← Search

Priyaranjan Pattnayak

4 accepted papers

2026

Assistive Prompt Mediation: Evaluating Language Models Under Accessibility Constraints

ICML 2026poster

Large language models (LLMs) are increasingly used as assistive interfaces for users who cannot reliably produce clean text due to accessibility constraints, yet existing evaluations assume iterative input repair and focus on task accuracy or generic noise robustness. We introduce Assistive Prompt M…

Cited by 0SourceScholar
2025

Crowdsource, Crawl, or Generate? Creating SEA-VL, a Multicultural Vision-Language Dataset for Southeast Asia

ACL 2025long

Despite Southeast Asia’s (SEA) extraordinary linguistic and cultural diversity, the region remains significantly underrepresented in vision-language (VL) research, resulting in AI models that inadequately capture SEA cultural nuances. To fill this gap, we present SEA-VL, an open-source initiative de…

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…