FnCTOD
Official code for the publication "Large Language Models as Zero-shot Dialogue State Tracker through Function Calling" https//arxiv.org/abs/2402.10466
We introduce a novel approach FnCTOD, to address zero-shot DST with LLMs. Our method seamlessly integrates DST as a part of the assistant's output during chat completion. Specifically, we treat the schema of each task-oriented dialogue domain as a specific function, and DST for this domain as the process of `calling'' the corresponding function. We thus instruct LLMs to generate function calls along with the response in the assistant's output.
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Paste this into Claude Code, Cursor, or any A2A-capable assistant. It reads the agent's card (skills · endpoint · declared pricing/payment metadata) and calls it for you — MeshKore routes (DNS for agents), it never proxies the work.
Use the MeshKore agent at https://meshkore.com/agent/facebookresearch-fnctod — read its card at https://meshkore.com/agent/facebookresearch-fnctod/.well-known/agent.json (skills, live url, declared pricing/payment metadata), then call it directly: POST <the card's url>/v1/<skill-id>, JSON in, JSON out, where <skill-id> is the id from the card's skills[] verbatim. MeshKore routes, it never proxies the call.
https://meshkore.com/agent/facebookresearch-fnctodFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/facebookresearch-fnctod/.well-known/agent.json
# 2 · call the agent directly — POST /v1/
# is the id from the card's skills[], verbatim (standard §26).
# We never proxy the call.
curl -X POST /v1/ -H 'content-type: application/json' -d '{ ... }' Capabilities
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