COSI-Lab：面向多视角多模态社交意图建模的会议生活实验室
COSI-Lab: Conference Living Lab for Modeling Multi-Perspective Multimodal Social Intention
COSI-Lab 发布了一个真实跨学科学术研讨会的多模态多传感器数据集，涵盖 32 位学者在弱脚本环境下的两场 30 分钟社交互动。研究聚焦由外部观察者判定的表观意图推断（AII）问题，提出将主观感知的多样性建模为可解释的视角驱动推理过程，而非标签噪声。数据集包含面向 AII 的新型标注流程、基准任务、全员语音质量音频以及隐私保护的多模态环境与可穿戴传感器数据。
Authors:Zonghuan Li, Litian Li, Arthur Mercier, Gara Dorta, Balint Dioszegi, Jose Morales-Vargas, Chenxu Hao, Ivan Kondyurin, Vanessa Begemann, Nale Lehmann-Willenbrock, Bernd Dudzik, Saunaq Chakrabarty, Sotiris Vacanas, Laura Cabrera-Quirós, Anne L.J. ter Wal, Vitaliy Popov, Jorge Castro-Godínez, Chirag Raman, Stephanie Tan, Hayley Hung
Abstract:COSI-Lab presents a multimodal multi-sensor dataset of a real interdisciplinary scientific workshop with 32 academics at an international conference. It captures ecologically valid social interactions in a weakly scripted setting consisting of two 30-minute mingling sessions with real professional and social consequences. We argue that intelligent systems could better handle subjective perceptions by modeling their multiplicity not as label noise but as an explainable perspective-driven reasoning process. We focus on the Apparent Intent Inference (AII) problem as determined by ex-situ observers and conceptualize intentions to be independent of the future. We contribute a novel annotation process for AII that accounts for a perceiver's own interpretative tendencies, quantitative and qualitative analyses of intent narratives with respect to diversity, plausibility and grounding, benchmark tasks for AII and relevant contextual factors, speech quality audio for all participants as well as privacy-preserving multi-modal environmental and wearable sensor data, enabling lexical and nonverbal behavior analysis; and the coupling of self-reported participant goals (30 minute to 3 hour) with annotated AII (seconds).
| Subjects: | Human-Computer Interaction (cs.HC); Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2607.28649 [cs.HC] |
| (or arXiv:2607.28649v2 [cs.HC] for this version) | |
| https://doi.org/10.48550/arXiv.2607.28649 arXiv-issued DOI via DataCite |
Submission history
From: Zonghuan Li [view email]
[v1]
Tue, 2 Jun 2026 13:44:54 UTC (9,500 KB)
[v2]
Sun, 11 Oct 2026 15:30:41 UTC (16,757 KB)
来源：arXiv：cs.AI · arxiv.org