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Paper Citation Record · LEDGER

EVE: Efficient Vision-Language Pre-training with Masked Prediction and Modality-Aware MoE

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2308.11971.

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

pith.paper-citation-record.v1
2308.11971 v2

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 2026-08-16T06:30:59.297886+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T11:37:10.941520Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-16T02:33:30.247660Z

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 89890d4f-b2b9-4ccf-82e2-514047b5f6c1 · inbound

MoE-LLaVA: Mixture of Experts for Large Vision-Language Models cites this paper.

MoE-LLaVA: Mixture of Experts for Large Vision-Language Models EVE: Efficient Vision-Language Pre-training with Masked Prediction and Modality-Aware MoE

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-16T02:33:30.250611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-16T02:33:30.143907Z digest=sha256:0e15d5128b3034336e189e2603678b916e602ddf7aa1444ab4d9f7694fa5a592

Observation c6deebb6-705d-4903-bc10-e97a54c52f78 · inbound

LMFusion: Adapting Pretrained Language Models for Multimodal Generation cites this paper.

LMFusion: Adapting Pretrained Language Models for Multimodal Generation EVE: Efficient Vision-Language Pre-training with Masked Prediction and Modality-Aware MoE

Reference 2020

Resolution
unresolved
no resolver link, observed 2026-08-11T11:37:10.941520Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:37:10.941520Z digest=sha256:140db224670e4919d451914354d2c09c719afa3c6c44a6d9be84f2369392e0ed