Papers by Sudipta Chattopadhyay
Localizing Malicious Outputs from CodeLLM (2025.findings-emnlp)
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| Challenge: | Using FreqRank, we localize malicious components in outputs for triggered inputs and their corresponding backdoor triggers. |
| Approach: | They propose a mutation-based defense to localize malicious components in LLM outputs and their corresponding backdoor triggers. |
| Outcome: | The proposed defense has an average attack success rate (ASR) of 86.6% and can localize the backdoor triggers in 98% of cases. |
Knowledge-based Consistency Testing of Large Language Models (2024.findings-emnlp)
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| Challenge: | Large language models (LLMs) are being increasingly utilized in real-world applications. |
| Approach: | They propose an automated testing framework which leverages a knowledge graph to construct test cases. |
| Outcome: | The proposed framework generates 19.2% error inducing inputs and reveals 16.5% knowledge gap across all tested LLMs. |