Scaling Large Reasoning Models beyond Human Supervision: A Path toward Superintelligence
Paper recorded by Signals 4 on 2026-08-31 in cs.AI. Abstract reproduced from arXiv; link to the original below.
Published 2026-08-31 on arXiv · recorded by Signals 4 on 2026-09-01
Category: cs.AI · 人工智能 · first seen 2026-09-01
Abstract
Recent advances in large reasoning models (LRMs) have shown that reinforcement learning with verifiable rewards (RLVR) can substantially improve reasoning in mathematics and code, where outcomes can be checked automatically. Extending this progress to open-ended and agentic tasks remains difficult because reliable rewards are harder to obtain and direct human supervision cannot keep pace with the
Read on arXiv →
Cite this page: Scaling Large Reasoning Models beyond Human Supervision: A Path toward Superintelligence: the #251 most recent of 300 cs.AI papers we have recorded (as of 2026-08-31). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/scaling-large-reasoning-models-beyond-human-supervision-a-path-toward-superintel.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable:
papers.json
Get 4 AI signals a day by email — free.
Get 4 AI signals a day by email — free