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Tejaswini Kumar

2 accepted papers

2025

MVTamperBench: Evaluating Robustness of Vision-Language Models

ACL 2025finding

Multimodal Large Language Models (MLLMs), are recent advancement of Vision-Language Models (VLMs) that have driven major advances in video understanding. However, their vulnerability to adversarial tampering and manipulations remains underexplored. To address this gap, we introduce MVTamperBench, a…

2025

SweEval: Do LLMs Really Swear? A Safety Benchmark for Testing Limits for Enterprise Use

NAACL 2025industry

Enterprise customers are increasingly adopting Large Language Models (LLMs) for critical communication tasks, such as drafting emails, crafting sales pitches, and composing casual messages. Deploying such models across different regions requires them to understand diverse cultural and linguistic con…