Constrained decoding derived from OpenAPI specifications eliminates hallucinated web API calls in LLM-generated code and substantially improves correctness across 24 models, while retrieval-augmented generation yields inconsistent, model-dependent gains.
Dialog2API: Task-Oriented Dialogue with API Description and Example Programs
2 Pith papers cite this work, alongside 1 external citations. Polarity classification is still indexing.
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abstract
Functionality and dialogue experience are two important factors of task-oriented dialogue systems. Conventional approaches with closed schema (e.g., conversational semantic parsing) often fail as both the functionality and dialogue experience are strongly constrained by the underlying schema. We introduce a new paradigm for task-oriented dialogue - Dialog2API - to greatly expand the functionality and provide seamless dialogue experience. The conversational model interacts with the environment by generating and executing programs triggering a set of pre-defined APIs. The model also manages the dialogue policy and interact with the user through generating appropriate natural language responses. By allowing generating free-form programs, Dialog2API supports composite goals by combining different APIs, whereas unrestricted program revision provides natural and robust dialogue experience. To facilitate Dialog2API, the core model is provided with API documents, an execution environment and optionally some example dialogues annotated with programs. We propose an approach tailored for the Dialog2API, where the dialogue states are represented by a stack of programs, with most recently mentioned program on the top of the stack. Dialog2API can work with many application scenarios such as software automation and customer service. In this paper, we construct a dataset for AWS S3 APIs and present evaluation results of in-context learning baselines.
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cs.SE 2years
2026 2representative citing papers
Proposes GODR, a framework-neutral runtime pattern treating goals and their lifecycle as first-class objects for complex, interruptible multi-domain dialogues.
citing papers explorer
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Mitigating Errors in LLM-Generated Web API Invocations via Retrieval-Augmented Generation and Constrained Decoding
Constrained decoding derived from OpenAPI specifications eliminates hallucinated web API calls in LLM-generated code and substantially improves correctness across 24 models, while retrieval-augmented generation yields inconsistent, model-dependent gains.
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From Task-Guided Conversational Graphs to Goal-Oriented Dialogue Runtimes
Proposes GODR, a framework-neutral runtime pattern treating goals and their lifecycle as first-class objects for complex, interruptible multi-domain dialogues.