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arXiv — cs.AI

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GLARE: Generative Learning via Adversarial Reward Estimation For Social Dynamics Forecasting

arXiv:2609.12165v1 Announce Type: new Abstract: Meeting continuation requires tracking the agenda, speaker roles, participant intentions, and disagreement across long multi-party discussions. We introduce the Meeting Dynamic Forecasting Benchmark (MDFB), constructed from 2,207…

arXiv — cs.AIBy: Tenghao Huang, Zhaoxuan Tan, Muhao Chen, Jonathan May, Mengting Wan, Longqi Yang, Pei Zhou, Sihao ChenSeptember 14, 2026 (Sep 14)
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  • arXiv:2609.12165v1 Announce Type: new Abstract: Meeting continuation requires tracking the agenda, speaker roles, participant intentions, and disagreement across long multi-party discussions
  • We introduce the Meeting Dynamic Forecasting Benchmark (MDFB), constructed from 2,207…
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GLARE: Generative Learning via Adversarial Reward Estimation For Social Dynamics Forecasting

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