM: A 176B-parameter open-access multilingual language model","author":"Scao"},{"issue":"70","key":"ref59","first-page":"1","article-title":"Scaling instruction-finetuned language models","volume":"25","author":"Chung","year":"2024","journal-title":"J. Mach. Learn. Res."},{"key":"ref60","article-title":"GPT-Neo: Large scale autoregressive language modeling with mesh-tensorflow","author":"Black","year":"2021"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1515\/cog-2021-0007"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1037\/h0058980"},{"key":"ref63","article-title":"explosion\/spaCy: v3.7.2: Fixes for APIs and requirements","author":"Montani","year":"2023"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1037\/h0057532"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1037\/h0076540"},{"key":"ref66","first-page":"4171","article-title":"BERT: Pre-training of deep bidirectional transformers for language understanding","volume-title":"Proc. Conf. North Amer. Chapter Assoc. Comput. Linguistics: Human Lang. Technol.","volume":"1","author":"Devlin","year":"2019"}],"container-title":["IEEE Transactions on Artificial Intelligence"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/9078688\/10841832\/10631663.pdf?arnumber=10631663","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,23]],"date-time":"2025-08-23T01:09:32Z","timestamp":1755911372000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10631663\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,1]]},"references-count":66,"journal-issue":{"issue":"1"},"URL":"https:\/\/doi.org\/10.1109\/tai.2024.3440248","relation":{},"ISSN":["2691-4581"],"issn-type":[{"value":"2691-4581","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,1]]}}}