SourceScore

Verified claim · AI-ML · 100% confidence

Phi-4 released on: 2024-12-12 by Microsoft Research.

Last verified 2026-05-16 · Methodology veritas-v0.1 · f75020a0604daad7

SourceScore rates how reliable a source is to cite — for AI answers and research. This is one verified claim from the catalog.

Structured fields

Subject
Phi-4
Predicate
released_on
Object
2024-12-12 by Microsoft Research
Confidence
100%
Tags
phi-4 · microsoft · synthetic-data · small-language-model · 2024 · released_on

Sources (2)

  1. [1] preprint · arXiv (Abdin, Aneja, Behl, Bubeck, et al. / Microsoft Research) · 2024-12-12

    Phi-4 Technical Report
    We present phi-4, a 14-billion parameter language model developed with a training recipe that is centrally focused on data quality. Unlike most language models, where pre-training is based primarily on organic data sources such as web content or code, phi-4 strategically incorporates synthetic data throughout the training process.
  2. [2] model card · Microsoft Research · 2024-12-12

    Phi-4 — Hugging Face model card

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Phi-4 released on: 2024-12-12 by Microsoft Research. — SourceScore Claim f75020a0604daad7 (verified 2026-05-16). https://sourcescore.org/api/v1/claims/f75020a0604daad7.json

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Frequently asked questions

Is the claim "Phi-4 released on: 2024-12-12 by Microsoft Research." verified?

Yes — SourceScore verified this claim with 100% confidence as of 2026-05-16. The verification uses 2 primary sources cross-referenced against the SourceScore methodology (version veritas-v0.1). Full source list + signed JSON envelope linked below.

What is the evidence for "Phi-4 released on: 2024-12-12 by Microsoft Research."?

Evidence comes from 2 primary sources: arXiv (Abdin, Aneja, Behl, Bubeck, et al. / Microsoft Research), Microsoft Research. Each source is listed below with verbatim excerpts and URLs. The signed JSON envelope at https://sourcescore.org/api/v1/claims/f75020a0604daad7.json includes an HMAC-SHA256 signature for audit verification.

When was this claim last verified by SourceScore?

Last verified 2026-05-16 under methodology version veritas-v0.1. The signed JSON envelope is dated and cryptographically signed for audit trail. Re-verification cadence depends on the claim type and source freshness.

How can I cite this SourceScore claim in my code or article?

Fetch the signed JSON envelope from https://sourcescore.org/api/v1/claims/f75020a0604daad7.json which includes the verbatim claim, primary sources, confidence, methodology version, last-verified date, and HMAC-SHA256 signature for audit. The CC-BY-4.0 license permits commercial use with attribution to SourceScore.

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cURL

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JavaScript / TypeScript

const r = await fetch("https://sourcescore.org/api/v1/claims/f75020a0604daad7.json"); const envelope = await r.json(); console.log(envelope.claim.statement); // "Phi-4 released on: 2024-12-12 by Microsoft Research."

Python

import httpx r = httpx.get("https://sourcescore.org/api/v1/claims/f75020a0604daad7.json") envelope = r.json() print(envelope["claim"]["statement"]) # "Phi-4 released on: 2024-12-12 by Microsoft Research."

LangChain (retrieve-then-cite)

from langchain_core.tools import tool import httpx @tool def get_phi_4_fact() -> dict: """Fetch the verified SourceScore claim for Phi-4.""" r = httpx.get("https://sourcescore.org/api/v1/claims/f75020a0604daad7.json") return r.json()
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