SourceScore

Verified claim · AI-ML · 100% confidence

Toolformer introduced in: Schick et al. 2023 — self-supervised LLM tool-use.

Last verified 2026-05-16 · Methodology veritas-v0.1 · cd4387e16e2c3e3d

Structured fields

Subject
Toolformer
Predicate
introduced_in
Object
Schick et al. 2023 — self-supervised LLM tool-use
Confidence
100%
Tags
toolformer · meta-ai · tool-use · function-calling · agents · 2023 · introduced_in

Sources (2)

  1. [1] preprint · arXiv (Schick, Dwivedi-Yu, Dessì, Raileanu, Lomeli, Zettlemoyer, Cancedda, Scialom / Meta AI) · 2023-02-09

    Toolformer: Language Models Can Teach Themselves to Use Tools
    In this paper, we show that LMs can teach themselves to use external tools via simple APIs and achieve the best of both worlds. We introduce Toolformer, a model trained to decide which APIs to call, when to call them, what arguments to pass, and how to best incorporate the results into future token prediction. This is done in a self-supervised way, requiring nothing more than a handful of demonstrations for each API.
  2. [2] official blog · Meta AI · 2023-02-09

    Toolformer — Meta AI Research publication

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Toolformer introduced in: Schick et al. 2023 — self-supervised LLM tool-use. — SourceScore Claim cd4387e16e2c3e3d (verified 2026-05-16). https://sourcescore.org/api/v1/claims/cd4387e16e2c3e3d.json

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LangChain (retrieve-then-cite)

from langchain_core.tools import tool import httpx @tool def get_toolformer_fact() -> dict: """Fetch the verified SourceScore claim for Toolformer.""" r = httpx.get("https://sourcescore.org/api/v1/claims/cd4387e16e2c3e3d.json") return r.json()