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New COSI-Lab dataset models multi-perspective social intentions

Researchers have introduced COSI-Lab, a novel dataset and framework designed to model multi-perspective social intentions in complex environments. This dataset captures interactions from a scientific workshop, focusing on Apparent Intent Inference (AII) by considering observers' interpretative tendencies. COSI-Lab aims to equip future intelligent systems with better subjective perception capabilities by treating the multiplicity of intentions as explainable, perspective-driven reasoning rather than mere label noise. The project includes a new annotation process for AII, quantitative and qualitative analyses of intent narratives, benchmark tasks, and multimodal data for behavior analysis. AI

IMPACT This research could lead to AI systems that better understand and interpret complex human social dynamics and intentions.

RANK_REASON The cluster describes a new academic paper and dataset release. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

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New COSI-Lab dataset models multi-perspective social intentions

COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · 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-Quir\'os, Anne L. J. ter Wa… ·

    COSI-Lab: Conference Living Lab for Modeling Multi-Perspective Multimodal Social Intention

    arXiv:2607.28649v1 Announce Type: cross Abstract: COSI-Lab presents a multimodal, multi-sensor dataset of an interdisciplinary scientific workshop containing 32 academics at an international conference. It captures ecologically valid social interactions in a weakly scripted setti…