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Paper Citation Record · LEDGER

MiniDrive: More Efficient Vision-Language Models with Multi-Level 2D Features as Text Tokens for Autonomous Driving

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2409.07267.

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

pith.paper-citation-record.v1
2409.07267 v5

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 2026-08-09T06:31:02.800959+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:17:59.143731Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-17T20:42:05.682556Z

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 5d47526d-1234-42ab-842b-a39c6969ca53 · inbound

TinyDrive: Multiscale Visual Question Answering with Selective Token Routing for Autonomous Driving cites this paper.

TinyDrive: Multiscale Visual Question Answering with Selective Token Routing for Autonomous Driving MiniDrive: More Efficient Vision-Language Models with Multi-Level 2D Features as Text Tokens for Autonomous Driving

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-07T15:17:59.143731Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:17:59.143731Z digest=sha256:a86de36018694882d708f8aeab380a2619e5ad972aac1cbe2ec2e2e04025c3c9

Observation 21da5a5b-d79b-4a30-a9b1-29b1c68fd39b · inbound

A Survey on Vision-Language-Action Models for Autonomous Driving cites this paper.

A Survey on Vision-Language-Action Models for Autonomous Driving MiniDrive: More Efficient Vision-Language Models with Multi-Level 2D Features as Text Tokens for Autonomous Driving

Reference 152

Resolution
unresolved
no resolver link, observed 2026-08-06T21:31:04.863773Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:31:04.863773Z digest=sha256:5b21bb8bcb8a335221deb624d03e33d124be42036553d6994eec436de85c3ba2

Observation 5f813ce0-2054-427d-b11b-70dab2f5dd13 · inbound

MoSE: Skill-by-Skill Mixture-of-Experts Learning for Embodied Autonomous Machines cites this paper.

MoSE: Skill-by-Skill Mixture-of-Experts Learning for Embodied Autonomous Machines MiniDrive: More Efficient Vision-Language Models with Multi-Level 2D Features as Text Tokens for Autonomous Driving

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-06T18:37:46.269978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:37:46.269978Z digest=sha256:7de0da89e0c66ec21fa72796ed9d4d6220ddfe503ba87b6574158e9c48654ef6

Observation cf71a6ea-1a41-4e55-8312-241a3c0dbcf3 · inbound

MiMo-Embodied: X-Embodied Foundation Model Technical Report cites this paper.

MiMo-Embodied: X-Embodied Foundation Model Technical Report MiniDrive: More Efficient Vision-Language Models with Multi-Level 2D Features as Text Tokens for Autonomous Driving

Reference 66

Resolution
verified exact
arxiv_id, observed 2026-05-17T20:42:05.684622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-17T20:40:54.096289Z digest=sha256:b56dd51e5fb5f9f2e6885ef89b708426f87b04c580c3907a7c97e8d1e5a20ccd

Observation f4d06326-d0be-4bcb-808c-0d733ac72020 · inbound

Spatial-aware Vision Language Model for Autonomous Driving cites this paper.

Spatial-aware Vision Language Model for Autonomous Driving MiniDrive: More Efficient Vision-Language Models with Multi-Level 2D Features as Text Tokens for Autonomous Driving

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-03T13:26:09.388873Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T13:26:09.388873Z digest=sha256:73eac331ca3917fa59d75f24849d25c33a6eb2d6f5236d8f0435255ddf8d5349