Showing cs.LGShow all
2 papers · 1 filter
cs.LG2026
Probe the Harness: Setup Checks for Stale-Data RL Comparisons in Language Models
Taiheng Pan
Methods for training language models on stale samples are judged by comparisons against importance-corrected baselines. We show that details of the experimental harness can reverse…
cs.LG2026
Cool the Sampler, Not the Learner: Sampling Temperature Moves the Staleness Cliff of Importance-Corrected GRPO
Taiheng Pan
Production RL for language models lets the sampler fall behind the learner and repairs the resulting mismatch with a truncated importance weight. We ask how long the sampler can go…