Papers by Hongjiang Xiao

2 papers
Multi-Task Representation Alignment on Language Understanding: A Mutual Information Perspective (2026.acl-long)

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Challenge: Existing approaches to multitask learning fail to address task interference issues . Existing methods focus on task balancing or probabilistic modeling but fail to learn sufficient representations for all target tasks.
Approach: They propose a multi-task representation alignment framework to achieve task-specific alignment and self-alignment on shared representations from a mutual information perspective.
Outcome: The proposed framework outperforms 13 representative MTL methods under label-noisy and data-constrained conditions.
PsyMem: Fine-grained Psychological Alignment and Explicit Memory Control for Advanced Role-Playing LLMs (2026.tacl-1)

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Challenge: Existing role-playing models rely on superficial textual descriptions or simplistic metrics, inadequately modeling both intrinsic and extrinsic character dimensions.
Approach: They propose a framework that integrates fine-grained psychological attributes and explicit memory control for role-playing.
Outcome: The proposed framework outperforms baseline models in human-likeness and character fidelity.

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