22 citations · 73 across the 11 of their papers we have counts for
3 papers · 1 filter
Beyond Active Learning: Leveraging the Full Potential of Human Interaction via Auto-Labeling, Human Correction, and Human Verification
Nathan Beck, Krishnateja Killamsetty, Suraj Kothawade +1
Active Learning (AL) is a human-in-the-loop framework to interactively and adaptively label data instances, thereby enabling significant gains in model performance compared to rand…
INGENIOUS: Using Informative Data Subsets for Efficient Pre-Training of Language Models
H S V N S Kowndinya Renduchintala, Krishnateja Killamsetty, Sumit Bhatia +4
A salient characteristic of pre-trained language models (PTLMs) is a remarkable improvement in their generalization capability and emergence of new capabilities with increasing mod…
MILO: Model-Agnostic Subset Selection Framework for Efficient Model Training and Tuning
Krishnateja Killamsetty, Alexandre V. Evfimievski, Tejaswini Pedapati +3
Training deep networks and tuning hyperparameters on large datasets is computationally intensive. One of the primary research directions for efficient training is to reduce trainin…