SPIN Unprocessed October 26, 2026 ai_technology research
Free Lunch for LLMs Confidence: The RL Critic Already Knows
View original on arxiv.orgOverview
arXiv:2610.31820v1 Announce Type: new Abstract: Reliable confidence estimation is essential for trustworthy deployment of large language models (LLMs), but dedicated confidence training stage requires additional data and compute. We ask a fundamental question: what prediction problem does confidence training actually solve? Inspired by prior work on external confidence estimation, we compare self- and external estimators of comparable capacity trained on the same (question, response, correctness
SpinGraph analysis pending — check back after processing.
Ask AI about this story
Opens with the SpinGraph .md URL and structured context — one click, prompt included.
More from arXiv Computation and Language
View all →- LazyFlash: Forward-Dense, Backward-Sparse Attention for Accelerated Long-Context Fine-Tuning
- TaxoSAE: Rethinking Sparse Autoencoders through Taxonomic Logic
- Mining Frames: Association Rule Mining as an Unsupervised Framework for News Framing Detection
- Machine-Readable Operator Manuals over the ISO 11783 Network for Offline, Multilingual LLM Assistance
- Scaling cross-situational word learning on children's naturalistic experiences
- SPECMEM: Accelerating Agentic Tool Calling via Live Memory Management
Markdown (.md) · JSON-LD schema (.json) · Machine-readable for AI & GEO