RESEARCHMonitorNEXT 12 MONTHS
Reinforcement Learning Done Right for Explicit Confidence Targets
arXiv cs.CL — Computation and Language
Factual evidence
What the source reports
Researchers propose a reinforcement learning method enabling LLMs to dynamically adjust abstention thresholds based on confidence targets.
Inspect the evidence
- Inclusion basis
- Enterprise AI
- Publisher and source type
- arXiv cs.CL — Computation and Language · RESEARCH
- Published by source
- 27 October 2026
- Collected by OneBench
- 28 Oct 2026, 02:01 UK
- Original headline
- Reinforcement Learning Done Right for Explicit Confidence Targets ↗
Stored source excerpt
arXiv:2610.35059v1 Announce Type: cross Abstract: Large language models (LLMs) can produce plausible but incorrect answers when they are uncertain, which can mislead users and undermine…
Short excerpt from the collected text, not the full source. Use the source link to read it in context.
The factual summary is a OneBench synthesis, not a quotation or independent verification. Collection time is not publication time. Open the source for its full context; related reporting can share the same underlying announcement.