Chahat Raj

Orcid: 0000-0003-0083-6812

According to our database1, Chahat Raj authored at least 24 papers between 2020 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
KnowBias: Mitigating Social Bias in LLMs via Know-Bias Neuron Enhancement.
CoRR, January, 2026

VIGNETTE: Socially Grounded Bias Evaluation for Vision-Language Models.
Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2026

Bias Association Discovery Framework for Open-Ended LLM Generations.
Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025
A review of web infodemic analysis and detection trends across multi-modalities using deep neural network.
Int. J. Data Sci. Anal., October, 2025

Discovering Bias Associations through Open-Ended LLM Generations.
CoRR, August, 2025

Talent or Luck? Evaluating Attribution Bias in Large Language Models.
CoRR, May, 2025

Measuring South Asian Biases in Large Language Models.
CoRR, May, 2025

Beneath the Surface: How Large Language Models Reflect Hidden Bias.
CoRR, February, 2025

What's Not Said Still Hurts: A Description-Based Evaluation Framework for Measuring Social Bias in LLMs.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2025, 2025

Toward Inclusive Language Models: Sparsity-Driven Calibration for Systematic and Interpretable Mitigation of Social Biases in LLMs.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2025, 2025

2024
Bitcoin price prediction using LSTM autoencoder regularized by false nearest neighbor loss.
Soft Comput., November, 2024

BiasDora: Exploring Hidden Biased Associations in Vision-Language Models.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

SALSA: Salience-Based Switching Attack for Adversarial Perturbations in Fake News Detection Models.
Proceedings of the Advances in Information Retrieval, 2024

Breaking Bias, Building Bridges: Evaluation and Mitigation of Social Biases in LLMs via Contact Hypothesis.
Proceedings of the Seventh AAAI/ACM Conference on AI, Ethics, and Society (AIES-24) - Full Archival Papers, October 21-23, 2024, San Jose, California, USA, 2024

2023
Global Voices, Local Biases: Socio-Cultural Prejudices across Languages.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

True and Fair: Robust and Unbiased Fake News Detection via Interpretable Machine Learning.
Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 2023

2022
ARCNN framework for multimodal infodemic detection.
Neural Networks, 2022

The Effectiveness of Social Media Engagement Strategy on Disaster Fundraising.
CoRR, 2022

2021
Machine Learning Techniques for Differential Diagnosis of Vertigo and Dizziness: A Review.
Sensors, 2021

A Review of Web Infodemic Analysis and Detection Trends across Multi-modalities using Deep Neural Networks.
CoRR, 2021

Is Dynamic Rumor Detection on social media Viable? An Unsupervised Perspective.
CoRR, 2021

People Lie, Actions Don't! Modeling Infodemic Proliferation Predictors among Social Media Users.
CoRR, 2021

ConvNet frameworks for multi-modal fake news detection.
Appl. Intell., 2021

2020
MediaEval 2020: An Ensemble-based Multimodal Approach for Coronavirus and 5G Conspiracy Tweet Detection.
Proceedings of the Working Notes Proceedings of the MediaEval 2020 Workshop, 2020


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