{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T16:43:55Z","timestamp":1782924235975,"version":"3.54.5"},"reference-count":10,"publisher":"Association for Computing Machinery (ACM)","issue":"2","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/publication-rights-and-licensing-policy"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["SIGecom Exch."],"published-print":{"date-parts":[[2026,1,1]]},"abstract":"<jats:p>This annotated reading list surveys emerging works at the intersection of information design and large language models (LLMs). While classical information design theory studies signaling in abstract mathematical models, real-world communication often occurs in natural language. We highlight papers that use LLMs to elicit and communicate information through natural-language messages, cover techniques used in \"information design + LLM\" research such as language-space optimization and LLM proxies, and discuss papers on LLM persuasion. We aim to illustrate the potential of LLMs to bridge the gap between the theory and practice of information design.<\/jats:p>","DOI":"10.1145\/3817099.3817106","type":"journal-article","created":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T15:43:59Z","timestamp":1782920639000},"page":"85-89","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Information Design with Large Language Models: An Annotated Reading List"],"prefix":"10.1145","volume":"23","author":[{"given":"Tao","family":"Lin","sequence":"first","affiliation":[{"name":"The Chinese University of Hong Kong, Shenzhen"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Safwan","family":"Hossain","sequence":"additional","affiliation":[{"name":"Harvard University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yiling","family":"Chen","sequence":"additional","affiliation":[{"name":"Harvard University"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2026,7,1]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1609\/icwsm.v18i1.31304"},{"key":"e_1_2_1_2_1","unstructured":"Duetting P. Hossain S. Lin T. Leme R. P. Ravindranath S. S. Xu H. and Zuo S. 2025. Information Design With Large Language Models. CoRR abs\/2509.25565."},{"key":"e_1_2_1_3_1","volume-title":"Proceedings of the 25th ACM Conference on Economics and Computation. ACM, New Haven CT USA, 614\u2013615","author":"Filippas A.","unstructured":"Filippas, A., Horton, J. J., and Manning, B. S. 2024. Large Language Models as Simulated Economic Agents: What Can We Learn from Homo Silicus? In Proceedings of the 25th ACM Conference on Economics and Computation. ACM, New Haven CT USA, 614\u2013615."},{"key":"e_1_2_1_4_1","unstructured":"Harris K. Immorlica N. Lucier B. and Slivkins A. 2023. Algorithmic Persuasion Through Simulation. CoRR abs\/2311.18138."},{"key":"e_1_2_1_5_1","unstructured":"Li W. Lin Y. Wang X. Jin B. Zha H. and Wang B. 2025. Verbalized Bayesian Persuasion. CoRR abs\/2502.01587."},{"key":"e_1_2_1_6_1","unstructured":"Rogiers A. Noels S. Buyl M. and Bie T. D. 2024. Persuasion with Large Language Models: a Survey. CoRR abs\/2411.06837."},{"key":"e_1_2_1_7_1","unstructured":"Soumalias E. Jiang Y. Zhu K. Curry M. Seuken S. and Parkes D. C. 2025. LLM-Powered Preference Elicitation in Combinatorial Assignment. CoRR abs\/2502.10308."},{"key":"e_1_2_1_8_1","doi-asserted-by":"crossref","unstructured":"Wu J. Yang C. Wu Y. Mahns S. Wang C. Zhu H. Fang F. and Xu H. 2025. AI Realtor: Towards Grounded Persuasive Language Generation for Automated Copywriting. CoRR abs\/2502.16810.","DOI":"10.1145\/3786335.3813172"},{"key":"e_1_2_1_9_1","volume-title":"Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Association for Computational Linguistics","author":"Xu R.","unstructured":"Xu, R., Lin, B., Yang, S., Zhang, T., Shi, W., Zhang, T., Fang, Z., Xu, W., and Qiu, H. 2024. The Earth is Flat because...: Investigating LLMs' Belief towards Misinformation via Persuasive Conversation. In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Association for Computational Linguistics, Bangkok, Thailand, 16259\u201316303."},{"key":"e_1_2_1_10_1","volume-title":"The Twelfth International Conference on Learning Representations.","author":"Yang C.","unstructured":"Yang, C., Wang, X., Lu, Y., Liu, H., Le, Q. V., Zhou, D., and Chen, X. 2024. Large Language Models as Optimizers. In The Twelfth International Conference on Learning Representations."}],"container-title":["ACM SIGecom Exchanges"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3817099.3817106","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T15:45:18Z","timestamp":1782920718000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3817099.3817106"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1,1]]},"references-count":10,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2026,1,1]]}},"alternative-id":["10.1145\/3817099.3817106"],"URL":"https:\/\/doi.org\/10.1145\/3817099.3817106","relation":{},"ISSN":["1551-9031"],"issn-type":[{"value":"1551-9031","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1,1]]},"assertion":[{"value":"2026-07-01","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}