Paper Citation Record · LEDGER

T-MARS: Improving Visual Representations by Circumventing Text Feature Learning

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2307.03132.

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

pith.paper-citation-record.v1
2307.03132 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T15:27:08.832852Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T09:49:44.890982Z

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 23bc8428-552b-496b-adcd-0b06efbf0260 · inbound

The Double-Ellipsoid Geometry of CLIP cites this paper.

The Double-Ellipsoid Geometry of CLIP T-MARS: Improving Visual Representations by Circumventing Text Feature Learning

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-12T15:27:08.832852Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0b583fd8-0396-49e2-97a4-b4c83b491f1a · inbound

Active Data Curation Effectively Distills Large-Scale Multimodal Models cites this paper.

Active Data Curation Effectively Distills Large-Scale Multimodal Models T-MARS: Improving Visual Representations by Circumventing Text Feature Learning

Reference 103

Resolution: unresolved; no resolver link, observed 2026-08-12T11:06:36.076847Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7ab61e17-d0ee-4519-8ef5-cf6420d81bda · inbound

Scaling Pre-training to One Hundred Billion Data for Vision Language Models cites this paper.

Scaling Pre-training to One Hundred Billion Data for Vision Language Models T-MARS: Improving Visual Representations by Circumventing Text Feature Learning

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-08T12:12:30.745548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 77f46a19-d285-4d68-a19c-1866b54a68c0 · inbound

Quality over Quantity: Boosting Data Efficiency Through Ensembled Multimodal Data Curation cites this paper.

Quality over Quantity: Boosting Data Efficiency Through Ensembled Multimodal Data Curation T-MARS: Improving Visual Representations by Circumventing Text Feature Learning

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-08T06:06:17.557918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d9da09a4-3fe4-4be0-b30a-ed005f0366b4 · inbound

What Does the Caption Really Say? Counterfactual Phrase Intervention for Compositional Data Selection in Vision-Language Pretraining cites this paper.

What Does the Caption Really Say? Counterfactual Phrase Intervention for Compositional Data Selection in Vision-Language Pretraining T-MARS: Improving Visual Representations by Circumventing Text Feature Learning

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-22T06:21:10.270477Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f069d1dc-4508-474e-b932-b754e49d125b · inbound

Data Selection Through Iterative Self-Filtering for Vision-Language Settings cites this paper.

Data Selection Through Iterative Self-Filtering for Vision-Language Settings T-MARS: Improving Visual Representations by Circumventing Text Feature Learning

Reference 77

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T09:49:44.892311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 82be6d52-1da5-4d4c-ba4e-2ed518577dd6 · inbound

DataComp-VLM: Improved Open Datasets for Vision-Language Models cites this paper.

DataComp-VLM: Improved Open Datasets for Vision-Language Models T-MARS: Improving Visual Representations by Circumventing Text Feature Learning

Reference 200

Resolution: verified exact; arxiv_id, observed 2026-07-01T15:45:47.689741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f75d8715-046b-4d2c-9685-fdcde13bd79b · inbound

DataComp-VLM: Improved Open Datasets for Vision-Language Models cites this paper.

DataComp-VLM: Improved Open Datasets for Vision-Language Models T-MARS: Improving Visual Representations by Circumventing Text Feature Learning

Reference 200

Resolution: verified exact; arxiv_id, observed 2026-07-02T21:17:23.898703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.