Papers by Yuanzhao Zhai

2 papers
EvoNarrator: Modeling Scientific Evolution for Feasible Hypothesis Generation (2026.acl-long)

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Challenge: Scientific discovery evolution does not occur ex nihilo but is characterized by structural deepening and reconfiguration of existing functionalities.
Approach: They propose a framework for hypothesis generation based on evolutionary narratives . they extract structured P-M-L-F quadruples from citation networks and introduce a mechanism to assess their semantic compatibility.
Outcome: The proposed framework reduces logical disconnects by evaluating its semantic compatibility.
COPR: Continual Human Preference Learning via Optimal Policy Regularization (2025.findings-acl)

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Challenge: Reinforcement Learning from Human Feedback (RLHF) is effective for aligning Large Language Models with human preferences, but its complex process limits its ability to continually learn human feedback.
Approach: They propose a non-RL offline method to convert historical optimal policies into optimization constraints when continually learning new preferences.
Outcome: The proposed method outperforms strong CL baselines in terms of reward-based evaluations and human assessment.

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