Papers by Jinxian Qu

1 papers
Dream to Chat: Model-based Reinforcement Learning on Dialogues with User Belief Modeling (2025.findings-emnlp)

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Challenge: a framework for constructing dialogue world models for natural language tasks is currently lacking.
Approach: They propose a framework that can be used to train a dialogue world model.
Outcome: The proposed framework can predict future utterances and user beliefs . it can achieve state-of-the-art performance on emotion classification and sentiment identification .

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