4 papers
Rewarding Intellectual Humility Learning When Not To Answer In Large Language Models
Abha Jha, Akanksha Mahajan, Ashwath Vaithinathan Aravindan +3
Large Language Models (LLMs) often produce hallucinated or unverifiable content, undermining their reliability in factual domains. This work investigates Reinforcement Learning wit…
Do VLMs Have Bad Eyes? Diagnosing Compositional Failures via Mechanistic Interpretability
Ashwath Vaithinathan Aravindan, Abha Jha, Mihir Kulkarni
Vision-Language Models (VLMs) have shown remarkable performance in integrating visual and textual information for tasks such as image captioning and visual question answering. Howe…
Sealing The Backdoor: Unlearning Adversarial Text Triggers In Diffusion Models Using Knowledge Distillation
Ashwath Vaithinathan Aravindan, Abha Jha, Matthew Salaway +2
Text-to-image diffusion models have revolutionized generative AI, but their vulnerability to backdoor attacks poses significant security risks. Adversaries can inject imperceptible…
Backdoor Defense in Diffusion Models via Spatial Attention Unlearning
Abha Jha, Ashwath Vaithinathan Aravindan, Matthew Salaway +2
Text-to-image diffusion models are increasingly vulnerable to backdoor attacks, where malicious modifications to the training data cause the model to generate unintended outputs wh…