Average token log-probability provides a zero-shot confidence signal for small LLMs that matches supervised baselines in-distribution and outperforms them out-of-distribution, with a new retrieval-conditional variant improving further at lower latency.
On calibration of modern neural networks,
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2representative citing papers
RACF corrects inconsistent depth camera distance estimates in autonomous vehicles using LiDAR and kinematic redundancy, achieving up to 35% RMSE reduction and better braking in tests on a Quanser QCar 2 platform.
citing papers explorer
-
Zero-Shot Confidence Estimation for Small LLMs: When Supervised Baselines Aren't Worth Training
Average token log-probability provides a zero-shot confidence signal for small LLMs that matches supervised baselines in-distribution and outperforms them out-of-distribution, with a new retrieval-conditional variant improving further at lower latency.
-
RACF: A Resilient Autonomous Car Framework with Object Distance Correction
RACF corrects inconsistent depth camera distance estimates in autonomous vehicles using LiDAR and kinematic redundancy, achieving up to 35% RMSE reduction and better braking in tests on a Quanser QCar 2 platform.