activity
20222026
most citedNBIAS: A Natural Language Processing Framework for Bias Identification in Text

5 citations · 10 across the 6 of their papers we have counts for

collaborators

6 papers

cs.AI2026

LLM-Agent-based Social Simulation for Attitude Diffusion

Deepak John Reji

This paper introduces discourse_simulator, an open-source framework that combines LLMs with agent-based modelling. It offers a new way to simulate how public attitudes toward immig…

cs.CL2024★ 4 cited

Developing Safe and Responsible Large Language Model : Can We Balance Bias Reduction and Language Understanding in Large Language Models?

Shaina Raza, Oluwanifemi Bamgbose, Shardul Ghuge +3

Large Language Models (LLMs) have advanced various Natural Language Processing (NLP) tasks, such as text generation and translation, among others. However, these models often gener…

eess.AS2024★ 1 cited

Empowering Communication: Speech Technology for Indian and Western Accents through AI-powered Speech Synthesis

Vinotha R, Hepsiba D, L. D. Vijay Anand +1

Neural Text-to-speech (TTS) synthesis is a powerful technology that can generate speech using neural networks. One of the most remarkable features of TTS synthesis is its capabilit…

cs.CL2023★ 5 cited

NBIAS: A Natural Language Processing Framework for Bias Identification in Text

Shaina Raza, Muskan Garg, Deepak John Reji +2

Bias in textual data can lead to skewed interpretations and outcomes when the data is used. These biases could perpetuate stereotypes, discrimination, or other forms of unfair trea…

cs.IR2022

Dbias: Detecting biases and ensuring Fairness in news articles

Shaina Raza, Deepak John Reji, Chen Ding

Because of the increasing use of data-centric systems and algorithms in machine learning, the topic of fairness is receiving a lot of attention in the academic and broader literatu…

cs.IR2022

An Approach to Ensure Fairness in News Articles

Shaina Raza, Deepak John Reji, Dora D. Liu +2

Recommender systems, information retrieval, and other information access systems present unique challenges for examining and applying concepts of fairness and bias mitigation in un…