1 citations · 1 across the 1 of their papers we have counts for
2 papers
cs.CL2024★ 1 cited
Diversify and Conquer: Diversity-Centric Data Selection with Iterative Refinement
Simon Yu, Liangyu Chen, Sara Ahmadian +1
Finetuning large language models on instruction data is crucial for enhancing pre-trained knowledge and improving instruction-following capabilities. As instruction datasets prolif…
cs.DS2024
GIST: Greedy Independent Set Thresholding for Max-Min Diversification with Submodular Utility
Matthew Fahrbach, Srikumar Ramalingam, Morteza Zadimoghaddam +3
This work studies a novel subset selection problem called max-min diversification with monotone submodular utility (), which has a wide range of applications in mach…