Papers by Xinting Hu

2 papers
Personalized Generation In Large Model Era: A Survey (2025.acl-long)

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Challenge: Recent advances in large generative models have catalyzed a paradigm shift in content generation to Personalized Generation (PGen).
Approach: They propose a multi-level taxonomy that systematically formalizes PGen's key components, core objectives, and abstract workflows.
Outcome: The proposed taxonomy bridging PGen research across multiple modalities highlights open challenges and promising directions for future exploration.
Robust Representation Learning with Reliable Pseudo-labels Generation via Self-Adaptive Optimal Transport for Short Text Clustering (2023.acl-long)

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Challenge: Existing approaches to short text clustering are prone to degenerate solutions and noisy data.
Approach: They propose a model to improve robustness against imbalanced and noisy data . they propose self-adaptive optimal transport and class-wise contrastive learning .
Outcome: The proposed model outperforms the state-of-the-art models on eight short text clustering datasets.

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