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cs.CL2025
ADAPT: Learning Task Mixtures for Budget-Constrained Instruction Tuning
Pritam Kadasi, Abhishek Upperwal, Mayank SIngh
We propose ADAPT, a meta-learning algorithm that \emph{learns} task sampling proportions under an explicit token budget for multi-task instruction tuning. Instead of fixing task we…
cs.CL2025
Model Hubs and Beyond: Analyzing Model Popularity, Performance, and Documentation
Pritam Kadasi, Sriman Reddy Kondam, Srivathsa Vamsi Chaturvedula +7
With the massive surge in ML models on platforms like Hugging Face, users often lose track and struggle to choose the best model for their downstream tasks, frequently relying on m…