Claim · 2019-04-26 · event · Stated in source · Supported

Mao et al. (2019) name their model the Neuro-Symbolic Concept Learner, which learns visual concepts, words and semantic parsing from images and question-answer pairs.

One recorded claim. The claim panel gives its qualification, the source passages with their place in each source, and how it was checked.

What it connects

The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural Supervision → uses the name →

Where it appears

No collection page holds this claim. It is listed with its records in the explorer.

Claim and evidence

The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural Supervisionuses the name ↓

Machine-checked, not reviewed by an editorStated in sourceSupported

Supporting evidence: primary · 1 source

Date: 2019-04-26 · event Records dated 2019 →

Scope and limits"We propose" is the paper's own statement.

The evidence 01

primary sourceSupports the claim

The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural Supervision

arXiv (v1) · 2019

Cite the original source

Cite the original document, not Selekoa. Check these details against it.

Source excerpt

“We propose the Neuro-Symbolic Concept Learner (NS-CL), a model that learns visual concepts, words, and semantic parsing of sentences without explicit supervision on any of them”

Location in source PDF p. 1, abstract

How it was read Retrieved directly from the publisher

Machine-checked · 2026-10-31

Source details and check notes

Authors: Jiayuan Mao; Chuang Gan; Pushmeet Kohli; Joshua B. Tenenbaum; Jiajun Wu
Version: Retrieved for the candidate pack on 2026-10-29 (SHA-256 fe8ac827268b24f30384ccde2c3f6b1a6f71d7cdff589ff262b6a43eca0dff3b). arXiv:1904.12584v1 PDF, headed "Published as a conference paper at ICLR 2019".
Canonical address: Open the canonical source ↗
Accessed: 2026-10-29
Language: English (en)
Attribution: Jiayuan Mao, Chuang Gan, Pushmeet Kohli, Joshua B. Tenenbaum, Jiajun Wu, “The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural Supervision”, 2019.
Reuse: No open redistribution licence asserted. Bibliographic metadata, editorial paraphrases and short attributed quotations (at most 50 words each). Recheck terms before wider redistribution.
Check notes: Candidate pack passage, Kinds of AI and technical history (research/technical-history). The quotation (26 words) matched the text retrieved for the candidate pack on 2026-10-29. Matching ignored differences of whitespace, case, quotation marks, dashes, PDF line-break hyphens and Unicode compatibility forms, so the source’s typography can differ. No human editorial review.

Status and meaning

Editorial status. Not reviewed by an editor. An exploratory record that no editor has accepted. This status does not say whether a person has read any linked passage. Each evidence record above shows how it was checked.

Relation. A passage of the document uses a name for a family of methods or a term, in the sense the concept’s naming criterion describes or, where labelled, in another sense. The record documents the use; it is not evidence that the name began there, and it implies no influence on or from another text.

Date. Date of submission (an arXiv version or a journal’s received date, as the source states it); not a later revision or the venue’s publication date.

Record ID th-ns-mao-2019-term