Exploring Ordinality in Text Classification: A Comparative Study of Explicit and Implicit Techniques

no code implementations • 20 May 2024 • Siva Rajesh Kasa, Aniket Goel, Karan Gupta, Sumegh Roychowdhury, Anish Bhanushali, Nikhil Pattisapu, Prasanna Srinivasa Murthy

Ordinal Classification (OC) is a widely encountered challenge in Natural Language Processing (NLP), with applications in various domains such as sentiment analysis, rating prediction, and more.

Ordinal Classification Sentiment Analysis +2

How Robust are LLMs to In-Context Majority Label Bias?

no code implementations • 27 Dec 2023 • Karan Gupta, Sumegh Roychowdhury, Siva Rajesh Kasa, Santhosh Kumar Kasa, Anish Bhanushali, Nikhil Pattisapu, Prasanna Srinivasa Murthy

In the In-Context Learning (ICL) setup, various forms of label biases can manifest.

In-Context Learning text-classification +1

Tackling Concept Shift in Text Classification using Entailment-style Modeling

no code implementations • 6 Nov 2023 • Sumegh Roychowdhury, Karan Gupta, Siva Rajesh Kasa, Prasanna Srinivasa Murthy, Alok Chandra

Pre-trained language models (PLMs) have seen tremendous success in text classification (TC) problems in the context of Natural Language Processing (NLP).

text-classification Text Classification

ADARES: Adaptive Resource Management for Virtual Machines

no code implementations • 5 Dec 2018 • Ignacio Cano, Lequn Chen, Pedro Fonseca, Tianqi Chen, Chern Cheah, Karan Gupta, Ramesh Chandra, Arvind Krishnamurthy

Our large-scale analysis confirms that VMs are often misconfigured, either overprovisioned or underprovisioned, and that this problem is pervasive across a wide range of private clusters.

Management Multi-Armed Bandits +1