Papers by Yujin Zhu

2 papers
UMRSpell: Unifying the Detection and Correction Parts of Pre-trained Models towards Chinese Missing, Redundant, and Spelling Correction (2023.acl-long)

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Challenge: Chinese Spelling Correction (CSC) is a task of detecting and correcting misspelled charac- ters in Chinese texts.
Approach: They propose a model to learn detection and correction parts together from a multi-task learning perspective.
Outcome: The proposed model can learn detection and correction parts together from a multi-task learning perspective.
CoMeT: Collaborative Memory Transformer for Efficient Long Context Modeling (2026.acl-long)

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Challenge: a novel architecture that enables LLMs to handle arbitrarily long sequences with constant memory usage and linear time complexity is a major barrier to long-context processing.
Approach: They propose a novel architecture that enables LLMs to handle arbitrarily long sequences with constant memory usage and linear time complexity.
Outcome: The proposed architecture can handle arbitrarily long sequences with constant memory usage and linear time complexity.

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