172 citations · 257 across the 17 of their papers we have counts for
4 papers · 1 filter
Parameter Efficient Fine-Tuning for Deep Learning-Based Full-Waveform Inversion
Koustav Ghosal, Abhranta Panigrahi, Arnav Chavan +2
Seismic full waveform inversion (FWI) has seen promising advancements through deep learning. Existing approaches typically focus on task-specific models trained and evaluated in is…
Surgical Feature-Space Decomposition of LLMs: Why, When and How?
Arnav Chavan, Nahush Lele, Deepak Gupta
Low-rank approximations, of the weight and feature space can enhance the performance of deep learning models, whether in terms of improving generalization or reducing the latency o…
Beyond Uniform Scaling: Exploring Depth Heterogeneity in Neural Architectures
Akash Guna R. T, Arnav Chavan, Deepak Gupta
Conventional scaling of neural networks typically involves designing a base network and growing different dimensions like width, depth, etc. of the same by some predefined scaling…
Faster and Lighter LLMs: A Survey on Current Challenges and Way Forward
Arnav Chavan, Raghav Magazine, Shubham Kushwaha +2
Despite the impressive performance of LLMs, their widespread adoption faces challenges due to substantial computational and memory requirements during inference. Recent advancement…