31 citations · 40 across the 8 of their papers we have counts for
6 papers · 1 filter
LLMGuard: Guarding Against Unsafe LLM Behavior
Shubh Goyal, Medha Hira, Shubham Mishra +6
Although the rise of Large Language Models (LLMs) in enterprise settings brings new opportunities and capabilities, it also brings challenges, such as the risk of generating inappr…
"Beware of deception": Detecting Half-Truth and Debunking it through Controlled Claim Editing
Sandeep Singamsetty, Nishtha Madaan, Sameep Mehta +2
The prevalence of half-truths, which are statements containing some truth but that are ultimately deceptive, has risen with the increasing use of the internet. To help combat this…
Generate Your Counterfactuals: Towards Controlled Counterfactual Generation for Text
Nishtha Madaan, Inkit Padhi, Naveen Panwar +1
Machine Learning has seen tremendous growth recently, which has led to larger adoption of ML systems for educational assessments, credit risk, healthcare, employment, criminal just…
Fair Transfer of Multiple Style Attributes in Text
Karan Dabas, Nishtha Madan, Vijay Arya +3
To preserve anonymity and obfuscate their identity on online platforms users may morph their text and portray themselves as a different gender or demographic. Similarly, a chatbot…
Judging a Book by its Description : Analyzing Gender Stereotypes in the Man Bookers Prize Winning Fiction
Nishtha Madaan, Sameep Mehta, Shravika Mittal +1
The presence of gender stereotypes in many aspects of society is a well-known phenomenon. In this paper, we focus on studying and quantifying such stereotypes and bias in the Man B…
Generating Clues for Gender based Occupation De-biasing in Text
Nishtha Madaan, Gautam Singh, Sameep Mehta +2
Vast availability of text data has enabled widespread training and use of AI systems that not only learn and predict attributes from the text but also generate text automatically.…