TailRL: RL That Optimizes Tail Rewards Instead of Averages
Researchers including Ruslan Salakhutdinov propose TailRL, which maximizes the tail likelihood of rewards instead of the average, preserving rare high-quality outputs with up to 256x sample savings via GUI localization.
2026-09-07 ~ 2026-09-07 · 2 related posts
- TailRL optimizes reward tails instead of mean, cutting samples 256x on GUI grounding — burny_tech · 2026-09-07
- TailRL: New RL Objective Maximizes Upper-Tail Reward Coverage Instead of Just the Mean — burny_tech · 2026-09-07