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cs.LG2026
DRIFT: Data Selection for LLM Instruction Tuning via On-Policy Attribution
Zefan Wang, Lincheng Li, Tianyu Yu +1
Data selection for instruction tuning is usually studied for efficiency, reaching strong performance with a fraction of the training data. We ask whether data selection can instead…
cs.LG2025
RLPR: Extrapolating RLVR to General Domains without Verifiers
Tianyu Yu, Bo Ji, Shouli Wang +9
Reinforcement Learning with Verifiable Rewards (RLVR) demonstrates promising potential in advancing the reasoning capabilities of LLMs. However, its success remains largely confine…