activity
20162021
most citedAI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias

265 citations · 334 across the 12 of their papers we have counts for

collaborators

14 papers

cs.CL2021

Text Simplification for Comprehension-based Question-Answering

Tanvi Dadu, Kartikey Pant, Seema Nagar +2

Text simplification is the process of splitting and rephrasing a sentence to a sequence of sentences making it easier to read and understand while preserving the content and approx…

cs.CL2021★ 2 cited

IIITG-ADBU@HASOC-Dravidian-CodeMix-FIRE2020: Offensive Content Detection in Code-Mixed Dravidian Text

Arup Baruah, Kaushik Amar Das, Ferdous Ahmed Barbhuiya +1

This paper presents the results obtained by our SVM and XLM-RoBERTa based classifiers in the shared task Dravidian-CodeMix-HASOC 2020. The SVM classifier trained using TF-IDF featu…

cs.HC2020

Gaze-based Autism Detection for Adolescents and Young Adults using Prosaic Videos

Karan Ahuja, Abhishek Bose, Mohit Jain +6

Autism often remains undiagnosed in adolescents and adults. Prior research has indicated that an autistic individual often shows atypical fixation and gaze patterns. In this short…

cs.LG2018

A Hitchhiker's Guide On Distributed Training of Deep Neural Networks

Karanbir Chahal, Manraj Singh Grover, Kuntal Dey

Deep learning has led to tremendous advancements in the field of Artificial Intelligence. One caveat however is the substantial amount of compute needed to train these deep learnin…

cs.AI2018★ 265 cited

AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias

Rachel K. E. Bellamy, Kuntal Dey, Michael Hind +15

Fairness is an increasingly important concern as machine learning models are used to support decision making in high-stakes applications such as mortgage lending, hiring, and priso…

cs.AI2018★ 23 cited

Automated Test Generation to Detect Individual Discrimination in AI Models

Aniya Agarwal, Pranay Lohia, Seema Nagar +2

Dependability on AI models is of utmost importance to ensure full acceptance of the AI systems. One of the key aspects of the dependable AI system is to ensure that all its decisio…