{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T00:30:09Z","timestamp":1775694609247,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":28,"publisher":"ACM","funder":[{"name":"The Ministry of Economic Development of the Russian Federation","award":["agreement identifier 000000C313925P4H0002; grant No 139-15-2025-012"],"award-info":[{"award-number":["agreement identifier 000000C313925P4H0002; grant No 139-15-2025-012"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,10,27]]},"DOI":"10.1145\/3746027.3754468","type":"proceedings-article","created":{"date-parts":[[2025,10,25]],"date-time":"2025-10-25T06:54:17Z","timestamp":1761375257000},"page":"13501-13503","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["HL-EAI: A Multimodal Framework Enabling Emotional Reciprocity in Human-AI Strategic Decision-Making"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0594-867X","authenticated-orcid":false,"given":"Mikhail","family":"Mozikov","sequence":"first","affiliation":[{"name":"Artificial Intelligence Research Institute, Moscow, Russian Federation and Ivannikov Institute for System Programming, Moscow, Russian Federation"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-8317-8820","authenticated-orcid":false,"given":"Daniil","family":"Orekhov","sequence":"additional","affiliation":[{"name":"National Research University Higher School of Economics, Moscow, Russian Federation"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-3292-8479","authenticated-orcid":false,"given":"Ivan","family":"Nasonov","sequence":"additional","affiliation":[{"name":"Moscow Institute of Physics and Technology, Moscow, Russian Federation"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-8473-7602","authenticated-orcid":false,"given":"Konstantin","family":"Baltsat","sequence":"additional","affiliation":[{"name":"Information Technologies, Mechanics and Optics University, Saint-Petersburg, Russian Federation"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-5599-9355","authenticated-orcid":false,"given":"Vladislav","family":"Pedashenko","sequence":"additional","affiliation":[{"name":"M. V. Lomonosov Moscow State University, Moscow, Russian Federation"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2682-8722","authenticated-orcid":false,"given":"Dmitrii","family":"Abramov","sequence":"additional","affiliation":[{"name":"Skolkovo Institute of Science and Technology, Moscow, Russian Federation and M. V. Lomonosov Moscow State University, Moscow, Russian Federation"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9893-3076","authenticated-orcid":false,"given":"Nikita","family":"Severin","sequence":"additional","affiliation":[{"name":"Independent Researcher, Belgrad, Serbia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8135-4622","authenticated-orcid":false,"given":"Yury","family":"Maximov","sequence":"additional","affiliation":[{"name":"LLC Interdata, Astana, Kazakhstan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6196-0564","authenticated-orcid":false,"given":"Andrey","family":"Savchenko","sequence":"additional","affiliation":[{"name":"Sber AI Lab, Moscow, Russian Federation"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3308-8825","authenticated-orcid":false,"given":"Ilya","family":"Makarov","sequence":"additional","affiliation":[{"name":"Artificial Intelligence Research Institute, Moscow, Russian Federation, Ivannikov Institute for System Programming, Moscow, Russian Federation, and Information Technologies, Mechanics and Optics University, Saint-Petersburg, Russian Federation"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,10,27]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Savchenko","author":"Demochkina Polina","year":"2021","unstructured":"Polina Demochkina and Andrey V. Savchenko. 2021. MobileEmotiFace: Efficient facial image representations in video-based emotion recognition on mobile devices. In *Proceedings of International Conference on Pattern Recognition (ICPR) Workshops and Challenges, Part V*. Springer, 266-274."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"crossref","unstructured":"Paul Ekman et al. 1999. Basic emotions. In *Handbook of Cognition and Emotion* 98 45-60.","DOI":"10.1002\/0470013494.ch3"},{"key":"e_1_3_2_1_3_1","volume-title":"AI: A comprehensive review and new perspectives on human-AI alignment. *arXiv preprint arXiv:2412.15114v1*.","author":"Qiyang Sun","year":"2024","unstructured":"Qiyang Sun et al. 2024. Towards friendly AI: A comprehensive review and new perspectives on human-AI alignment. *arXiv preprint arXiv:2412.15114v1*."},{"key":"e_1_3_2_1_4_1","unstructured":"Yuan Zhang et al. 2024. Multimodal emotion recognition by fusing video semantic in MOOC learning scenarios. *arXiv preprint arXiv:2404.07484*."