Claim · 2020-02-14 · event · Stated in source · Supported

According to Marcus (2020), Mao et al. (2019) proposed a hybrid neural net-symbolic system for visual question answering, NS-CL, that surpassed the deep-learning alternatives they examined.

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 Next Decade in AI: Four Steps Towards Robust Artificial Intelligence → attributes to → The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural Supervision

Where it appears

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

Claim and evidence

The Next Decade in AI: Four Steps Towards Robust Artificial Intelligenceattributes to ↓The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural Supervision

Machine-checked, not reviewed by an editorStated in sourceSupported

Supporting evidence: primary · 1 source

Date: 2020-02-14 · event Records dated 2020 →
Kind of attribution: Summarises an argument or finding of the work

Scope and limitsAttributed statement; the performance comparison is reported by Marcus from the cited paper, not checked here.

The evidence 01

primary sourceSupports the claim

The Next Decade in AI: Four Steps Towards Robust Artificial Intelligence

arXiv (v3) · 2020-02-14

Cite the original source

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

Source excerpt

“have recently proposed a hybrid neural net-symbolic system for visual question answering called NS-CL (short for the Neuro-Symbolic concept learner) that surpasses the deep learning alternatives they examined.”

Location in source PDF p. 18, section 2.1

How it was read Retrieved directly from the publisher

Machine-checked · 2026-10-31

Source details and check notes

Authors: Gary Marcus
Version: Retrieved for the candidate pack on 2026-10-29 (SHA-256 80cb5a5ab68821a7a9cfd86f690622112f5957fcb49cbb783a1cf5b66348a926). arXiv:2002.06177v3 PDF, dated on its title page 17 February 2020.
Canonical address: Open the canonical source ↗
Accessed: 2026-10-29
Language: English (en)
Attribution: Gary Marcus, “The Next Decade in AI: Four Steps Towards Robust Artificial Intelligence”, 2020-02-14.
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 (28 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. The source role is primary for this record: the passage is the citing text’s own attribution, which is what the record states (corrected at admission; the pack had secondary, relative to the work credited). A cross-family machine check (31 October 2026, item 89) re-read the record’s sources and found that they support what the record states. 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 document expressly attributes an argument, concept, term, finding or approach to another work, in its own words; the kind of attribution is recorded. The record is the citing document’s claim. It is not evidence that the cited work originated the idea, that the attribution is accurate, or of influence beyond the passage. Citation alone is recorded as a citation.

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-marcus-credits-mao