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FADE: Factored Ability--Difficulty Filtering for Online RLVR Scheduling

Paper recorded by Signals 4 on 2026-11-02 in cs.LG. Abstract reproduced from arXiv; link to the original below.

Published 2026-11-02 on arXiv · recorded by Signals 4 on 2026-11-03

Category: cs.LG · 机器学习 · first seen 2026-11-03

Abstract

Group-based reinforcement learning with verifiable rewards (RLVR) learns only from prompts whose sampled completions disagree: all-pass and all-fail groups produce zero relative advantage and burn generation budget without moving the policy. Adaptive schedulers try to steer rollouts toward informative prompts, yet they rely on per-prompt pass-rate trackers that entangle two quantities evolving at

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#18 most recent of 703 cs.LG papers we have recorded · ↑ newer: Not All Reasoning Generalizes: A Case Study on Learning Generalizable · ↓ older: Thought-deciphering via hierarchical EEG-to-text alignment
Cite this page: FADE: Factored Ability--Difficulty Filtering for Online RLVR Scheduling: the #18 most recent of 703 cs.LG papers we have recorded (as of 2026-11-02). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/fade-factored-ability-difficulty-filtering-for-online-rlvr-scheduling.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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