Paper Citation Record · LEDGER

MMCOMPOSITION: Revisiting the Compositionality of Pre-trained Vision-Language Models

As of 4 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2410.09733.

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

pith.paper-citation-record.v1
2410.09733 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T10:00:10.824477Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-10T06:15:00.866473Z

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 72696188-7aeb-4108-aa46-b636a46f7385 · inbound

Visual Compositional Tuning cites this paper.

Visual Compositional Tuning MMCOMPOSITION: Revisiting the Compositionality of Pre-trained Vision-Language Models

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-22T17:41:53.105066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation eca0d95a-d76d-416e-bf40-aa99013712fe · inbound

ChartNet: A Million-Scale, High-Quality Multimodal Dataset for Robust Chart Understanding cites this paper.

ChartNet: A Million-Scale, High-Quality Multimodal Dataset for Robust Chart Understanding MMCOMPOSITION: Revisiting the Compositionality of Pre-trained Vision-Language Models

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-14T22:39:32.954917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 27372a24-07a9-4c29-9881-909e16265e62 · inbound

MementoGUI: Learning Agentic Multimodal Memory Control for Long-Horizon GUI Agents cites this paper.

MementoGUI: Learning Agentic Multimodal Memory Control for Long-Horizon GUI Agents MMCOMPOSITION: Revisiting the Compositionality of Pre-trained Vision-Language Models

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-20T11:58:14.947470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 94c3e4ce-b0ce-468f-a1b9-62f70045d21c · inbound

Agent Skills Should Go Beyond Text: The Case for Visual Skills cites this paper.

Agent Skills Should Go Beyond Text: The Case for Visual Skills MMCOMPOSITION: Revisiting the Compositionality of Pre-trained Vision-Language Models

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-06-28T17:12:23.895716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 026b55e2-a04a-44d3-be46-718b85d65819 · inbound

MemoBench: Benchmarking World Modeling in Dynamically Changing Environments cites this paper.

MemoBench: Benchmarking World Modeling in Dynamically Changing Environments MMCOMPOSITION: Revisiting the Compositionality of Pre-trained Vision-Language Models

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-07-01T18:25:57.789709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 30318801-6c61-45bb-a607-f13110a5bcf6 · inbound

MemoBench: Benchmarking World Modeling in Dynamically Changing Environments cites this paper.

MemoBench: Benchmarking World Modeling in Dynamically Changing Environments MMCOMPOSITION: Revisiting the Compositionality of Pre-trained Vision-Language Models

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-07-01T09:35:40.670430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 7104efbb-ce55-4f2d-ab61-b9bca81830da · inbound

MemoBench: Benchmarking World Modeling in Dynamically Changing Environments cites this paper.

MemoBench: Benchmarking World Modeling in Dynamically Changing Environments MMCOMPOSITION: Revisiting the Compositionality of Pre-trained Vision-Language Models

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-07-02T20:57:22.793660Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 4aafa573-09b4-42ca-982f-898331afc419 · inbound

MemoBench: Benchmarking World Modeling in Dynamically Changing Environments cites this paper.

MemoBench: Benchmarking World Modeling in Dynamically Changing Environments MMCOMPOSITION: Revisiting the Compositionality of Pre-trained Vision-Language Models

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-07-03T22:49:00.915059Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 00aa0689-4103-4c6e-891b-8480f87b4465 · inbound

MemoBench: Benchmarking World Modeling in Dynamically Changing Environments cites this paper.

MemoBench: Benchmarking World Modeling in Dynamically Changing Environments MMCOMPOSITION: Revisiting the Compositionality of Pre-trained Vision-Language Models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-07-14T17:14:19.770867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 84daaa27-8626-4168-b9ee-cc3c1c2e9e5e · inbound

MemoBench: Benchmarking World Modeling in Dynamically Changing Environments cites this paper.

MemoBench: Benchmarking World Modeling in Dynamically Changing Environments MMCOMPOSITION: Revisiting the Compositionality of Pre-trained Vision-Language Models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-02T10:00:10.824477Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 42c656a9-cb30-441c-9236-974d2d20ed31 · inbound

Learning to Compose: Revisiting Proxy Task Design for Zero-Shot Composed Image Retrieval cites this paper.

Learning to Compose: Revisiting Proxy Task Design for Zero-Shot Composed Image Retrieval MMCOMPOSITION: Revisiting the Compositionality of Pre-trained Vision-Language Models

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-07-02T15:17:07.310166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.