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cs.LG2025
How Many Parameters Does Your Task Really Need? Task Specific Pruning with LLM-Sieve
Waleed Reda, Abhinav Jangda, Krishna Chintalapudi
As Large Language Models (LLMs) are increasingly deployed for narrow tasks in resource-constrained settings, a central question arises: how much of an LLM is truly necessary for a…
cs.LG2020
MCAL: Minimum Cost Human-Machine Active Labeling
Hang Qiu, Krishna Chintalapudi, Ramesh Govindan
Today, ground-truth generation uses data sets annotated by cloud-based annotation services. These services rely on human annotation, which can be prohibitively expensive. In this p…