Paper Citation Record · LEDGER

Enhancing Vision Foundation Models via Multimodal Continual Pre-Training

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2503.18931.

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

pith.paper-citation-record.v1
2503.18931 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:25:24.829220Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T20:28:55.869127Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
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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 c46a81ec-02b1-4ec5-ab43-cb66102d8b74 · inbound

Grounding Intelligence in Movement cites this paper.

Grounding Intelligence in Movement Enhancing Vision Foundation Models via Multimodal Continual Pre-Training

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T20:25:24.829220Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a0ac5561-0de9-4a55-ac6a-1b6be85ae714 · inbound

jina-embeddings-v5-omni: Geometry-preserving Embeddings via Locked Aligned Towers cites this paper.

jina-embeddings-v5-omni: Geometry-preserving Embeddings via Locked Aligned Towers Enhancing Vision Foundation Models via Multimodal Continual Pre-Training

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-07-21T02:21:17.004501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 1fc270fa-540c-48c6-a29a-12d73b3027ef · inbound

jina-embeddings-v5-omni: Geometry-preserving Embeddings via Locked Aligned Towers cites this paper.

jina-embeddings-v5-omni: Geometry-preserving Embeddings via Locked Aligned Towers Enhancing Vision Foundation Models via Multimodal Continual Pre-Training

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-07-21T02:21:17.004501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 295ae530-6c9f-40d0-a41c-db0940039fb0 · inbound

jina-embeddings-v5-omni: Geometry-preserving Embeddings via Locked Aligned Towers cites this paper.

jina-embeddings-v5-omni: Geometry-preserving Embeddings via Locked Aligned Towers Enhancing Vision Foundation Models via Multimodal Continual Pre-Training

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-07-21T02:21:17.004501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 4d778a25-db20-48c7-afae-87c9e024a33f · inbound

IDEAL: In-DEpth ALignment Makes A Discrete Representation AutoEncoder cites this paper.

IDEAL: In-DEpth ALignment Makes A Discrete Representation AutoEncoder Enhancing Vision Foundation Models via Multimodal Continual Pre-Training

Reference 6

Resolution: metadata mismatch; arxiv_id, observed 2026-07-21T02:21:17.004501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 4a844d73-232e-462e-b260-d028b2f3a9fc · inbound

Unified Multimodal Autoregressive Modeling with Shared Context-Visual Tokenizer is Key to Unification cites this paper.

Unified Multimodal Autoregressive Modeling with Shared Context-Visual Tokenizer is Key to Unification Enhancing Vision Foundation Models via Multimodal Continual Pre-Training

Reference 6

Resolution: metadata mismatch; arxiv_id, observed 2026-07-21T02:21:17.004501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.