RL-ADA: A World-Feedback Framework for Adversarially Robust Enterprise Dialogue Agents
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arXiv:2609.02902v1 Announce Type: new Abstract: Deploying task-oriented dialogue agents in enterprise customer support faces a persistent annotation bottleneck: robust training requires labelled interaction data at scale, yet enterprise conversational logs are privacy-sensitive and expensive to ann…
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- 2026-09-04 04:00 · arXiv cs.CL
RL-ADA: A World-Feedback Framework for Adversarially Robust Enterprise Dialogue Agents
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