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

This story is from 2026-09-14. It is preserved in the archive; the latest stories are on the live feed.

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 real-world meetings a…

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  1. 2026-09-14 04:00 · arXiv cs.AI
    GLARE: Generative Learning via Adversarial Reward Estimation For Social Dynamics Forecasting

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