Papers by Bihan Zhou

3 papers
RuleEdit: Towards Rule-Level Knowledge Generalization to Mitigate Over-Editing in Large Language Models (2025.findings-acl)

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Challenge: Existing knowledge editing methods focus on instance-level editing, which is prone to knowledge degradation and general ability deterioration due to redundant instance-specific modifications.
Approach: They propose a rule-level editing method that generalizes rule-derived knowledge to update rule-based instances.
Outcome: The proposed method improves portability and performance over baselines for LLaMA-2-7B on RULEmix.
Video-Text Prompting for Weakly Supervised Spatio-Temporal Video Grounding (2024.emnlp-main)

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Challenge: Existing methods extract each candidate tube feature independently by cropping objects from video frame feature, discarding all contextual information such as position change and inter-entity relationship.
Approach: They propose to use video-text prompts to construct candidate feature instead of cropping tube region from feature map . they also propose negative contrastive samples whose candidate object is erased instead of being highlighted .
Outcome: The proposed methods surpass existing weakly-supervised methods by a great margin . they draw visual markers over objects tubes as video prompts .
Constructing Procedural Graphs with Multiple Dependency Relations: A New Dataset and Baseline (2023.findings-acl)

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Challenge: Existing methods to structure procedural knowledge focus on representing descriptive knowledge but ignore another commonsense knowledge-Procedural Knowledge.
Approach: They propose to generate flow graphs from procedural documents by extracting sequential dependency between sentences and missing two important dependencies in procedural document.
Outcome: The proposed method can generate flow graphs from unstructured documents with syntactic information and discourse structures.

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