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Nalini K. Ratha

2 accepted papers

2026

Forget Less by Learning from Parents Through Hierarchical Relationships

AAAI 2026technical

Custom Diffusion Models (CDMs) offer impressive capabilities for personalization in generative modeling, yet they remain vulnerable to catastrophic forgetting when learning new concepts sequentially. Existing approaches primarily focus on minimizing interference between concepts, often neglecting th

Cited by 0SourcePDFScholar
2026

LABEL-FREE MITIGATION OF SPURIOUS CORRELATIONS IN VLMS USING SPARSE AUTOENCODERS

ICLR 2026poster

Vision-Language Models (VLMs) have demonstrated impressive zero-shot capabilities across a wide range of tasks and domains. However, their performance is often compromised by learned spurious correlations, which can adversely affect downstream applications. Existing mitigation strategies typically d…

Cited by 0SourcecodeScholar