Jain, Vinija

A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications

Sahoo, P., Singh, A. K., Saha, S., Jain, V., Mondal, S., & Chadha, A. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 288

A Comprehensive Survey of Hallucination Mitigation Techniques in Large Language Models

Tonmoy, S. M. T. I., Zaman, S. M. M., Jain, V., Rani, A., Rawte, V., Chadha, A., & Das, A. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 129

Cause and Effect: Can Large Language Models Truly Understand Causality?

Ashwani, S., Hegde, K., Reddy Mannuru, N., Singh Sengar, D., Jindal, M., Chaitanya Rao Kathala, K., Banga, D., Jain, V., & Chadha, A. (2024) · Proceedings of the AAAI Symposium Series

Explainable Artificial Intelligence (XAI)Topic Modeling

Cited by 18

The Evolution of Mixture of Experts: A Survey from Basics to Breakthroughs

Vats, A., Raja, R., Jain, V., & Chadha, A. (2024) · Preprints.org

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 10

Are Small Language Models Ready to Compete with Large Language Models for Practical Applications?

Sinha, N., Jain, V., & Chadha, A. (2025) · Proceedings of the 5th Workshop on Trustworthy NLP (TrustNLP 2025)

Topic ModelingNatural Language Processing Techniques

Cited by 9

SAHOO: Safeguarded Alignment for High-Order Optimization Objectives in Recursive Self-Improvement

Sahoo, S., Chadha, A., Jain, V., & Chaudhary, D. (2026) · arXiv

Ethics and Social Impacts of AITopic Modeling

Cited by 0