Raghav Singhal

According to our database, Raghav Singhal authored at least 23 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

ABBA: Highly Expressive Hadamard Product Adaptation for Large Language Models.

Raghav Singhal, Kaustubh Ponkshe, Rohit Vartak, Praneeth Vepakomma

CoRR, May, 2025

Safety Subspaces are Not Distinct: A Fine-Tuning Case Study.

Kaustubh Ponkshe, Shaan Shah, Raghav Singhal, Praneeth Vepakomma

CoRR, May, 2025

Jacobian-Free Newton-Krylov with a globalization method for solving groundwater flow models of multi-layer aquifer systems.

Raghav Singhal, Emin C. Dogrul, Zhaojun Bai

CoRR, May, 2025

Regularization-based Framework for Quantization-, Fault- and Variability-Aware Training.

Anmol Biswas, Raghav Singhal, Sivakumar Elangovan, Shreyas Sabnis, Udayan Ganguly

CoRR, March, 2025

Fed-SB: A Silver Bullet for Extreme Communication Efficiency and Performance in (Private) Federated LoRA Fine-Tuning.

Raghav Singhal, Kaustubh Ponkshe, Rohit Vartak, Lav R. Varshney, Praneeth Vepakomma

CoRR, February, 2025

A General Framework for Inference-time Scaling and Steering of Diffusion Models.

Raghav Singhal, Zachary Horvitz, Ryan Teehan, Mengye Ren, Zhou Yu, Kathleen McKeown, Rajesh Ranganath

CoRR, January, 2025

M3CoL: Harnessing Shared Relations via Multimodal Mixup Contrastive Learning for Multimodal Classification.

Raja Kumar, Raghav Singhal, Pranamya Prashant Kulkarni, Deval Mehta, Kshitij Sharad Jadhav

Trans. Mach. Learn. Res., 2025

FedEx-LoRA: Exact Aggregation for Federated and Efficient Fine-Tuning of Large Language Models.

Raghav Singhal, Kaustubh Ponkshe, Praneeth Vepakomma

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

2024

Initialization using Update Approximation is a Silver Bullet for Extremely Efficient Low-Rank Fine-Tuning.

Kaustubh Ponkshe, Raghav Singhal, Eduard Gorbunov, Alexey Tumanov, Samuel Horváth, Praneeth Vepakomma

CoRR, 2024

Exact Aggregation for Federated and Efficient Fine-Tuning of Foundation Models.

Raghav Singhal, Kaustubh Ponkshe, Praneeth Vepakomma

CoRR, 2024

Harnessing Shared Relations via Multimodal Mixup Contrastive Learning for Multimodal Classification.

Raja Kumar, Raghav Singhal, Pranamya Prashant Kulkarni, Deval Mehta, Kshitij S. Jadhav

CoRR, 2024

Temporal and Spatial Reservoir Ensembling Techniques for Liquid State Machines.

Anmol Biswas, Sharvari Ashok Medhe, Raghav Singhal, Udayan Ganguly

Proceedings of the International Conference on Neuromorphic Systems, 2024

Adaptive Sampling of k-Space in Magnetic Resonance for Rapid Pathology Prediction.

Chen-Yu Yen, Raghav Singhal, Umang Sharma, Rajesh Ranganath, Sumit Chopra, Lerrel Pinto

Proceedings of the Forty-first International Conference on Machine Learning, 2024

What's the score? Automated Denoising Score Matching for Nonlinear Diffusions.

Raghav Singhal, Mark Goldstein, Rajesh Ranganath

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Gecko adhesion based sea star crawler robot.

Sampada Acharya, Peter Roberts, Tejas Rane, Raghav Singhal, Peize Hong, Viraj Ranade, Carmel Majidi, Victoria A. Webster-Wood, B. Reeja-Jayan

Frontiers Robotics AI, October, 2023

Enhanced regularization for on-chip training using analog and temporary memory weights.

Raghav Singhal, Vivek Saraswat, Shreyas Deshmukh, Sreenivas Subramoney, Laxmeesha Somappa, Maryam Shojaei Baghini, Udayan Ganguly

Neural Networks, August, 2023

Comprehensive study of forced convection over a heated elliptical cylinder with varying angle of incidences to uniform free stream.

Raghav Singhal, Sailen Dutta, Jiten C. Kalita

CoRR, 2023

On the Feasibility of Machine Learning Augmented Magnetic Resonance for Point-of-Care Identification of Disease.

Raghav Singhal, Mukund Sudarshan, Anish Mahishi, Sri Kaushik, Luke Ginocchio, Angela Tong, Hersh Chandarana, Daniel K. Sodickson, Rajesh Ranganath, Sumit Chopra

CoRR, 2023

Translation and Scale Invariance for Event-Based Object tracking.

Jens Egholm Pedersen, Raghav Singhal, Jörg Conradt

Proceedings of the Neuro-Inspired Computational Elements Conference, 2023

Where to Diffuse, How to Diffuse, and How to Get Back: Automated Learning for Multivariate Diffusions.

Raghav Singhal, Mark Goldstein, Rajesh Ranganath

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

An efficient explicit jump HOC immersed interface approach for transient incompressible viscous flows.

Raghav Singhal, Jiten C. Kalita

CoRR, 2022

2021

A Novel HOC-Immersed Interface Approach For Elliptic Problems.

Raghav Singhal, Jiten C. Kalita

CoRR, 2021

2019

Kernelized Complete Conditional Stein Discrepancy.

Raghav Singhal, Saad Lahlou, Rajesh Ranganath

CoRR, 2019