{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T13:17:44Z","timestamp":1778246264902,"version":"3.51.4"},"reference-count":58,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2027,1,1]],"date-time":"2027-01-01T00:00:00Z","timestamp":1798761600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2027,1,1]],"date-time":"2027-01-01T00:00:00Z","timestamp":1798761600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2027,1,1]],"date-time":"2027-01-01T00:00:00Z","timestamp":1798761600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2027,1,1]],"date-time":"2027-01-01T00:00:00Z","timestamp":1798761600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2027,1,1]],"date-time":"2027-01-01T00:00:00Z","timestamp":1798761600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2027,1,1]],"date-time":"2027-01-01T00:00:00Z","timestamp":1798761600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2027,1,1]],"date-time":"2027-01-01T00:00:00Z","timestamp":1798761600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/100004672","name":"Accenture Inc","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100004672","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Computer Speech &amp; Language"],"published-print":{"date-parts":[[2027,1]]},"DOI":"10.1016\/j.csl.2026.101991","type":"journal-article","created":{"date-parts":[[2026,4,8]],"date-time":"2026-04-08T16:38:32Z","timestamp":1775666312000},"page":"101991","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Can language models persuade? Exploring the persuasive efficacy of Large Language and Vision Language models"],"prefix":"10.1016","volume":"101","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-8946-0007","authenticated-orcid":false,"given":"Rohan","family":"Kirti","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Atharva S.","family":"Deshmukh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kiran K.","family":"Dugana","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yash","family":"Rathore","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shipra","family":"Shriparn","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sriparna","family":"Saha","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Roshni R.","family":"Ramnani","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anutosh","family":"Maitra","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"key":"10.1016\/j.csl.2026.101991_b1","series-title":"Gpt-4 technical report","author":"Achiam","year":"2023"},{"key":"10.1016\/j.csl.2026.101991_b2","series-title":"Pixtral 12B","author":"Agrawal","year":"2024"},{"key":"10.1016\/j.csl.2026.101991_b3","series-title":"Palm 2 technical report","author":"Anil","year":"2023"},{"key":"10.1016\/j.csl.2026.101991_b4","unstructured":"Banerjee, S., Lavie, A., 2005. METEOR: An automatic metric for MT evaluation with improved correlation with human judgments. In: Proceedings of the Acl Workshop on Intrinsic and Extrinsic Evaluation Measures for Machine Translation and\/Or Summarization. pp. 65\u201372."},{"key":"10.1016\/j.csl.2026.101991_b5","series-title":"How well can llms negotiate? negotiationarena platform and analysis","author":"Bianchi","year":"2024"},{"key":"10.1016\/j.csl.2026.101991_b6","first-page":"152","article-title":"The persuasive power of large language models","volume":"vol. 18","author":"Breum","year":"2024"},{"key":"10.1016\/j.csl.2026.101991_b7","first-page":"1877","article-title":"Language models are few-shot learners","volume":"33","author":"Brown","year":"2020","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.csl.2026.101991_b8","series-title":"Large language models are as persuasive as humans, but why? About the cognitive effort and moral-emotional language of LLM arguments","author":"Carrasco-Farre","year":"2024"},{"key":"10.1016\/j.csl.2026.101991_b9","series-title":"Social influence dialogue systems: A survey of datasets and models for social influence tasks","author":"Chawla","year":"2022"},{"key":"10.1016\/j.csl.2026.101991_b10","series-title":"DEEPER insight into your user: Directed persona refinement for dynamic persona modeling","author":"Chen","year":"2025"},{"key":"10.1016\/j.csl.2026.101991_b11","doi-asserted-by":"crossref","unstructured":"Chen, Z., Wu, J., Wang, W., Su, W., Chen, G., Xing, S., Zhong, M., Zhang, Q., Zhu, X., Lu, L., et al., 2024. Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. pp. 24185\u201324198.","DOI":"10.1109\/CVPR52733.2024.02283"},{"issue":"2","key":"10.1016\/j.csl.2026.101991_b12","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1038\/scientificamerican0201-76","article-title":"The science of persuasion","volume":"284","author":"Cialdini","year":"2001","journal-title":"Sci. Am."},{"issue":"6714","key":"10.1016\/j.csl.2026.101991_b13","doi-asserted-by":"crossref","first-page":"eadq1814","DOI":"10.1126\/science.adq1814","article-title":"Durably reducing conspiracy beliefs through dialogues with AI","volume":"385","author":"Costello","year":"2024","journal-title":"Science"},{"key":"10.1016\/j.csl.2026.101991_b14","series-title":"UltraFeedback: Boosting language models with high-quality feedback","author":"Cui","year":"2023"},{"issue":"1","key":"10.1016\/j.csl.2026.101991_b15","doi-asserted-by":"crossref","first-page":"643","DOI":"10.1146\/annurev.economics.102308.124309","article-title":"Persuasion: empirical evidence","volume":"2","author":"DellaVigna","year":"2010","journal-title":"Annu. Rev. Econ."