SourceScore

Verified claim · AI-ML · 100% confidence

Layer Normalization introduced in paper: Layer Normalization (Ba, Kiros, Hinton, 2016).

Last verified 2026-05-16 · Methodology veritas-v0.1 · f72db86c784a1b32

Structured fields

Subject
Layer Normalization
Predicate
introduced_in_paper
Object
Layer Normalization (Ba, Kiros, Hinton, 2016)
Confidence
100%
Tags
layer-normalization · normalization · transformer-ingredient · foundational · 2016 · hinton

Sources (1)

  1. [1] preprint · arXiv (Ba, Kiros, Hinton) · 2016-07-21

    Layer Normalization
    We transpose batch normalization into layer normalization by computing the mean and variance used for normalization from all of the summed inputs to the neurons in a layer on a single training case.

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Layer Normalization introduced in paper: Layer Normalization (Ba, Kiros, Hinton, 2016). — SourceScore Claim f72db86c784a1b32 (verified 2026-05-16). https://sourcescore.org/api/v1/claims/f72db86c784a1b32.json

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import httpx r = httpx.get("https://sourcescore.org/api/v1/claims/f72db86c784a1b32.json") envelope = r.json() print(envelope["claim"]["statement"]) # "Layer Normalization introduced in paper: Layer Normalization (Ba, Kiros, Hinton, 2016)."

LangChain (retrieve-then-cite)

from langchain_core.tools import tool import httpx @tool def get_layer_normalization_fact() -> dict: """Fetch the verified SourceScore claim for Layer Normalization.""" r = httpx.get("https://sourcescore.org/api/v1/claims/f72db86c784a1b32.json") return r.json()