Papers with dialog progression

1 papers
DyBBT: Dynamic Balance via Bandit-inspired Targeting for Dialog Policy with Cognitive Dual Systems (2026.acl-long)

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Challenge: Task oriented dialog systems often rely on static exploration strategies that do not adapt to dynamic dialog contexts.
Approach: They propose a dialog policy learning framework that formalizes the exploration challenge through a structured cognitive state space C.
Outcome: The proposed framework achieves SOTA performance in success rate, efficiency, and generalization.

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