Claim · 2023-12-21 · publication · Stated in source · Supported

The InternVL report, with authors from Nanjing University, OpenGVLab of Shanghai AI Laboratory, Tsinghua University, SenseTime Research and other institutions, was posted to arXiv on 21 December 2023 (version 1).

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

Shanghai Artificial Intelligence Laboratory / 上海人工智能实验室 → published → InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks

Where it appears

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

Claim and evidence

Shanghai Artificial Intelligence Laboratory / 上海人工智能实验室published ↓InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks

Machine-checked, not reviewed by an editorStated in sourceSupported

Supporting evidence: primary · 1 source; Context: primary · 1 source

Date: 2023-12-21 · publication Records dated 2023 →

Scope and limitsA multi-institution paper; recording it under Shanghai AI Laboratory rests on the OpenGVLab affiliation and the OpenGVLab code link, and does not establish sole authorship. Performance claims are out of scope.

The evidence 02

primary sourceSupports the claim

InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks

arXiv · 2023-12-21

Cite the original source

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

Source excerpt

“2 OpenGVLab, Shanghai AI Laboratory”

Location in source Title page, affiliations

How it was read Retrieved directly from the publisher

Machine-checked · 2026-10-31

Source details and check notes

Authors: Zhe Chen; Jiannan Wu; Wenhai Wang
Version: Dated document, retrieved on 2026-10-29 (SHA-256 9c1b09946f5e357f77f5ba2d5395a6d5e53d6f95eecec93b03fbd3205c136768) directly from the publisher. Version: 2312.14238v1. PDF of version 1 (21 December 2023); the abstract page notes a later v3 of 15 January 2024, not inspected. The author list gives the first credited authors only; see the document for the full list.
Canonical address: Open the canonical source ↗
Accessed: 2026-10-29
Language: English (en)
Attribution: Zhe Chen, Jiannan Wu, Wenhai Wang, “InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks”, 2023-12-21.
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, Chinese frontier-AI institutions, third collection (research/china-labs-3). The quotation (5 words) matched the text retrieved for the candidate pack on 2026-10-29 and again in a fresh retrieval the same day, read directly from the publisher. Matching ignored differences of whitespace, case, quotation marks, dashes and Unicode compatibility forms, so the source’s typography can differ. No human editorial review.

primary sourceContext only

InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks

arXiv · 2023-12-21

Cite the original source

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

Source excerpt

“https://github.com/OpenGVLab/InternVL”

Location in source Title page

How it was read Retrieved directly from the publisher

Machine-checked · 2026-10-31

Source details and check notes

Authors: Zhe Chen; Jiannan Wu; Wenhai Wang
Version: Dated document, retrieved on 2026-10-29 (SHA-256 9c1b09946f5e357f77f5ba2d5395a6d5e53d6f95eecec93b03fbd3205c136768) directly from the publisher. Version: 2312.14238v1. PDF of version 1 (21 December 2023); the abstract page notes a later v3 of 15 January 2024, not inspected. The author list gives the first credited authors only; see the document for the full list.
Canonical address: Open the canonical source ↗
Accessed: 2026-10-29
Language: English (en)
Attribution: Zhe Chen, Jiannan Wu, Wenhai Wang, “InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks”, 2023-12-21.
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, Chinese frontier-AI institutions, third collection (research/china-labs-3). The quotation (1 words) matched the text retrieved for the candidate pack on 2026-10-29 and again in a fresh retrieval the same day, read directly from the publisher. Matching ignored differences of whitespace, case, quotation marks, dashes 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. Publication of a specific document or version. Publication of a policy is not evidence of implementation.

Date. Submission date of the cited arXiv version; not the model's release date and not the date of later versions.

Record ID c3-shlab-internvl-report