Unveiling the Secret Recipe: A Guide For Supervised Fine-Tuning Small LLMs. - Aldo Pareja; Nikhil Shivakumar Nayak; Hao Wang; Krishnateja Killamsetty; Shivchander Sudalairaj; Wenlong Zhao 001; Seungwook Han; Abhishek Bhandwaldar; Guangxuan Xu; Kai Xu 016; Ligong Han; Luke Inglis; et al. (ICLR, 2025)

Towards Interpretable Soft Prompts. - Oam Patel; Jason Wang; Nikhil Shivakumar Nayak; Suraj Srinivas; Himabindu Lakkaraju (CoRR, 2025)

Graph Attention for Heterogeneous Graphs with Positional Encoding. - Nikhil Shivakumar Nayak (CoRR, 2025)

Mathematical Modeling of Option Pricing with an Extended Black-Scholes Framework. - Nikhil Shivakumar Nayak (CoRR, 2025)

Sculpting Subspaces: Constrained Full Fine-Tuning in LLMs for Continual Learning. - Nikhil Shivakumar Nayak; Krishnateja Killamsetty; Ligong Han; Abhishek Bhandwaldar; Prateek Chanda; Kai Xu 016; Hao Wang; Aldo Pareja; Oleg Silkin; Mustafa Eyceoz; Akash Srivastava (CoRR, 2025)

Hopscotch: Discovering and Skipping Redundancies in Language Models. - Mustafa Eyceoz; Nikhil Shivakumar Nayak; Hao Wang; Ligong Han; Akash Srivastava (CoRR, 2025)

Learning What Matters: Probabilistic Task Selection via Mutual Information for Model Finetuning. - Prateek Chanda; Saral Sureka; Parth Pratim Chatterjee; Krishnateja Killamsetty; Nikhil Shivakumar Nayak; Ganesh Ramakrishnan (CoRR, 2025)