},{"key":"e_1_3_2_1_5_1","volume-title":"From multimodal LLM to human-level AI: Modality, instruction, reasoning and beyond. In *Proceedings of the 32nd ACM International Conference on Multimedia*, 11289-11291","author":"Fei Hao","unstructured":"Hao Fei, Xiangtai Li, Haotian Liu, Fuxiao Liu, Zhuosheng Zhang, Hanwang Zhang, and Shuicheng Yan. 2024. From multimodal LLM to human-level AI: Modality, instruction, reasoning and beyond. In *Proceedings of the 32nd ACM International Conference on Multimedia*, 11289-11291."},{"key":"e_1_3_2_1_6_1","volume-title":"AssistEditor","author":"Gao Difei","unstructured":"Difei Gao, Siyuan Hu, Zechen Bai, Qinghong Lin, and Mike Zheng Shou. 2024. AssistEditor: Multi-agent collaboration for GUI workflow automation in video creation. In *Proceedings of the 32nd ACM International Conference on Multimedia*, 11255-11257."},{"key":"e_1_3_2_1_7_1","volume-title":"WorldGPT: Empowering LLM as multimodal world model. In *Proceedings of the 32nd ACM International Conference on Multimedia*, 7346-7355","author":"Ge Zhiqi","unstructured":"Zhiqi Ge, Hongzhe Huang, Mingze Zhou, Juncheng Li, Guoming Wang, Siliang Tang, and Yueting Zhuang. 2024. WorldGPT: Empowering LLM as multimodal world model. In *Proceedings of the 32nd ACM International Conference on Multimedia*, 7346-7355."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"crossref","unstructured":"Xing Guo Yudong Zhang Siyuan Lu and Zhihai Lu. 2024. Facial expression recognition: A review. *Multimedia Tools and Applications* 83(8) 23689-23735.","DOI":"10.1007\/s11042-023-15982-x"},{"key":"e_1_3_2_1_9_1","volume-title":"Lorenzo Jorge Mart\u00ednez Pazos, and William G\u00f3mez Fern\u00e1ndez","author":"Garc\u00eda Arturo Orellana","year":"2023","unstructured":"Arturo Orellana Garc\u00eda, David Batard, Lorenzo Jorge Mart\u00ednez Pazos, and William G\u00f3mez Fern\u00e1ndez. 2023. Monitoring emotional response during mental health therapy."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.joep.2014.02.002"},{"key":"e_1_3_2_1_11_1","volume-title":"Simone Dalla Bella, and Isabelle Peretz","author":"Khalfa St\u00e9phanie","year":"2008","unstructured":"St\u00e9phanie Khalfa, Mathieu Roy, Pierre Rainville, Simone Dalla Bella, and Isabelle Peretz. 2008. Role of tempo entrainment in psychophysiological differentiation of happy and sad music? *International Journal of Psychophysiology*, 68(1), 17-26."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","unstructured":"Andrea Larney Amanda Rotella and Pat Barclay. 2019. Stake size effects in ultimatum game and dictator game offers: a meta-analysis. *Organizational Behavior and Human Decision Processes* 151 61-72. https:\/\/doi.org\/10.1016\/j.obhdp.2019.01.002.","DOI":"10.1016\/j.obhdp.2019.01.002"},{"key":"e_1_3_2_1_13_1","unstructured":"Zaijing Li Gongwei Chen Rui Shao Yuquan Xie Dongmei Jiang and Liqiang Nie. 2024. Enhancing emotional generation capability of large language models via emotional chain-of-thought. *arXiv preprint arXiv:2401.06836*."},{"key":"e_1_3_2_1_14_1","unstructured":"Mikhail Mozikov et al. 2024. EAI: Emotional decision-making of LLMs in strategic games and ethical dilemmas. In *The Thirty-eighth Annual Conference on Neural Information Processing Systems*. https:\/\/openreview.net\/forum?id=8aAaYEwNR4."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","unstructured":"Carolina P\u00e9rez-Due\u00f1as M. Fernanda Rivas Olusegun A. Oyediran and Francisco Garc\u00eda-Torres. 2018. Induced negative mood increases dictator game giving. *Frontiers in Psychology* 9. https:\/\/doi.org\/10.3389\/fpsyg.2018.01542.","DOI":"10.3389\/fpsyg.2018.01542"},{"key":"e_1_3_2_1_16_1","volume-title":"Mills","author":"Prkachin Kenneth M.","year":"1999","unstructured":"Kenneth M. Prkachin, Rhonda M. Williams-Avery, Caroline Zwaal, and David E. Mills. 1999. Cardiovascular changes during induced emotion: An application of Lang's theory of emotional imagery. *Journal of Psychosomatic Research*, 47(3), 255-267."},{"key":"e_1_3_2_1_17_1","volume-title":"Omni-emotion: Extending video MLLM with detailed face and audio modeling for multimodal emotion analysis. *arXiv preprint arXiv:2501.09502*.","author":"Wei Xihan","year":"2025","unstructured":"Xihan Wei, Qize Yang, Detao Bai, and Yi-Xing Peng. 2025. Omni-emotion: Extending video MLLM with detailed face and audio modeling for multimodal emotion analysis. *arXiv preprint arXiv:2501.09502*."},{"key":"e_1_3_2_1_18_1","first-page":"30119","volume-title":"Proceedings of Machine Learning Research*","volume":"202","author":"Savchenko Andrey","year":"2023","unstructured":"Andrey Savchenko. 