},{"key":"10.1016\/j.csl.2026.101991_b16","series-title":"Zero-shot persuasive chatbots with LLM-generated strategies and information retrieval","author":"Furumai","year":"2024"},{"key":"10.1016\/j.csl.2026.101991_b17","series-title":"The pile: An 800gb dataset of diverse text for language modeling","author":"Gao","year":"2020"},{"key":"10.1016\/j.csl.2026.101991_b18","series-title":"The llama 3 herd of models","author":"Grattafiori","year":"2024"},{"key":"10.1016\/j.csl.2026.101991_b19","series-title":"Decoupling strategy and generation in negotiation dialogues","author":"He","year":"2018"},{"key":"10.1016\/j.csl.2026.101991_b20","series-title":"Mistral 7B","author":"Jiang","year":"2023"},{"key":"10.1016\/j.csl.2026.101991_b21","series-title":"Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","first-page":"1678","article-title":"Persuading across diverse domains: a dataset and persuasion large language model","author":"Jin","year":"2024"},{"issue":"CSCW1","key":"10.1016\/j.csl.2026.101991_b22","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3579592","article-title":"Working with AI to persuade: Examining a large language model\u2019s ability to generate pro-vaccination messages","volume":"7","author":"Karinshak","year":"2023","journal-title":"Proc. ACM Human-Computer Interact."},{"key":"10.1016\/j.csl.2026.101991_b23","series-title":"2016 4th International Conference on Cyber and IT Service Management","first-page":"1","article-title":"Cosine similarity to determine similarity measure: Study case in online essay assessment","author":"Lahitani","year":"2016"},{"issue":"3","key":"10.1016\/j.csl.2026.101991_b24","doi-asserted-by":"crossref","first-page":"1014","DOI":"10.3390\/app14031014","article-title":"Real-time movie recommendation: Integrating persona-based user modeling with NMF and deep neural networks","volume":"14","author":"Lee","year":"2024","journal-title":"Appl. Sci."},{"key":"10.1016\/j.csl.2026.101991_b25","doi-asserted-by":"crossref","unstructured":"Lian, J., Lei, Y., Huang, X., Yao, J., Xu, W., Xie, X., 2024. Recai: Leveraging large language models for next-generation recommender systems. In: Companion Proceedings of the ACM Web Conference 2024. pp. 1031\u20131034.","DOI":"10.1145\/3589335.3651242"},{"key":"10.1016\/j.csl.2026.101991_b26","series-title":"Perconet: News recommendation with explicit persona and contrastive learning","author":"Liu","year":"2023"},{"issue":"1","key":"10.1016\/j.csl.2026.101991_b27","doi-asserted-by":"crossref","first-page":"4692","DOI":"10.1038\/s41598-024-53755-0","article-title":"The potential of generative AI for personalized persuasion at scale","volume":"14","author":"Matz","year":"2024","journal-title":"Sci. Rep."},{"issue":"3","key":"10.1016\/j.csl.2026.101991_b28","doi-asserted-by":"crossref","first-page":"276","DOI":"10.11613\/BM.2012.031","article-title":"Interrater reliability: the kappa statistic","volume":"22","author":"McHugh","year":"2012","journal-title":"Biochem. Medica"},{"key":"10.1016\/j.csl.2026.101991_b29","doi-asserted-by":"crossref","unstructured":"Meguellati, E., Han, L., Bernstein, A., Sadiq, S., Demartini, G., 2024. How good are LLMS in generating personalized advertisements?. In: Companion Proceedings of the ACM Web Conference 2024. pp. 826\u2013829.","DOI":"10.1145\/3589335.3651520"},{"key":"10.1016\/j.csl.2026.101991_b30","series-title":"Llama 3.2-3B-instruct","author":"Meta","year":"2024"},{"key":"10.1016\/j.csl.2026.101991_b31","series-title":"Llama 3.2: Connect 2024 vision for edge and mobile devices","author":"Meta AI","year":"2024"},{"key":"10.1016\/j.csl.2026.101991_b32","series-title":"International Conference on Design Science Research in Information Systems and Technology","first-page":"81","article-title":"Designing a large language model-based coaching intervention for lifestyle behavior change","author":"Meywirth","year":"2024"},{"key":"10.1016\/j.csl.2026.101991_b33","article-title":"An llm-driven chatbot in higher education for databases and information systems","author":"Neumann","year":"2024","journal-title":"IEEE Trans. Educ."},{"key":"10.1016\/j.csl.2026.101991_b34","first-page":"380","article-title":"Using of jaccard coefficient for keywords similarity","volume":"vol. 1","author":"Niwattanakul","year":"2013"},{"key":"10.1016\/j.csl.2026.101991_b35","series-title":"The Handbook of Communication Skills","first-page":"333","article-title":"Persuasion","author":"O\u2019keefe","year":"2006"},{"key":"10.1016\/j.csl.2026.101991_b36","series-title":"GPT-4o mini: Advancing cost-efficient intelligence","author":"OpenAI","year":"2024"},{"key":"10.1016\/j.csl.2026.101991_b37","article-title":"Zero-shot learning with semantic output codes","volume":"22","author":"Palatucci","year":"2009","journal-title":"Adv. Neural Inf. Process. Syst."