Xiaotian Lu — accepted AI-conference papers

2024

AHP-Powered LLM Reasoning for Multi-Criteria Evaluation of Open-Ended Responses

Xiaotian Lu, Jiyi Li, Koh Takeuchi, Hisashi Kashima

EMNLP 2024finding

Question answering (QA) tasks have been extensively studied in the field of natural language processing (NLP). Answers to open-ended questions are highly diverse and difficult to quantify, and cannot be simply evaluated as correct or incorrect, unlike close-ended questions with definitive answers. W…

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2024

Evaluating Saliency Explanations in NLP by Crowdsourcing

Xiaotian Lu, Jiyi Li, Zhen Wan, Xiaofeng Lin, Koh Takeuchi, Hisashi Kashima

COLING 2024main

Deep learning models have performed well on many NLP tasks. However, their internal mechanisms are typically difficult for humans to understand. The development of methods to explain models has become a key issue in the reliability of deep learning models in many important applications. Various sali…

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