Safety as Computation: Certified Answer Reuse via Capability Closure in Task-Oriented Dialogue
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Abstract (arXiv)
We introduce a new paradigm for task-oriented dialogue systems: safety certification as a computational primitive for answer reuse. Current systems treat each turn independently, recomputing answers via retrieval or generation even when they are already derivable from prior state. We show that in capability-based systems, the safety certification step computes a fixed-point closure cl(At) that already contains every answer reachable from the current configuration. We operationalize this insight with a Certified Answer Store (CAS) augmented by Pre-Answer Blocks (PAB): at each certified turn, the system materializes all derivable follow-up answers together with minimal provenance witnesses. Subsequent queries are answered in sub-millisecond time via formal containment checks, eliminating redundant retrieval and generation.
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References · 15
- 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,355
- 2023Toolformer: Language Models Can Teach Themselves to Use Toolscited by 4,072
- 2023ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIscited by 1,880
- 2024From Local to Global: A Graph RAG Approach to Query-Focused Summarizationcited by 1,411
- 2018MultiWOZ -- A Large-Scale Multi-Domain Wizard-of-Oz Dataset for Task-Oriented Dialogue Modellingcited by 760
- 2020A Simple Language Model for Task-Oriented Dialoguecited by 331
- 2019Transferable Multi-Domain State Generator for Task-Oriented Dialogue Systemscited by 215
- 2020MultiWOZ 2.2 : A Dialogue Dataset with Additional Annotation Corrections and State Tracking Baselinescited by 201
- 2020TripPy: A Triple Copy Strategy for Value Independent Neural Dialog State Trackingcited by 130
- 2019Proactive Human-Machine Conversation with Explicit Conversation Goalscited by 87
- 2018From Eliza to XiaoIce: Challenges and Opportunities with Social Chatbotscited by 85
- 2024Beyond-RAG: Question Identification and Answer Generation in Real-Time Conversationscited by 9
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