16 citations · 20 across the 4 of their papers we have counts for
4 papers
SARATHI: Efficient LLM Inference by Piggybacking Decodes with Chunked Prefills
Amey Agrawal, Ashish Panwar, Jayashree Mohan +3
Large Language Model (LLM) inference consists of two distinct phases - prefill phase which processes the input prompt and decode phase which generates output tokens autoregressivel…
"Can't Take the Pressure?": Examining the Challenges of Blood Pressure Estimation via Pulse Wave Analysis
Suril Mehta, Nipun Kwatra, Mohit Jain +1
The use of observed wearable sensor data (e.g., photoplethysmograms [PPG]) to infer health measures (e.g., glucose level or blood pressure) is a very active area of research. Such…
Towards Automating Retinoscopy for Refractive Error Diagnosis
Aditya Aggarwal, Siddhartha Gairola, Uddeshya Upadhyay +6
Refractive error is the most common eye disorder and is the key cause behind correctable visual impairment, responsible for nearly 80% of the visual impairment in the US. Refractiv…
Distance Learner: Incorporating Manifold Prior to Model Training
Aditya Chetan, Nipun Kwatra
The manifold hypothesis (real world data concentrates near low-dimensional manifolds) is suggested as the principle behind the effectiveness of machine learning algorithms in very…