Papers by Jiaxi Wu

3 papers
Relaxing the Constraints: A Dual-Importance Projection Mechanism for Lifelong Model Editing (2026.findings-acl)

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Challenge: Existing knowledge editing methods rely on strict orthogonal projection to preserve previously edited knowledge, but this constraint limits gradient expressiveness, resulting in degradation of model generalization and overall performance as the number of edits increases.
Approach: They propose a method that leverages Singular Value Decomposition to identify critical gradient subspaces and introduces a dual mechanism comprising "accumulated importance" and "projection importance"
Outcome: Extensive experiments on five mainstream LLMs show that the proposed method achieves an average comprehensive performance improvement of 10.36% and effectively maintains the model’s general capabilities on downstream tasks.
APEX: Learning Adaptive Priorities for Multi-Objective Alignment in Vision-Language Generation (2026.findings-acl)

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Challenge: APEX optimizes for text-to-image generation by combining learning potential, conflict penalty, and progress need.
Approach: They propose an algorithm that stabilizes heterogeneous rewards and dynamically schedules objectives . they propose a method that achieves better Pareto trade-offs across four heterogenous objectives based on P3 Adaptive Priorities .
Outcome: The proposed algorithm achieves better pareto trade-offs across four heterogeneous objectives while maintaining competitive OCR accuracy.
COVID-19 Vaccine Misinformation in Middle Income Countries (2023.emnlp-main)

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Challenge: a multilingual dataset of COVID-19 vaccine misinformation is available from Brazil, Indonesia, and Nigeria.
Approach: They propose to use a multilingual dataset of COVID-19 vaccine misinformation from Brazil, Indonesia, and Nigeria to assess their relevance to vaccines and the presence of misinformation.
Outcome: The proposed models improve from 2.7 to 15.9 percentage points in macro F1-score compared to baseline models.

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