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Paper Citation Record · LEDGER

Does CLIP's Generalization Performance Mainly Stem from High Train-Test Similarity?

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2310.09562.

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

pith.paper-citation-record.v1
2310.09562 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 2026-08-08T06:32:00.761636+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:50:58.869165Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T02:52:27.053293Z

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 eb592648-1229-459d-983a-d2cd8215eae8 · inbound

LLMs on the Line: Data Determines Loss-to-Loss Scaling Laws cites this paper.

LLMs on the Line: Data Determines Loss-to-Loss Scaling Laws Does CLIP's Generalization Performance Mainly Stem from High Train-Test Similarity?

Reference 30

Resolution
verified exact
arxiv_id, observed 2026-05-23T02:52:27.055543Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-23T02:47:37.492619Z digest=sha256:da0d49effed0a029569a4fa476a424df1c7d05e021d4425bd3ca9fb53648e79a

Observation 6ab94d23-151a-49a9-b34e-470c668a9f38 · inbound

FOCoOp: Enhancing Out-of-Distribution Robustness in Federated Prompt Learning for Vision-Language Models cites this paper.

FOCoOp: Enhancing Out-of-Distribution Robustness in Federated Prompt Learning for Vision-Language Models Does CLIP's Generalization Performance Mainly Stem from High Train-Test Similarity?

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-06T23:50:58.869165Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:50:58.869165Z digest=sha256:17e23ceff59f5a7c6f032a234acab6e74461a952431ee596939f756c843b334d

Observation ff125acc-ffd6-40b4-a56c-72fbd9374c3d · inbound

LAION-C: An Out-of-Distribution Benchmark for Web-Scale Vision Models cites this paper.

LAION-C: An Out-of-Distribution Benchmark for Web-Scale Vision Models Does CLIP's Generalization Performance Mainly Stem from High Train-Test Similarity?

Reference 6

Resolution
metadata mismatch
arxiv_id, observed 2026-05-22T00:54:31.280540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-22T00:53:19.382994Z digest=sha256:130502696b54bc44b7ce716cce68347a55d4ec91b682e0c78c0ff60392ee6eb8

Observation 5ce51729-76a7-4d30-b965-2801f923c945 · inbound

Less Precise Can Be More Reliable: A Systematic Evaluation of Quantization's Impact on VLMs Beyond Accuracy cites this paper.

Less Precise Can Be More Reliable: A Systematic Evaluation of Quantization's Impact on VLMs Beyond Accuracy Does CLIP's Generalization Performance Mainly Stem from High Train-Test Similarity?

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-05-18T13:56:26.526689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-18T13:54:09.545262Z digest=sha256:9e2d361cbca11f4f8b66aa3e8f7c6119b19cd2f69aea15a27c9e47e138de426f

Observation 6fb379a8-8f3c-4d81-b58c-83194832dada · inbound

Less Precise Can Be More Reliable: A Systematic Evaluation of Quantization's Impact on VLMs Beyond Accuracy cites this paper.

Less Precise Can Be More Reliable: A Systematic Evaluation of Quantization's Impact on VLMs Beyond Accuracy Does CLIP's Generalization Performance Mainly Stem from High Train-Test Similarity?

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-05-21T22:30:44.092541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-21T22:26:05.211335Z digest=sha256:6b32795ff3fac21f85e38b6edb0e25730cde05b16e6579c6d456fbbe0c0811c6