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Paper Citation Record · LEDGER

Reproducible scaling laws for contrastive language-image learning

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2212.07143.

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

pith.paper-citation-record.v1
2212.07143 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 13 of 13 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 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:50:21.488475Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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

External citation measurements

29
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation b08436f6-1ac7-4119-939d-30cfa8f90f41 · inbound

BiomedCLIP: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairs cites this paper.

BiomedCLIP: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairs Reproducible scaling laws for contrastive language-image learning

Reference 62

Resolution
verified exact
arxiv_id, observed 2026-05-13T10:42:22.444828Z

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=2026-05-13T10:42:22.378367Z digest=sha256:9efa9bbdf91acdd4e7e767a81463d0c0470b90deb57fc0e02334af31a3e8b526

Observation 9715ba09-e208-4913-9dee-dacd82f9feb7 · inbound

Demystifying CLIP Data cites this paper.

Demystifying CLIP Data Reproducible scaling laws for contrastive language-image learning

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-05-16T09:20:20.258305Z

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=arxiv_source observed=2026-05-16T09:20:20.143143Z digest=sha256:202a1ae2ad9bbebd60caf936f089b30c813be981c39167b51787d9deb6550bcd

Observation e028cb0c-5dc6-43e0-a6a0-b2a019949f23 · inbound

ViSTa Dataset: Do vision-language models understand sequential tasks? cites this paper.

ViSTa Dataset: Do vision-language models understand sequential tasks? Reproducible scaling laws for contrastive language-image learning

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-12T16:45:47.329565Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T16:45:47.329565Z digest=sha256:325a32823cb86a8a0c9639b0c471709227a39f0e6118f95a91e11ad1b67feda8

Observation a06b8540-cd2b-4cf5-ae83-42f9b05ebd21 · inbound

CLOVER: Cross-Layer Orthogonal Vectors Pruning and Fine-Tuning cites this paper.

CLOVER: Cross-Layer Orthogonal Vectors Pruning and Fine-Tuning Reproducible scaling laws for contrastive language-image learning

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-12T12:13:55.158701Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T12:13:55.158701Z digest=sha256:753e35764f2ec1db107a0996aebf6748873bf74958c07b3b5a940dac40b7dd66

Observation f8aaa533-26f6-4eab-9783-c38b1e9ed019 · inbound

How to Merge Your Multimodal Models Over Time? cites this paper.

How to Merge Your Multimodal Models Over Time? Reproducible scaling laws for contrastive language-image learning

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-11T19:24:42.955755Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T19:24:42.955755Z digest=sha256:a86aed9f6764f31083a765bc9407dc3dce003ae797df50a2e1101d19b881215a

Observation 15a4872c-1688-4572-a902-f6242f19c7c2 · inbound

MASR: Self-Reflective Reasoning through Multimodal Hierarchical Attention Focusing for Agent-based Video Understanding cites this paper.

MASR: Self-Reflective Reasoning through Multimodal Hierarchical Attention Focusing for Agent-based Video Understanding Reproducible scaling laws for contrastive language-image learning

Reference 72

Resolution
unresolved
no resolver link, observed 2026-08-16T10:50:21.488475Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:50:21.488475Z digest=sha256:7f33a40f681e47196ca655a7e8d7cd6034c53771391b7085ee5dbf75a62e33cf

Observation 4ef9cd22-a929-4e0d-a04a-a292dd647dde · inbound

diveXplore at the Video Browser Showdown 2024 cites this paper.

diveXplore at the Video Browser Showdown 2024 Reproducible scaling laws for contrastive language-image learning

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-15T16:46:25.165629Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:46:25.165629Z digest=sha256:b6b6ea1af988b0ae3cd662a373f85170dca396ab6d67360f64521eeab3a76877

Observation acab2e52-707d-4483-a256-c636ab96fd9b · inbound

Magic-MM-Embedding: Towards Visual-Token-Efficient Universal Multimodal Embedding with MLLMs cites this paper.

Magic-MM-Embedding: Towards Visual-Token-Efficient Universal Multimodal Embedding with MLLMs Reproducible scaling laws for contrastive language-image learning

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-03T04:20:51.146796Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T04:20:51.146796Z digest=sha256:0e847915ae901465520461b13d0bab9b08bfd61d280fdf3c95a7d4c30e512e24

Observation 04d7566f-7a83-4a45-bb6a-58d9e052c98d · inbound

Rethinking Model Selection in VLM Through the Lens of Gromov-Wasserstein Distance cites this paper.

Rethinking Model Selection in VLM Through the Lens of Gromov-Wasserstein Distance Reproducible scaling laws for contrastive language-image learning

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-11T16:56:07.383990Z

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=2026-05-09T14:27:54.092750Z digest=sha256:2f1893971fe0f3abc566a6d6cbfe0b44b7ab8376feadb63d4321813de562c89f

Observation ea629e6a-4d35-4f93-95f9-4b4a1c4a7486 · inbound

$A^2$: Smaller Self-Supervised ViTs Localize Better than Larger Ones cites this paper.

$A^2$: Smaller Self-Supervised ViTs Localize Better than Larger Ones Reproducible scaling laws for contrastive language-image learning

Reference 5

Resolution
metadata mismatch
arxiv_id, observed 2026-06-28T11:22:02.953031Z

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=2026-06-28T11:14:47.182429Z digest=sha256:8841667bc08c1d66f69ffdd459ddc7ce458dc2ad5aa4a15a03fa7c6800e9ce94

Observation a4046ef0-5b55-4d7e-bb6d-abf873858213 · inbound

Benchmark AUC Is Not Deployable Reliability: A Cross-Dataset Audit of Off-the-Shelf Features for Surveillance Video Anomaly Detection cites this paper.

Benchmark AUC Is Not Deployable Reliability: A Cross-Dataset Audit of Off-the-Shelf Features for Surveillance Video Anomaly Detection Reproducible scaling laws for contrastive language-image learning

Reference 12

Resolution
metadata mismatch
arxiv_id, observed 2026-06-30T07:34:21.586222Z

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=2026-06-30T07:29:32.843624Z digest=sha256:64018dedcee1db783f152fac392132d112c30c8fc9cf1113d7c0401016b62408

Observation 4c92cdeb-a40f-4bfe-84cb-56147902b07f · inbound

Efficient PEFT Methods with Adaptive Checkpointing for Vision Models and VLMs on Resource Constrained Consumer-GPUs cites this paper.

Efficient PEFT Methods with Adaptive Checkpointing for Vision Models and VLMs on Resource Constrained Consumer-GPUs Reproducible scaling laws for contrastive language-image learning

Reference 26

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T15:28:33.740990Z

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=2026-07-03T15:21:11.367562Z digest=sha256:55269e7a2da10210b82d0529028e13d6b887fa46851edd9674537858783475ff

Observation ee5a565a-6ed5-4274-8286-a1485c55bbb5 · inbound

SOS-LoRA: Static Orthogonal-Subspace Low-Rank Adaptation with Fixed Multi-Scale Scaling cites this paper.

SOS-LoRA: Static Orthogonal-Subspace Low-Rank Adaptation with Fixed Multi-Scale Scaling Reproducible scaling laws for contrastive language-image learning

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-02T09:51:03.329640Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T09:51:03.329640Z digest=sha256:6eff2fb22470a0a3f8b5bfd9dfc184e084956ae17092f09e3def7c354948a94a