Papers by Md Rafi Ur Rashid
From Insight to Exploit: Leveraging LLM Collaboration for Adaptive Adversarial Text Generation (2025.findings-emnlp)
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| Challenge: | LLMs can provide substantial zero-shot performance on diverse tasks, but it is crucial to assess their robustness against adversarial inputs. |
| Approach: | They introduce Static Deceptor and Dynamic Deceptr to generate adversarial examples . they produce subtle and natural-looking adversarials that preserve semantic similarity to text . |
| Outcome: | The proposed attacks are based on two LLM-based attacks that generate natural-looking examples that deceive the target LLM. |
SequentialBreak: Large Language Models Can be Fooled by Embedding Jailbreak Prompts into Sequential Prompt Chains (2025.acl-srw)
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| Challenge: | SequentialBreak enables LLMs to bypass safety mechanisms by arranging malicious prompts in a single query. |
| Approach: | They propose a single-query jailbreak technique that arranges multiple benign prompts in sequence with a hidden malicious instruction among them to bypass safety mechanisms. |
| Outcome: | The proposed technique outperforms baselines on open-source and closed-source models. |