{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/escot-towards-interpretable-emotional-support","title":"ESCoT: Towards Interpretable Emotional Support Dialogue Systems","arxiv_id":"2406.10960","date":"2024-06-16","proceeding":null,"authors":["Tenggan Zhang","Xinjie Zhang","Jinming Zhao","Li Zhou","Qin Jin"],"abstract":"Understanding the reason for emotional support response is crucial for establishing connections between users and emotional support dialogue systems. Previous works mostly focus on generating better responses but ignore interpretability, which is extremely important for constructing reliable dialogue systems. To empower the system with better interpretability, we propose an emotional support response generation scheme, named $\\textbf{E}$motion-Focused and $\\textbf{S}$trategy-Driven $\\textbf{C}$hain-$\\textbf{o}$f-$\\textbf{T}$hought ($\\textbf{ESCoT}$), mimicking the process of $\\textit{identifying}$, $\\textit{understanding}$, and $\\textit{regulating}$ emotions. Specially, we construct a new dataset with ESCoT in two steps: (1) $\\textit{Dialogue Generation}$ where we first generate diverse conversation situations, then enhance dialogue generation using richer emotional support strategies based on these situations; (2) $\\textit{Chain Supplement}$ where we focus on supplementing selected dialogues with elements such as emotion, stimuli, appraisal, and strategy reason, forming the manually verified chains. Additionally, we further develop a model to generate dialogue responses with better interpretability. We also conduct extensive experiments and human evaluations to validate the effectiveness of the proposed ESCoT and generated dialogue responses. Our data and code are available at $\\href{https://github.com/TeigenZhang/ESCoT}{https://github.com/TeigenZhang/ESCoT}$.","url_abs":"https://arxiv.org/abs/2406.10960v1","url_pdf":"https://arxiv.org/pdf/2406.10960v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"escot-towards-interpretable-emotional-support","repo_url":"https://github.com/teigenzhang/escot","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"ok"}}],"tasks":[{"task_slug":"dialogue-generation","task_name":"Dialogue Generation"},{"task_slug":"response-generation","task_name":"Response Generation"}],"methods":[{"method_slug":"focus","method_name":"Focus"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=2406.10960","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2406.10960"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. 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