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Rishika Bhagwatkar

2 accepted papers

2025

CAVE : Detecting and Explaining Commonsense Anomalies in Visual Environments

EMNLP 2025

Humans can naturally identify, reason about, and explain anomalies in their environment. In computer vision, this long-standing challenge remains limited to industrial defects or unrealistic, synthetically generated anomalies, failing to capture the richness and unpredictability of real-world anomal

Cited by 0SourcePDFScholar
2024

Improving Adversarial Robustness in Vision-Language Models with Architecture and Prompt Design

EMNLP 2024finding

Vision-Language Models (VLMs) have seen a significant increase in both research interest and real-world applications across various domains, including healthcare, autonomous systems, and security. However, their growing prevalence demands higher reliability and safety including robustness to adversa…

Cited by 1SourcePDFScholar