Papers by Xien Liu

2 papers
Table-based Fact Verification with Self-adaptive Mixture of Experts (2022.findings-acl)

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Challenge: Existing research focuses on table-based fact verification, but a new trend is extending the scope to structured evidence.
Approach: They propose a mixture-of-experts neural network to recognize and execute different types of reasoning . they use a management module to decide the contribution of each expert network to the verification result .
Outcome: The proposed method achieves 85.1% accuracy on the TabFact dataset, comparable with the previous state-of-the-art models.
LLM Sensitivity Evaluation Framework for Clinical Diagnosis (2025.coling-main)

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Challenge: Existing studies on the sensitivity of Large Language Models (LLMs) to irrelevant contexts neglect the importance of key information.
Approach: They investigate the sensitivity of large language models to key medical information by introducing different perturbation strategies to investigate their sensitivity.
Outcome: The proposed models are based on three LLMs, namely GPT-3.5, GPT-4, Gemini, Claude3 and LLaMA2-7b, and demonstrate their reliability and sensitivity to medical information.

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