Papers by Pankayaraj Pathmanathan
Teach a Reward Model to Correct Itself: Reward Guided Adversarial Failure Discovery for Robust Reward Modeling (2026.acl-long)
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| Challenge: | Existing failure discovery methods rely on prior knowledge of preference attributes . Existing methods do not scale to new models or data. |
| Approach: | They propose a preference distribution agnostic procedure that uses the reward model itself to guide controlled decoding toward mis specified responses while preserving the underlying preference class. |
| Outcome: | The proposed procedure improves robustness without degrading reward quality across models. |
PoisonedParrot: Subtle Data Poisoning Attacks to Elicit Copyright-Infringing Content from Large Language Models (2025.naacl-long)
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Michael-Andrei Panaitescu-Liess, Pankayaraj Pathmanathan, Yigitcan Kaya, Zora Che, Bang An, Sicheng Zhu, Aakriti Agrawal, Furong Huang
| Challenge: | PoisonedParrot is the first stealthy data poisoning attack that induces an LLM to generate copyrighted content even when the model has not been directly trained on the copyright material. |
| Approach: | They propose a stealthy data poisoning attack that induces an LLM to generate copyrighted content even when it has not been directly trained on the copyright material. |
| Outcome: | The proposed model induces an LLM to generate copyrighted content with no discernible side effects and is surprisingly effective at priming the model to generate content with little side effects. |