2 citations · 4 across the 2 of their papers we have counts for
2 papers
cs.LG2023★ 2 cited
Prompt Generate Train (PGT): Few-shot Domain Adaption of Retrieval Augmented Generation Models for Open Book Question-Answering
C. S. Krishna
We propose a framework - Prompt, Generate, Train (PGT) - to efficiently develop a generative question-answering model for open-book question-answering over a proprietary collection…
cs.LG2020★ 2 cited
Hyperparameter optimization with REINFORCE and Transformers
Chepuri Shri Krishna, Ashish Gupta, Swarnim Narayan +2
Reinforcement Learning has yielded promising results for Neural Architecture Search (NAS). In this paper, we demonstrate how its performance can be improved by using a simplified T…