Papers by Yuanyuan Feng

2 papers
SEP-MLDC: A Simple and Effective Paradigm for Multi-Label Document Classification (2025.findings-naacl)

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Challenge: Existing methods focus on optimizing document features, overlooking the potential of high-quality label features to enhance classification performance.
Approach: They propose a multi-label document classification paradigm that utilizes large language models to expand the label content and generate pseudo-samples for the tail categories.
Outcome: The proposed method significantly outperforms state-of-the-art models.
Beyond Fixed Psychological Personas: State Beats Trait, but Language Models are State-Blind (2026.findings-acl)

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Challenge: Existing persona datasets capture only trait, and ignore impact of state.
Approach: They use a Reddit dataset to study user interactions with language models . they find that existing persona datasets capture only trait and ignore impact of state .
Outcome: The proposed dataset decomposes variance and finds that LLMs are state-blind . the reward models react to user state, but inconsistently, the authors say .

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