arXiv CS AI#tech
Test-Time Deep Thinking to Explore Implicit Rulestranslating…
Factuality: 90/100USACornell University
arXiv:2605.24828v1 Announce Type: new
Abstract: With the continuous advancement of Large Language Models (LLMs), intelligent agents are becoming increasingly vital. However, these agents often fail in environments governed by implicit rules--hidden constraints that cannot be observed directly and must be inferred through interaction. This causes agents to fall into repetitive trial-and-error loops, ultimately leading to task failure. To address this challenge, we propose Test-Time Exploration (