Papers by Minxin Guo
From Domains to Instances: Dual-Granularity Data Synthesis for LLM Unlearning (2026.findings-acl)
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Xiaoyu Xu, Minxin Du, Zitong LI, Zi Liang, Zhibiao Guo, Zhang Shiyu, Peizhao Hu, Qingqing Ye, Haibo Hu
| Challenge: | Currently, the evaluation of unlearning is limited due to the lack of granularity in the model. |
| Approach: | They propose a framework for synthesizing high-quality forget sets that exploits the target model per se to elicit data that matches its internal knowledge distribution through seed-guided and adversarial prompting. |
| Outcome: | The proposed framework achieves a superior balance of relevance, diversity, and efficiency across benchmarks. |
Visual Hallucinations of Multi-modal Large Language Models (2024.findings-acl)
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| Challenge: | Existing studies find VH instances only in existing image datasets, which results in biased understanding of MLLMs’ performance under VH. |
| Approach: | They propose a tool called VHTest to generate a diverse set of VH instances from existing image datasets and a text-to-image generative model to generate VH images based on the text descriptions. |
| Outcome: | The proposed tool finds VH instances in existing image datasets and generates images based on the text descriptions. |