Papers by Changxuan Wan

5 papers
Event Pattern-Instance Graph: A Multi-Round Role Representation Learning Strategy for Document-Level Event Argument Extraction (2025.findings-acl)

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Challenge: Existing role-based span selection strategies ignore interrelations between events . authors propose a multi-round role representation learning strategy for document-level event argument extraction .
Approach: They propose a pattern-instance graph to capture role semantics embedded in various associations . they also propose re-inventing the role representations learned from previous analyzed documents .
Outcome: The proposed model captures role semantics embedded in various associations . iteratively updates representations of role nodes and edges to enrich their semantic information . the model improves prediction performance in subsequent rounds of span selection .
Enhancing Text-to-SQL Capabilities of Large Language Models through Tailored Promptings (2024.lrec-main)

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Challenge: Large language models with prompting have achieved encouraging results on many natural language processing tasks due to the absence of task-tailored promptings.
Approach: They propose three promptings specifically designed for Text-to-SQL: SL-prompt, CC-promped, and SL+CC prompt.
Outcome: The proposed promptings achieve execution accuracy of 86.2% and test-suite accuracy of 76% . the granularity of schema linking and the order of clause generation have great impact on performance, which are considered little in previous research.
OEE-CFC: A Dataset for Open Event Extraction from Chinese Financial Commentary (2024.findings-emnlp)

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Challenge: Existing corpora with unconventional entities serving as event arguments lack rich multi-events and shared arguments.
Approach: They develop an open event template that includes 21 event argument roles and an open corpus supporting open event extraction.
Outcome: The proposed corpus includes 17,469 events, 44,221 arguments, 3,644 complex arguments, and 5,898 shared arguments.
FaStFact: Faster, Stronger Long-Form Factuality Evaluations in LLMs (2025.findings-emnlp)

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Challenge: Prior evaluation pipelines fail to evaluate factuality of long-form LLMs due to inefficiency and costly human assessment.
Approach: They propose a fast and strong evaluation pipeline that can evaluate factuality of long-form LLMs . they propose 'faStFact' to reduce cost of web searching and inference calling .
Outcome: The proposed evaluation pipeline achieves highest alignment with human evaluation and efficiency among existing baselines.
Joint Document-Level Event Extraction via Token-Token Bidirectional Event Completed Graph (2023.acl-long)

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Challenge: a joint exaction method can be used to extract document-level event records . it avoids inefficiency and error propagation issues in traditional pipeline methods .
Approach: They propose a joint exaction method that can avoid inefficiency and error propagation issues . they propose eType-Role1-Roul2 as the edge type to reveal which tokens play argument roles .
Outcome: The proposed method can avoid inefficiency and error propagation issues in traditional pipeline methods.

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