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Paper Citation Record · LEDGER

X$^2$-VLM: All-In-One Pre-trained Model For Vision-Language Tasks

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2211.12402.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2211.12402 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:00:34.127001Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-18T13:02:37.495563Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 78aefb08-78d4-476d-a35f-ae965cd083a0 · inbound

Vision-Language Foundation Models as Effective Robot Imitators cites this paper.

Vision-Language Foundation Models as Effective Robot Imitators X$^2$-VLM: All-In-One Pre-trained Model For Vision-Language Tasks

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-16T21:44:27.636185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-16T21:44:27.562453Z digest=sha256:38d521febdb2716419a942c0ce485562bf5d6a215c4f65222455fc2bf34297e6

Observation 2c153e38-dc5b-44ca-af25-dcc294b3b58b · inbound

Visual question answering: from early developments to recent advances -- a survey cites this paper.

Visual question answering: from early developments to recent advances -- a survey X$^2$-VLM: All-In-One Pre-trained Model For Vision-Language Tasks

Reference 107

Resolution
unresolved
no resolver link, observed 2026-08-10T21:46:28.542444Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T21:46:28.542444Z digest=sha256:ba6a29a79a38580887c64c3500a78b6e638a6fc319f6f01db3f615386cbd3f2c

Observation 803b90c5-5350-4593-ad3e-b099f4f80ad1 · inbound

Admitting Ignorance Helps the Video Question Answering Models to Answer cites this paper.

Admitting Ignorance Helps the Video Question Answering Models to Answer X$^2$-VLM: All-In-One Pre-trained Model For Vision-Language Tasks

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-10T20:22:28.836606Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:22:28.836606Z digest=sha256:8e859367a1d90106136318535e9df59efb14a13c6645daf8c5f6639b073b9327

Observation 005fd9fe-3143-454f-aafd-b152152a3729 · inbound

Investigating the Effect of Parallel Data in the Cross-Lingual Transfer for Vision-Language Encoders cites this paper.

Investigating the Effect of Parallel Data in the Cross-Lingual Transfer for Vision-Language Encoders X$^2$-VLM: All-In-One Pre-trained Model For Vision-Language Tasks

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-16T05:00:34.127001Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:00:34.127001Z digest=sha256:223b0f648b2ed8d20322e029c1fe8c4570e4781d7700b3fe8947cdb7b8a47ed2

Observation ca5c8fa8-8eab-468f-94a3-3dc0f21a84ff · inbound

Multilingual Vision-Language Models, A Survey cites this paper.

Multilingual Vision-Language Models, A Survey X$^2$-VLM: All-In-One Pre-trained Model For Vision-Language Tasks

Reference 164

Resolution
verified exact
arxiv_id, observed 2026-05-18T13:02:37.498107Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-18T13:02:08.000814Z digest=sha256:f3394fe73c86d50ca76ae9858b225aa4b7c0eb4012d56c4ae9fb3da41fa59c6b