Democratizing AI: Open-source Scalable LLM Training on GPU-based Supercomputers. - Siddharth Singh; Prajwal Singhania; Aditya Ranjan; John Kirchenbauer; Jonas Geiping; Yuxin Wen; Neel Jain; Abhimanyu Hans; Manli Shu; Aditya Tomar; Tom Goldstein; Abhinav Bhatele (SC, 2024)

Automated Programmatic Performance Analysis of Parallel Programs. - Onur Cankur; Aditya Tomar; Daniel Nichols; Connor Scully-Allison; Katherine E. Isaacs; Abhinav Bhatele (CoRR, 2024)

Stereotype Detection as a Catalyst for Enhanced Bias Detection: A Multi-Task Learning Approach. - Aditya Tomar; V. Rudra Murthy; Pushpak Bhattacharyya (ACL (Findings), 2025)

QuantSpec: Self-Speculative Decoding with Hierarchical Quantized KV Cache. - Rishabh Tiwari; Haocheng Xi; Aditya Tomar; Coleman Hooper; Sehoon Kim 001; Maxwell Horton; Mahyar Najibi; Michael W. Mahoney; Kurt Keutzer; Amir Gholami (CoRR, 2025)

Mathematics Isn't Culture-Free: Probing Cultural Gaps via Entity and Scenario Perturbations. - Aditya Tomar; Nihar Ranjan Sahoo; Ashish R. Mittal; Rudra Murthy; Pushpak Bhattacharyya (CoRR, 2025)

BharatBBQ: A Multilingual Bias Benchmark for Question Answering in the Indian Context. - Aditya Tomar; Nihar Ranjan Sahoo; Pushpak Bhattacharyya (CoRR, 2025)

Can Transformers Break Encryption Schemes via In-Context Learning? - Jathin Korrapati; Patrick Mendoza; Aditya Tomar; Abein Abraham (CoRR, 2025)

XQuant: Breaking the Memory Wall for LLM Inference with KV Cache Rematerialization. - Aditya Tomar; Coleman Hooper; Minjae Lee; Haocheng Xi; Rishabh Tiwari; Wonjun Kang; Luca Manolache; Michael W. Mahoney; Kurt Keutzer; Amir Gholami (CoRR, 2025)