Paper Citation Record · LEDGER

CLIPA-v2: Scaling CLIP Training with 81.1% Zero-shot ImageNet Accuracy within a \$10,000 Budget; An Extra \$4,000 Unlocks 81.8% Accuracy

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2306.15658.

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

pith.paper-citation-record.v1
2306.15658 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T00:12:36.344203Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-16T13:05:36.534537Z

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 2558bb42-b67c-4550-beec-8ac2d5276b32 · inbound

Sigmoid Loss for Language Image Pre-Training cites this paper.

Sigmoid Loss for Language Image Pre-Training CLIPA-v2: Scaling CLIP Training with 81.1% Zero-shot ImageNet Accuracy within a \$10,000 Budget; An Extra \$4,000 Unlocks 81.8% Accuracy

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-16T13:05:36.537477Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation bceb4b44-50cd-47c2-87ae-3bcb5c4667a1 · inbound

LR0.FM: Low-Res Benchmark and Improving Robustness for Zero-Shot Classification in Foundation Models cites this paper.

LR0.FM: Low-Res Benchmark and Improving Robustness for Zero-Shot Classification in Foundation Models CLIPA-v2: Scaling CLIP Training with 81.1% Zero-shot ImageNet Accuracy within a \$10,000 Budget; An Extra \$4,000 Unlocks 81.8% Accuracy

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-09T00:12:36.344203Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0c90f524-d196-4e7b-88af-85c2b502fdaf · inbound

SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features cites this paper.

SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features CLIPA-v2: Scaling CLIP Training with 81.1% Zero-shot ImageNet Accuracy within a \$10,000 Budget; An Extra \$4,000 Unlocks 81.8% Accuracy

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-05-10T15:49:22.350187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6844705f-e478-4b50-ae68-7e9b99814dcb · inbound

Perception Encoder: The best visual embeddings are not at the output of the network cites this paper.

Perception Encoder: The best visual embeddings are not at the output of the network CLIPA-v2: Scaling CLIP Training with 81.1% Zero-shot ImageNet Accuracy within a \$10,000 Budget; An Extra \$4,000 Unlocks 81.8% Accuracy

Reference 71

Resolution: verified exact; arxiv_id, observed 2026-05-13T22:21:15.762983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.