2023. Facial expression recognition with adaptive frame rate based on multiple testing correction. In *Proceedings of the 40th International Conference on Machine Learning (ICML), Proceedings of Machine Learning Research*, Vol. 202. Andreas Krause, Emma Brunskill, Kyunghyun Cho, Barbara Engelhardt, Sivan Sabato, and Jonathan Scarlett (Eds.). PMLR, 30119-30129."},{"key":"e_1_3_2_1_19_1","volume-title":"Ad Lingua: Text classification improves symbolism prediction in image advertisements. In *Proceedings of the 28th International Conference on Computational Linguistics*","author":"Savchenko Andrey","year":"2020","unstructured":"Andrey Savchenko, Anton Alekseev, Sejeong Kwon, Elena Tutubalina, Evgeny Myasnikov, and Sergey Nikolenko. 2020. Ad Lingua: Text classification improves symbolism prediction in image advertisements. In *Proceedings of the 28th International Conference on Computational Linguistics*, 1886-1892."},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"crossref","unstructured":"Andrey Savchenko and Lyudmila Savchenko. 2025. Leveraging lightweight facial models and textual modality in audio-visual emotional understanding in-the-wild. In *Proceedings of the Computer Vision and Pattern Recognition Conference* 5778-5788.","DOI":"10.1109\/CVPRW67362.2025.00577"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"crossref","unstructured":"Andrey V. Savchenko. 2024. Leveraging pre-trained multi-task deep models for trustworthy facial analysis in affective behaviour analysis in-the-wild. In *Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition* 4703-4712.","DOI":"10.1109\/CVPRW63382.2024.00473"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"crossref","unstructured":"Andrey V. Savchenko. 2017. Maximum-likelihood dissimilarities in image recognition with deep neural networks. *Computer Optics* 41(3) 422-430.","DOI":"10.18287\/2412-6179-2017-41-3-422-430"},{"key":"e_1_3_2_1_23_1","volume-title":"Multi-task affective behaviour analysis based on MT-EmotiNet models. In *European Conference on Computer Vision*","author":"Savchenko Andrey V.","unstructured":"Andrey V. Savchenko. 2025. Multi-task affective behaviour analysis based on MT-EmotiNet models. In *European Conference on Computer Vision*. Springer, 244-256."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"crossref","unstructured":"Alexandre Schaefer Fr\u00e9d\u00e9ric Nils Xavier Sanchez and Pierre Philippot. 2010. Assessing the effectiveness of a large database of emotion-eliciting films: A new tool for emotion researchers. *Cognition and Emotion* 24(7) 1153-1172.","DOI":"10.1080\/02699930903274322"},{"key":"e_1_3_2_1_25_1","volume-title":"EMOSTIM: A database of emotional film clips with discrete and componential assessment. *IEEE Transactions on Affective Computing*.","author":"Somarathna Rukshani","year":"2023","unstructured":"Rukshani Somarathna, Patrik Vuilleumier, and Gelareh Mohammadi. 2023. EMOSTIM: A database of emotional film clips with discrete and componential assessment. *IEEE Transactions on Affective Computing*."},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jesp.2010.01.007"},{"key":"e_1_3_2_1_27_1","volume-title":"Kiran Ramnath, Sougata Chaudhuri, Shubham Mehrotra, Xiang-Bo Mao, Sitaram Asur, et al.","author":"Wang Zhichao","year":"2024","unstructured":"Zhichao Wang, Bin Bi, Shiva Kumar Pentyala, Kiran Ramnath, Sougata Chaudhuri, Shubham Mehrotra, Xiang-Bo Mao, Sitaram Asur, et al. 2024. A comprehensive survey of LLM alignment techniques: RLHF, RLAIF, PPO, DPO and more. *arXiv preprint arXiv:2407.16216*."},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"crossref","unstructured":"Tao Zhang and Zhenhua Tan. 2024. Survey of deep emotion recognition in dynamic data using facial speech and textual cues. *Multimedia Tools and Applications* 83(25) 66223-66262.","DOI":"10.1007\/s11042-023-17944-9"}],"event":{"name":"MM '25: The 33rd ACM International Conference on Multimedia","location":"Dublin Ireland","acronym":"MM '25","sponsor":["SIGMM ACM Special Interest Group on Multimedia"]},"container-title":["Proceedings of the 33rd ACM International Conference on Multimedia"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3746027.3754468","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,9]],"date-time":"2025-12-09T19:43:45Z","timestamp":1765309425000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3746027.3754468"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,27]]},"references-count":28,"alternative-id":["10.1145\/3746027.3754468","10.1145\/3746027"],"URL":"https:\/\/doi.org\/10.1145\/3746027.3754468","relation":{},"subject":[],"published":{"date-parts":[[2025,10,27]]},"assertion":[{"value":"2025-10-27","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}