Papers by Weixin Li

3 papers
Causal Intervention and Counterfactual Reasoning for Multi-modal Fake News Detection (2023.acl-long)

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Challenge: Existing methods for multi-modal fake news detection neglect the fact that some label-specific features cannot generalize well to the testing set, thus suffering from the latent data bias.
Approach: They propose a Causal intervention and Counterfactual reasoning based debiasing framework for multi-modal fake news detection that eliminates the image-only bias by deducting the direct effect of the image from the total effect on labels.
Outcome: The proposed framework eliminates the psycholinguistic bias in the text and the bias of inferring news label based on only image features.
MemRec: Collaborative Memory-Augmented Agentic Recommender System (2026.acl-long)

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Challenge: Existing recommender systems rely on semantic user and item memories to make predictions, but these memories are kept in isolation.
Approach: They propose a framework that architecturally decouples memory management from reasoning to decouple memory management and reasoning from the user and item memories.
Outcome: The proposed framework decouples memory management from reasoning and achieves state-of-the-art performance on four benchmarks.
Free your mouse! Command Large Language Models to Generate Code to Format Word Documents (2024.emnlp-main)

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Challenge: Recent LLMs have significantly improved code generation, making it increasingly accessible to users.
Approach: They propose an automatic document formatting method, Text-to-Format, driven by various prompting strategies and a high-quality dataset DocFormEval data.
Outcome: The proposed method improves the efficiency and experience of users in formatting the document and improves document formatting task.

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