Papers by Junfei Cheng

2 papers
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.
Intention Knowledge Graph Construction for User Intention Relation Modeling (2026.eacl-long)

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Challenge: Existing knowledge graphs focus on connecting intentions but lacks the ability to model the relationships between different intentions.
Approach: They propose a framework to automatically generate an intention knowledge graph, capturing connections between user intentions.
Outcome: The proposed model outperforms state-of-the-art methods and shows its utility.

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