Jinzhe Liu — accepted AI-conference papers

2026

Locate-then-Sparsify: Attribution Guided Sparse Strategy for Visual Hallucination Mitigation

Tiantian Dang, Chao Bi, Shufan Shen, Jinzhe Liu, Qingming Huang, Shuhui Wang

CVPR 2026

Despite the significant advancements in Large Vision-Language Models (LVLMs), their tendency to generate hallucinations undermines reliability and restricts broader practical deployment. Among the hallucination mitigation methods, feature steering emerges as a promising approach that reduces erroneo

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2025

Edit Less, Achieve More: Dynamic Sparse Neuron Masking for Lifelong Knowledge Editing in LLMs

Jinzhe Liu, Junshu Sun, Shufan Shen, Chenxue Yang, Shuhui Wang

NeurIPS 2025poster

Lifelong knowledge editing enables continuous, precise updates to outdated knowledge in large language models (LLMs) without computationally expensive full retraining. However, existing methods often accumulate errors throughout the editing process, causing a gradual decline in both editing accuracy…

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