Papers by Xirong Li

3 papers
Article Reranking by Memory-Enhanced Key Sentence Matching for Detecting Previously Fact-Checked Claims (2021.acl-long)

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Challenge: Existing methods to detect false claims ignore the characteristics of FC-articles . claims are often quoted to describe checked events, providing lexical information . sentence templates to introduce or debunk claims are common across articles, providing pattern information.
Approach: They propose a model to rerank FC-articles using key sentences and pattern information.
Outcome: The proposed model outperforms existing methods on two real-world datasets showing that key sentences can be used to predict if an article fact-checks the given claim.
Tackling Long Code Search with Splitting, Encoding, and Aggregating (2024.lrec-main)

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Challenge: Existing pretraining models take the first 256 tokens of code snippets by default, limiting the input length to 512.
Approach: They propose a baseline SEA model which splits long code into code blocks and aggregates them to obtain a comprehensive long code representation.
Outcome: The proposed model can model long code without changing their internal structure and re-pretraining.
Mitigating Hallucination in Multimodal Large Language Model via Hallucination-targeted Direct Preference Optimization (2025.findings-acl)

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Challenge: Multimodal Large Language Models (MLLMs) are known to hallucinate, which limits their practical applications.
Approach: They propose a method that uses three types of preference pairs to target hallucinations from their diverse forms and causes.
Outcome: The proposed method surpasses most state-of-the-art methods and shows potential for further improvements.

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