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20 results for “Complex Social Behavior dataset”

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cs.CVcs.AIEmpiricalRecentJul 10, 2026

Evolution of Accuracy and Visual-Cognitive Errors in a Decade of Vision-Language AI Models

Shravan Murlidaran, Miguel P. Eckstein

This paper introduces the Complex Social Behavior (CSB) dataset and evaluates the progress of scene description accuracy in vision language models (VLMs) from 2017 to 2025. The authors find that MLLMs…

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cs.HCcs.MMDatasetRecentJul 15, 2026

VIP-MINGLE: A Corpus for Videoconference and In-Person Multimodal Interaction in Group Language Engagement

Andrew Chang, Abhinay K Bodi, Wenxin Deng, Junrui Huang +5 more

The paper introduces VIP-MINGLE, a multimodal dataset of 59 hours of group conversations in both in-person and videoconferencing settings, with raw data, psychometric data, processed features, and ann…

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cs.CLcs.AIcs.HCRecentMay 28, 2026

EUDAIMONIA: Evaluating Undesirable Dynamics in AI

Jun Rui Huang, Wang Bill Zhu, Ziyi Liu, Nathanael Fast +2 more

The paper introduces EUDAIMONIA, a new framework and benchmark for evaluating how well LLMs align with user welfare in social interactions, finding that even state-of-the-art models frequently violate…

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cs.AIRecentJun 1, 2026

Tracking the Behavioral Trajectories of Adapting Agents

Jonah Leshin, Manish Shah, Ian Timmis

The paper introduces a framework to quantitatively measure evolving agent behaviors (traits) by analyzing changes in their configuration text files, achieving high accuracy in classifying behavioral s…

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cs.AIcs.CLRecentMay 27, 2026

Adopt $\neq$ Adapt: Longitudinal Analyses of LLM Conversations in the Wild

Rebecca M. M. Hicke, Kiran Tomlinson

Analyzing longitudinal data from 12,000 Copilot users, the paper finds that individual user habits regarding LLM interaction are highly sticky and difficult to change, and that existing datasets may o…

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cs.CLSurveyRecentJul 3, 2026

Mental Health Disorder Detection Beyond Social Media: A Systematic Review of Available Datasets

Sadiya Sayara Chowdhury Puspo, Ana-Maria Bucur, Stevie Chancellor, Özlem Uzuner +1 more

This paper conducts a systematic review of non-social media, free-text datasets for mental health research, revealing their predominant focus on English and depression detection, and identifying key g…

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cs.IREmpiricalRecentJul 8, 2026

Granularity in Actoin: Graphing sources for social history

Sofus Landor Dam, Johan Heinsen

This paper presents a pipeline for transforming historical sources into structured data using machine learning tools and the GRAM-framework, enabling automated, skeletal graphing of actions.

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cs.MAcs.AIcs.LGRecentMay 28, 2026

Discovering Cooperative Pipelines: Autoresearch for Sequential Social Dilemmas

Víctor Gallego

The paper introduces an outer-loop AI agent that autonomously redesigns LLM policy-synthesis pipelines for multi-agent social dilemmas, demonstrating that the optimal pipeline structure depends critic…

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cs.CLcs.AIEmpiricalRecentJun 29, 2026

TRACE: Temporal Relationship-Aware Conversational Entrainment Detection in Dyadic Speech

Sathvik Manikantan Napa Ugandhar, Hao Zhang, Alison Gunzler, Yuzhe Wang +4 more

This paper introduces DyadEE, a dataset for emotional entrainment detection in conversational interactions, and TRACE, a window-level framework for modeling dyadic interaction using emotion fine-tuned…

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cs.HCEmpiricalRecentJul 15, 2026

Interaction Density as a Behavioural Signature of Exhibit Type: A Minimal-Log Study from a Two-Venue Science Experience Centre

R A Udaya Rakshith, Inavamsi Enaganti, Umang J Gala

This paper analyzes interaction data from touch-enabled exhibits at a science center to derive a behavioral signature called interaction density and uses it to distinguish between fast-paced games and…

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cs.CLDatasetRecentJul 16, 2026

TikStance: A Multimodal and Hierarchical Dataset for Multi-target Stance Analysis in TikTok Political Conversations

Yazhi Zhang, Fuqiang Niu, Bowen Zhang

The paper introduces TikStance, a multimodal and context-aware dataset for stance detection in political discussions on TikTok.

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cs.CLRecentJun 1, 2026

Beyond Isolated Behaviors: Hierarchical User Modeling for LLM Personalization

Liang Wang, Xinyi Mou, Xiaoyou Liu, Tiannan Wang +2 more

The paper proposes a hierarchical framework, PHF (Practice-Habitus-Field), inspired by Bourdieu's Theory of Practice, to improve LLM personalization by modeling user behaviors at three distinct levels…

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cs.AIcs.CLRecentMay 28, 2026

Teaching Values to Machines: Simulating Human-Like Behavior in LLMs

Asaf Yehudai, Naama Rozen, Ariel Gera

The paper successfully demonstrates that Large Language Models (LLMs) can be induced to adopt coherent, human-like value structures, showing strong alignment with human psychological patterns.

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cs.AIRecentMay 28, 2026

NICE: A Theory-Grounded Diagnostic Benchmark for Social Intelligence of LLMs

Yunjin Qi, Zhaojun Jiang, Xuan Wu, Hanxi Pan +9 more

The paper introduces NICE, a novel, theory-grounded diagnostic benchmark for assessing the social intelligence of LLMs, which reveals that current frontier models consistently struggle with specific f…

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cs.AIRecentMay 27, 2026

Human-like in-group bias in instruction-tuned language model agents

Messi H. J. Lee

This study demonstrates that instruction-tuned language model agents exhibit robust, group-contingent in-group bias, structurally mimicking human social biases, even when standard action logs fail to…

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cs.CRcs.AIcs.CVRecentMay 11, 2026

BEACON: A Multimodal Dataset for Learning Behavioral Fingerprints from Gameplay Data

Ishpuneet Singh, Gursmeep Kaur, Uday Pratap Singh Atwal, Guramrit Singh +2 more

The paper introduces BEACON, a large-scale, multimodal dataset capturing diverse behavioral signals from competitive Valorant gameplay, designed for rigorous testing of continuous authentication and b…

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cs.CRRecentJun 4, 2026

Cheating in Multiplayer Online Games: a Dataset

Hugo Bertin, Marc Dacier, Yérom-David Bromberg

This paper introduces a novel, comprehensive dataset that logs various cheating activities, including difficult-to-detect network flow disruption cheats, for the purpose of developing robust detection…

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