},{"issue":"7","key":"10.1016\/j.csl.2026.101991_b38","doi-asserted-by":"crossref","first-page":"1763","DOI":"10.1109\/TKDE.2013.168","article-title":"Personalized recommendation combining user interest and social circle","volume":"26","author":"Qian","year":"2013","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"10.1016\/j.csl.2026.101991_b39","first-page":"53728","article-title":"Direct preference optimization: Your language model is secretly a reward model","volume":"36","author":"Rafailov","year":"2023","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.csl.2026.101991_b40","series-title":"International Conference on Neural Information Processing","first-page":"543","article-title":"Introducing multi-modality in persuasive task oriented virtual sales agent","author":"Raut","year":"2022"},{"key":"10.1016\/j.csl.2026.101991_b41","series-title":"A systematic survey of prompt engineering in large language models: Techniques and applications","author":"Sahoo","year":"2024"},{"key":"10.1016\/j.csl.2026.101991_b42","series-title":"2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation","first-page":"1740","article-title":"Persuade me!: A user-based recommendation system approach","author":"S\u00e1nchez-Corcuera","year":"2019"},{"key":"10.1016\/j.csl.2026.101991_b43","series-title":"Large language models can enhance persuasion through linguistic feature alignment","author":"Shin","year":"2024"},{"key":"10.1016\/j.csl.2026.101991_b44","doi-asserted-by":"crossref","first-page":"118775","DOI":"10.1016\/j.eswa.2022.118775","article-title":"Towards personalized persuasive dialogue generation for adversarial task oriented dialogue setting","volume":"213","author":"Tiwari","year":"2023","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.csl.2026.101991_b45","series-title":"Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)","first-page":"1035","article-title":"Persona or context? Towards building context adaptive personalized persuasive virtual sales assistant","author":"Tiwari","year":"2022"},{"key":"10.1016\/j.csl.2026.101991_b46","series-title":"Llama: Open and efficient foundation language models","author":"Touvron","year":"2023"},{"key":"10.1016\/j.csl.2026.101991_b47","series-title":"Zephyr: Direct distillation of LM alignment","author":"Tunstall","year":"2023"},{"key":"10.1016\/j.csl.2026.101991_b48","article-title":"Matching networks for one shot learning","volume":"29","author":"Vinyals","year":"2016","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.csl.2026.101991_b49","series-title":"Qwen2-VL: Enhancing vision-language model\u2019s perception of the world at any resolution","author":"Wang","year":"2024"},{"key":"10.1016\/j.csl.2026.101991_b50","series-title":"Persuasion for good: Towards a personalized persuasive dialogue system for social good","author":"Wang","year":"2019"},{"key":"10.1016\/j.csl.2026.101991_b51","series-title":"GPT-J-6B: A 6 billion parameter autoregressive language model","author":"Wang","year":"2021"},{"key":"10.1016\/j.csl.2026.101991_b52","first-page":"24824","article-title":"Chain-of-thought prompting elicits reasoning in large language models","volume":"35","author":"Wei","year":"2022","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.csl.2026.101991_b53","series-title":"MiniCPM-V: A GPT-4V level MLLM on your phone","author":"Yao","year":"2024"},{"key":"10.1016\/j.csl.2026.101991_b54","doi-asserted-by":"crossref","unstructured":"Zhang, A., Chen, Y., Sheng, L., Wang, X., Chua, T.-S., 2024. On generative agents in recommendation. In: Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval. pp. 1807\u20131817.","DOI":"10.1145\/3626772.3657844"},{"key":"10.1016\/j.csl.2026.101991_b55","series-title":"Personalizing dialogue agents: I have a dog, do you have pets too?","author":"Zhang","year":"2018"},{"key":"10.1016\/j.csl.2026.101991_b56","series-title":"Bertscore: Evaluating text generation with bert","author":"Zhang","year":"2019"},{"key":"10.1016\/j.csl.2026.101991_b57","first-page":"46595","article-title":"Judging llm-as-a-judge with mt-bench and chatbot arena","volume":"36","author":"Zheng","year":"2023","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.csl.2026.101991_b58","series-title":"Fine-tuning language models from human preferences","author":"Ziegler","year":"2019"}],"container-title":["Computer Speech &amp; Language"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0885230826000549?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0885230826000549?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T12:41:14Z","timestamp":1778244074000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0885230826000549"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2027,1]]},"references-count":58,"alternative-id":["S0885230826000549"],"URL":"https:\/\/doi.org\/10.1016\/j.csl.2026.101991","relation":{},"ISSN":["0885-2308"],"issn-type":[{"value":"0885-2308","type":"print"}],"subject":[],"published":{"date-parts":[[2027,1]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Can language models persuade? Exploring the persuasive efficacy of Large Language and Vision Language models","name":"articletitle","label":"Article Title"},{"value":"Computer Speech & Language","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.csl.2026.101991","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"101991"}}