2 citations · 4 across the 14 of their papers we have counts for
8 papers · 1 filter
Say It Differently: Linguistic Styles as Jailbreak Vectors
Srikant Panda, Avinash Rai
Large Language Models (LLMs) are commonly evaluated for robustness against paraphrased or semantically equivalent jailbreak prompts, yet little attention has been paid to linguisti…
Pushing on Multilingual Reasoning Models with Language-Mixed Chain-of-Thought
Guijin Son, Donghun Yang, Hitesh Laxmichand Patel +9
Recent frontier models employ long chain-of-thought reasoning to explore solution spaces in context and achieve stonger performance. While many works study distillation to build sm…
AccessEval: Benchmarking Disability Bias in Large Language Models
Srikant Panda, Amit Agarwal, Hitesh Laxmichand Patel
Large Language Models (LLMs) are increasingly deployed across diverse domains but often exhibit disparities in how they handle real-life queries. To systematically investigate thes…
Who's Asking? Investigating Bias Through the Lens of Disability Framed Queries in LLMs
Vishnu Hari, Kalpana Panda, Srikant Panda +2
Large Language Models (LLMs) routinely infer users demographic traits from phrasing alone, which can result in biased responses, even when no explicit demographic information is pr…
DAIQ: Auditing Demographic Attribute Inference from Question in LLMs
Srikant Panda, Hitesh Laxmichand Patel, Shahad Al-Khalifa +3
Recent evaluations of Large language models (LLMs) audit social bias primarily through prompts that explicitly reference demographic attributes, overlooking whether models infer se…
SweEval: Do LLMs Really Swear? A Safety Benchmark for Testing Limits for Enterprise Use
Hitesh Laxmichand Patel, Amit Agarwal, Arion Das +6
Enterprise customers are increasingly adopting Large Language Models (LLMs) for critical communication tasks, such as drafting emails, crafting sales pitches, and composing casual…