GLARE: Generative Learning via Adversarial Reward Estimation for social dynamics forecasting; introduces the Meeting Dynamic Forecasting Benchmark (MDFB) using 2,207 real-world meetings and 24,794 future-facing queries
Read the original at arxiv.org→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...
Original headline: "GLARE: Generative Learning via Adversarial Reward Estimation For Social Dynamics Forecasting"
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- Sep 14, 04:00 UTC arXiv cs.AI lead source GLARE: Generative Learning via Adversarial Reward Estimation For Social Dynamics Forecasting