Papers by Jia-Nan Li
A Survey on Personalized Alignment—The Missing Piece for Large Language Models in Real-World Applications (2025.findings-acl)
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| Challenge: | Large Language Models (LLMs) have demonstrated remarkable capabilities, yet their transition to real-world applications reveals a critical limitation: the inability to adapt to individual preferences while maintaining alignment with universal human values. |
| Approach: | They propose a framework that enables LLMs to adapt their behavior within ethical boundaries based on individual preferences. |
| Outcome: | The proposed framework analyzes implementation approaches and evaluates their effectiveness across various scenarios. |
From 1,000,000 Users to Every User: Scaling Up Personalized Preference for User-level Alignment (2026.acl-long)
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| Challenge: | Current approaches to align large language models assume uniform human preferences, overlooking the diversity inherent in human populations. |
| Approach: | They propose a framework for scalable personalized alignment of large language models . they establish a preference space characterizing psychological and behavioral dimensions . |
| Outcome: | The proposed framework improves on existing methods with an average of 17.06% accuracy gain across four benchmarks and a strong adaptation capability to novel preferences. |