4 citations · 12 across the 17 of their papers we have counts for
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cs.AI2026
Probe-and-Resume: When and How to Evaluate Agent Execution
Jiakai Xu, Tiancheng Ge, Tujie Guan +4
Test-time search can improve agent performance by exploring alternative actions and using a critic to select promising branches. We study this approach in terminal-based computer-u…
cs.AI2025★ 1 cited
Speculative Actions: A Lossless Framework for Faster Agentic Systems
Naimeng Ye, Arnav Ahuja, Georgios Liargkovas +3
AI agents are increasingly deployed in complex, interactive environments, yet their runtime remains a major bottleneck for training, evaluation, and real-world use. Typical agent b…