Papers by Zhulin Tao

    1 papers
    Scattered Hypothesis Generation for Open-Ended Event Forecasting (2026.findings-acl)

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    Challenge: Existing methods for event forecasting focus on the most probable outcomes, neglecting the intrinsic uncertainty of real-world events.
    Approach: They propose a reinforcement learning framework that optimizes inclusiveness and diversity of the hypothesis by integrating validity-gated score into the overall objective.
    Outcome: The proposed framework outperforms baselines on two real-world benchmark datasets.

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