| A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications P Sahoo, AK Singh, S Saha, V Jain, S Mondal, A Chadha arXiv preprint arXiv:2402.07927, 2024 | 1439 | 2024 |
| A Comprehensive Survey of Hallucination Mitigation Techniques in Large Language Models SM Tonmoy, SM Zaman, V Jain, A Rani, V Rawte, A Chadha, A Das arXiv preprint arXiv:2401.01313, 2024 | 724 | 2024 |
| Unveiling Hallucination in Text, Image, Video, and Audio Foundation Models: A Comprehensive Survey P Sahoo, P Meharia, A Ghosh, S Saha, V Jain, A Chadha EMNLP 2024 Findings, 2024 | 127* | 2024 |
| Exploring the Frontier of Vision-Language Models: A Survey of Current Methodologies and Future Directions A Ghosh, A Acharya, S Saha, V Jain, A Chadha Elsevier Preprint, 2024 | 127 | 2024 |
| Breaking Down the Defenses: a Comparative Survey of Attacks on Large Language Models AG Chowdhury, MM Islam, V Kumar, FH Shezan, V Jain, A Chadha arXiv preprint arXiv:2403.04786, 2024 | 97 | 2024 |
| The What, Why, and How of Context Length Extension Techniques in Large Language Models--A Detailed Survey S Pawar, SM Tonmoy, SM Zaman, V Jain, A Chadha, A Das arXiv preprint arXiv:2401.07872, 2024 | 49 | 2024 |
| Cause and Effect: Can Large Language Models Truly Understand Causality? S Ashwani, K Hegde, NR Mannuru, M Jindal, DS Sengar, KCR Kathala, ... AAAI 2025 Symposium on AI Trustworthiness and Risk Assessment for Challenged …, 2024 | 48 | 2024 |
| Parameter Efficient Fine-Tuning: A Comprehensive Analysis Across Applications CCS Balne, S Bhaduri, T Roy, V Jain, A Chadha arXiv preprint arXiv:2404.13506, 2024 | 43 | 2024 |
| Exploring the Impact of Large Language Models on Recommender Systems: An Extensive Review A Vats, V Jain, R Raja, A Chadha arXiv preprint arXiv:2402.18590, 2024 | 40 | 2024 |
| Counter Turing Test (CT^2): AI-Generated Text Detection is Not as Easy as You May Think--Introducing AI Detectability Index M Chakraborty, SM Tonmoy, SM Zaman, K Sharma, NR Barman, C Gupta, ... EMNLP 2023 -- Outstanding Paper Award, 2023 | 39 | 2023 |
| The Evolution of Mixture of Experts: A Survey from Basics to Breakthroughs A Vats, R Raja, V Jain, A Chadha Preprints, 2024 | 24 | 2024 |
| Investigating Annotator Bias in Large Language Models for Hate Speech Detection A Das, Z Zhang, F Jamshidi, V Jain, A Chadha, N Raychawdhary, ... NeurIPS 2024 Safe Generative AI Workshop, 2024 | 19 | 2024 |
| Refining Text-to-Image Generation: Towards Accurate Training-Free Glyph-Enhanced Image Generation S Lakhanpal, S Chopra, V Jain, A Chadha, M Luo WACV 2025, 2024 | 18 | 2024 |
| How Culturally Aware Are Vision-Language Models? O Burda-Lassen, A Chadha, S Goswami, V Jain 2025 IEEE 6th International Conference on Image Processing, Applications and …, 2025 | 17 | 2025 |
| PHAnToM: Personality Has An Effect on Theory-of-Mind Reasoning in Large Language Models FA Tan, GC Yeo, F Wu, W Xu, V Jain, A Chadha, K Jaidka, Y Liu, SK Ng ICWSM 2025, 2024 | 17* | 2024 |
| Decoding the Diversity: A Review of the Indic AI Research Landscape KJ Sankalp, V Jain, S Bhaduri arXiv preprint arXiv:2406.09559, 0 | 16* | |
| Breaking down the defenses: A comparative survey of attacks on large language models, 2024 AG Chowdhury, MM Islam, V Kumar, FH Shezan, V Kumar, V Jain, ... URL https://arxiv. org/abs/2403.04786, 0 | 15 | |
| Guiding Vision-Language Model Selection for Visual Question-Answering Across Tasks, Domains, and Knowledge Types N Sinha, V Jain, A Chadha COLING 2025 Workshop of Evaluation of Multi-Modal Generation (EvalMG), 2024 | 13 | 2024 |
| Are Small Language Models Ready to Compete With Large Language Models for Practical Applications? N Sinha, V Jain, A Chadha Proceedings of the 5th Workshop on Trustworthy NLP (TrustNLP 2025), 365-398, 2025 | 12 | 2025 |
| From Prejudice to Parity: A New Approach to Debiasing Large Language Model Word Embeddings A Rakshit, S Singh, S Keshari, AG Chowdhury, V Jain, A Chadha COLING 2025, 2024 | 10 | 2024 |
Aman ChadhaGenAI Leadership @ Apple • Stanford AI • UW-Madison ECE • Ex: AWS, Alexa, Nvidia, QualcommVerified email at amazon.com
