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New TIDES dataset enhances AI's understanding of multi-party conversations

By PulseAugur Editorial · [1 sources] ·

Researchers have introduced TIDES, a new longitudinal dataset designed to improve the modeling of multi-party social dynamics in group conversations. This dataset comprises over 75,000 utterances in English and Korean from 12 university project teams over a full semester, offering a naturalistic view of team evolution. Experiments show that fine-tuning models on TIDES enhances next-speaker prediction and performs comparably to proprietary models on benchmarks like the AMI Meeting Corpus, though human evaluations indicate that improved prediction doesn't always lead to more natural-sounding dialogue. AI

IMPACT Improves AI's ability to model complex group conversations and team dynamics.

RANK_REASON The cluster contains a research paper detailing a new dataset and experimental results. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New TIDES dataset enhances AI's understanding of multi-party conversations

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The cluster contains a research paper detailing a new dataset and experimental results. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Heechan Lee, Jeonggyu Kang, Junho Myung, Jaywoong Jeong, Juho Kim, Joseph Seering ·

    TIDES: A Longitudinal Bilingual Dataset for Modeling Multi-Party Social Dynamics

    arXiv:2608.01724v1 Announce Type: new Abstract: Group conversations are fundamental to human collaboration, yet standard large language models (LLMs) still struggle with the complexities of multi-party interaction. This challenge persists in part because existing group conversati…

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