Papers by Yunfeng Ning
CAVGAN: Unifying Jailbreak and Defense of LLMs via Generative Adversarial Attacks on their Internal Representations (2025.findings-acl)
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| Challenge: | Existing studies have isolated LLM jailbreak attacks and defenses . a new framework combines attack and defense to protect against malicious queries . |
| Approach: | They propose a framework that combines attack and defense to protect the Large Language Model (LLM) by embedding harmful problems into the safe area. |
| Outcome: | The proposed framework achieves an average jailbreak success rate of 88.85% across three popular LLMs while the defense success rate reaches an average of 84.17%. |
MuKA: Multimodal Knowledge Augmented Visual Information-Seeking (2025.coling-main)
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| Challenge: | Existing methods for visual information-seeking tasks rely on textual knowledge . existing methods can impair information retrieval and confuse MLLMs . |
| Approach: | They propose a framework which leverages a multimodal knowledge base to address these limitations. |
| Outcome: | The proposed framework outperforms state-of-the-art methods on the InfoSeek and E-VQA benchmarks. |