Papers by Yunbo Tang

1 papers
BAPO: Boundary-Aware Policy Optimization for Reliable Agentic Search (2026.findings-acl)

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Challenge: Existing RL-based agentic search models fail to recognize reasoning boundaries and rarely admit "I DON'T KNOW" lack of reliability leads to plausible but unreliable answers, introducing significant risks .
Approach: They propose a framework to cultivate reliable boundary awareness without compromising accuracy.
Outcome: Experiments show that the proposed framework improves the reliability of agentic search models.

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