Papers by Changcheng Li

2 papers
GEAR: Graph-based Evidence Aggregating and Reasoning for Fact Verification (P19-1)

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Challenge: Existing methods to extract information from evidence are unable to grasp relational and logical information among the evidence.
Approach: They propose a graph-based evidence aggregating and reasoning framework to integrate evidence from multiple pieces of evidence.
Outcome: The proposed framework achieves significant performance improvements on a large-scale benchmark dataset.
A Syntactic and Semantic Probe into Language Evolution based on Large Language Models (2026.findings-acl)

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Challenge: Existing studies on language evolution have relied on manual annotated resources and rely on dependency parsing.
Approach: They propose to use attention-based structural distance and semantic space distance to measure language development.
Outcome: The proposed measures show that human and LLMs share common characteristics in language processing.

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