Papers2

#uncertainty calibration

Calibrate-Then-Act: Cost-Aware Exploration in LLM Agents

Wenxuan Ding, Nicholas Tomlin et al.Feb 18arXiv

This paper teaches AI agents to make smart choices about when to explore for more information and when to act right away.

#Calibrate-Then-Act#cost-aware exploration#LLM agents

Not triaged yet

Beyond Token-level Supervision: Unlocking the Potential of Decoding-based Regression via Reinforcement Learning

Intermediate

Ming Chen, Sheng Tang et al.Dec 6arXiv

The paper shows that making a model write a number as a sequence of digits and then grading the whole number at the end works better than grading each digit separately.

#decoding-based regression#sequence-level reward#reinforcement learning

Not triaged yet