Papers by Shun Jiang

3 papers
Doc2EDAG: An End-to-End Document-level Framework for Chinese Financial Event Extraction (D19-1)

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Challenge: Existing event extraction methods are limited to extract event arguments within the sentence scope.
Approach: They propose a model which generates an entity-based directed acyclic graph to fulfill document-level EE effectively.
Outcome: The proposed model can generate entity-based directed acyclic graph to fulfill document-level EE effectively.
Revisiting the Evaluation of End-to-end Event Extraction (2021.findings-acl)

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Challenge: Existing EE research uses the role-averaged evaluation metric, but it is misleading to downstream applications.
Approach: They propose two new evaluation metrics that explicitly penalize wrongly identified event arguments.
Outcome: The proposed evaluation metrics improve the initial evaluation by 10% . the proposed training scheme is better than the existing one, the authors show .
Disambiguation in Conversational Question Answering in the Era of LLMs and Agents: A Survey (2025.emnlp-main)

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Challenge: Existing literature on ambiguity and disambiguation with Large Language Models (LLMs) ambiguities are a fundamental challenge in human-AI interactions due to complexity and flexibility of human language.
Approach: They propose to define key terms and concepts and categorize various disambiguation approaches enabled by LLMs and provide a comparative analysis of their advantages and disadvantages.
Outcome: The proposed frameworks are compared against different disambiguation approaches and highlight their relevance for future research.

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