Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
When Do We Not Need Larger Vision Models?
As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2403.13043.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T15:17:22.756008Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-07-05T11:41:02.805036Z
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 cc85ff8f-9599-464e-8401-c799f953c6ac · inbound
Multimodal Autoregressive Pre-training of Large Vision Encoders cites this paper.
Multimodal Autoregressive Pre-training of Large Vision Encoders When Do We Not Need Larger Vision Models?
Reference 103
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T15:17:22.756008Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8bdecde8-5bd6-48cd-99c3-30c96ce04cf7 · inbound
RefHCM: A Unified Model for Referring Perceptions in Human-Centric Scenarios cites this paper.
RefHCM: A Unified Model for Referring Perceptions in Human-Centric Scenarios When Do We Not Need Larger Vision Models?
Reference 57
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T12:05:52.763273Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 46314a16-111e-4ea6-a0c2-69c8fa65bbba · inbound
FEA-SLT: A Gloss-Free End-to-End Framework for Facial-Expression-Aware Sign Language Translation cites this paper.
FEA-SLT: A Gloss-Free End-to-End Framework for Facial-Expression-Aware Sign Language Translation When Do We Not Need Larger Vision Models?
Reference 2024
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T12:19:05.755187Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 928a73ae-3339-4401-9510-5cdd5afe0bbf · inbound
ClawEnvKit: Automatic Environment Generation for Claw-Like Agents cites this paper.
ClawEnvKit: Automatic Environment Generation for Claw-Like Agents When Do We Not Need Larger Vision Models?
Reference 32
- Resolution
- verified exact
- local_arxiv, observed 2026-07-05T11:41:02.807457Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 72805b24-9ff7-427e-8f52-31466409cff8 · inbound
Advancing Vision Transformer with Enhanced Spatial Priors cites this paper.
Advancing Vision Transformer with Enhanced Spatial Priors When Do We Not Need Larger Vision Models?
Reference 32
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T09:23:37.635162Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 02daeadd-fcdd-49e8-98ef-14e32e2938c4 · 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 When Do We Not Need Larger Vision Models?
Reference 31
- Resolution
- malformed identifier
- arxiv_id, observed 2026-07-02T02:06:26.740154Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 144f1609-5b75-41cc-9cd7-a031ea417612 · inbound
HAFI-VLM: A Frequency Perspective for Diagnosing and Enhancing Visual Perception in Vision-Language Models cites this paper.
HAFI-VLM: A Frequency Perspective for Diagnosing and Enhancing Visual Perception in Vision-Language Models When Do We Not Need Larger Vision Models?
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T14:48:45.165044Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.