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Paper Citation Record · LEDGER

Less is More: Removing Text-regions Improves CLIP Training Efficiency and Robustness

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2305.05095.

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

pith.paper-citation-record.v1
2305.05095 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T12:12:30.652561Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T22:36:50.760616Z

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 d87dc198-a1f3-4a3c-a618-787ce9507f85 · 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 Less is More: Removing Text-regions Improves CLIP Training Efficiency and Robustness

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-08T12:12:30.652561Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T12:12:30.652561Z digest=sha256:1a37675697a818b174f11dc85663b02fc77522c0b93cbe57c6009062fe04eed8

Observation 94387481-f722-4ff7-b6d5-4a4d5bacff81 · inbound

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation cites this paper.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Less is More: Removing Text-regions Improves CLIP Training Efficiency and Robustness

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-08-06T22:36:50.840513Z

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=2026-08-06T22:36:42.353046Z digest=sha256:ba11a641d11cdae2f01cd72c9d7243e0d492d8d0bfe4d4c5f99d0593ba7b8595