Dylan Zhang

The Best Instruction-Tuning Data are Those That Fit

$PLUM$: Improving Code LMs Using On-Policy Preference Learning Powered by Automatic Test Cases

Improving Influence-based Instruction Tuning Data Selection for Balanced Learning of Diverse Capabilities

$Only-IF$: Revealing the Decisive Effect of Instruction Diversity on Generalization