Papers by Xinleishi Xinleishi
AutoQual: An LLM Agent for Automated Discovery of Interpretable Features for Review Quality Assessment (2025.emnlp-industry)
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| Challenge: | Existing methods for assessing review quality are unscalable across domains and fail to adapt to evolving content patterns. |
| Approach: | They propose an LLM-based agent framework that automates the discovery of interpretable features. |
| Outcome: | The proposed framework improves on a large-scale online platform with a billion-level user base. |
Open-Set Living Need Prediction with Large Language Models (2025.findings-acl)
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Xiaochong Lan, Jie Feng, Yizhou Sun, Chen Gao, Jiahuan Lei, Xinleishi Xinleishi, Hengliang Luo, Yong Li
| Challenge: | Existing approaches to living need prediction treat it as a closed-set classification problem, severely limiting their ability to capture diversity and complexity of living needs. |
| Approach: | They propose a system leveraging large language models for unrestricted need prediction that leverages Maslow's hierarchy of needs to align predictions with human living needs. |
| Outcome: | The proposed system outperforms closed-set approaches on need-based life service recall by an average of 19.37% on real-world datasets. |