1 citations · 1 across the 6 of their papers we have counts for
7 papers
The Hidden Cost of Modeling P(X): Vulnerability to Membership Inference Attacks in Generative Text Classifiers
Owais Makroo, Siva Rajesh Kasa, Sumegh Roychowdhury +4
Membership Inference Attacks (MIAs) pose a critical privacy threat by enabling adversaries to determine whether a specific sample was included in a model's training dataset. Despit…
Assess and Prompt: A Generative RL Framework for Improving Engagement in Online Mental Health Communities
Bhagesh Gaur, Karan Gupta, Aseem Srivastava +2
Online Mental Health Communities (OMHCs) provide crucial peer and expert support, yet many posts remain unanswered due to missing support attributes that signal the need for help.…
Generative or Discriminative? Revisiting Text Classification in the Era of Transformers
Siva Rajesh Kasa, Karan Gupta, Sumegh Roychowdhury +7
The comparison between discriminative and generative classifiers has intrigued researchers since Efron's seminal analysis of logistic regression versus discriminant analysis. While…
CXMArena: Unified Dataset to benchmark performance in realistic CXM Scenarios
Raghav Garg, Kapil Sharma, Karan Gupta
Large Language Models (LLMs) hold immense potential for revolutionizing Customer Experience Management (CXM), particularly in contact center operations. However, evaluating their p…
Exploring Ordinality in Text Classification: A Comparative Study of Explicit and Implicit Techniques
Siva Rajesh Kasa, Aniket Goel, Karan Gupta +4
Ordinal Classification (OC) is a widely encountered challenge in Natural Language Processing (NLP), with applications in various domains such as sentiment analysis, rating predicti…
How Robust are LLMs to In-Context Majority Label Bias?
Karan Gupta, Sumegh Roychowdhury, Siva Rajesh Kasa +4
In the In-Context Learning (ICL) setup, various forms of label biases can manifest. One such manifestation is majority label bias, which arises when the distribution of labeled exa…
Tackling Concept Shift in Text Classification using Entailment-style Modeling
Sumegh Roychowdhury, Karan Gupta, Siva Rajesh Kasa +2
Pre-trained language models (PLMs) have seen tremendous success in text classification (TC) problems in the context of Natural Language Processing (NLP). In many real-world text cl…