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Paper Citation Record · LEDGER

TinyDrive: Multiscale Visual Question Answering with Selective Token Routing for Autonomous Driving

As of 9 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 0 inbound Pith citation observations for arXiv:2505.15564.

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

pith.paper-citation-record.v1
2505.15564 v1

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:17:59.256014Z

measured 25 of 25 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

25 of 25 outbound references displayed

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  • verified fuzzy5
  • unresolved20
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  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7e64a61a-71e6-4e4c-be3f-662eaad4cd16 · outbound

This paper cites Meteor: An automatic metric for mt evaluation with improved correlation with human judgments.

TinyDrive: Multiscale Visual Question Answering with Selective Token Routing for Autonomous Driving Meteor: An automatic metric for mt evaluation with improved correlation with human judgments

Reference 1

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source=pdf_text observed=2026-08-07T15:17:56.835309Z digest=sha256:1bfd1f1290023882be3fecfa12fdad2b5f7f20b802c3fbdd541b66d26f9e3cff

Observation 9fcf04d0-5c10-4474-ad28-1cc727abe1e1 · outbound

This paper cites Driving with llms: Fusing object-level vector modality for explainable autonomous driving.

TinyDrive: Multiscale Visual Question Answering with Selective Token Routing for Autonomous Driving Driving with llms: Fusing object-level vector modality for explainable autonomous driving

Reference 2

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source=pdf_text observed=2026-08-07T15:17:56.901743Z digest=sha256:0eb9c18172a450f6dcf55b54c061d90fce5a35667253cbbff40e598a9f55f454

Observation 81a3509f-7c9f-4fdd-aaf2-f1548c93f254 · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding.

TinyDrive: Multiscale Visual Question Answering with Selective Token Routing for Autonomous Driving Bert: Pre-training of deep bidirectional transformers for language understanding

Reference 3

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source=pdf_text observed=2026-08-07T15:17:57.011789Z digest=sha256:c70225b71a2d9de2c9a75017861e73cfb6f4f317af427b83251ef9f97c077d84

Observation 4d7fa30c-2bd9-4463-bbe5-4840fa556a73 · outbound

This paper cites Unireplknet: A universal perception large-kernel convnet for audio video point cloud time-series and image recognition.

TinyDrive: Multiscale Visual Question Answering with Selective Token Routing for Autonomous Driving Unireplknet: A universal perception large-kernel convnet for audio video point cloud time-series and image recognition

Reference 4

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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=2026-08-07T15:17:57.103782Z digest=sha256:fe3dfa5972cec70f8fbefd07e4f9ef947c077fd15e13157d937838a726a86641

Observation ab96dcd8-ffb9-4d12-b42c-18ca802dfe8b · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

TinyDrive: Multiscale Visual Question Answering with Selective Token Routing for Autonomous Driving An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 5

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source=pdf_text observed=2026-08-07T15:17:57.217357Z digest=sha256:5986b2749b629f6855e6839acafdeaa166126209c8573fef5da3156245dd925c

Observation b2f4eb50-3c55-4160-9cd0-11feb99c8957 · outbound

This paper cites Multi-Frame, Lightweight & Efficient Vision-Language Models for Question Answering in Autonomous Driving.

TinyDrive: Multiscale Visual Question Answering with Selective Token Routing for Autonomous Driving Multi-Frame, Lightweight & Efficient Vision-Language Models for Question Answering in Autonomous Driving

Reference 6

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source=pdf_text observed=2026-08-07T15:17:57.316187Z digest=sha256:9dd5f90b37c41465867c9d0e3d09f23104e8a729576acfde04b26e83c6e88298

Observation cc0523e0-2561-4f4f-b7aa-3b56e31c720e · outbound

This paper cites World models for autonomous driving: An initial survey.IEEE Transac- tions on Intelligent Vehicles, 2024.

TinyDrive: Multiscale Visual Question Answering with Selective Token Routing for Autonomous Driving World models for autonomous driving: An initial survey.IEEE Transac- tions on Intelligent Vehicles, 2024

Reference 7

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

source=pdf_text observed=2026-08-07T15:17:57.433962Z digest=sha256:33f649608d5314bf0728376d65efa6dddbce0f9044080adb06112d2df30f84cb

Observation b2b65d36-4d46-468f-86a0-ccaf1d90e4bd · outbound

This paper cites Traffic navigation via reinforcement learning with episodic-guided prioritized experience replay.Engineering Applications of Artificial Intelligence, 137:109147, 2024.

TinyDrive: Multiscale Visual Question Answering with Selective Token Routing for Autonomous Driving Traffic navigation via reinforcement learning with episodic-guided prioritized experience replay.Engineering Applications of Artificial Intelligence, 137:109147, 2024

Reference 8

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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=2026-08-07T15:17:57.551778Z digest=sha256:75717348d28b6058df32828e53467594c17de05cdb1f2c965d856b72ced468d1

Observation b04098d7-837d-45e3-a4fc-b6e2d66c5290 · outbound

This paper cites Lora: Low-rank adaptation of large language models.ICLR, 1(2):3, 2022.

TinyDrive: Multiscale Visual Question Answering with Selective Token Routing for Autonomous Driving Lora: Low-rank adaptation of large language models.ICLR, 1(2):3, 2022

Reference 9

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source=pdf_text observed=2026-08-07T15:17:57.647411Z digest=sha256:af2ffa7b9ce306dff546bec129d2003e462b35c3a09b97cb1952154fe3ef54c7

Observation adfe776a-2b93-459c-bea3-9178be04ecea · outbound

This paper cites Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models.

TinyDrive: Multiscale Visual Question Answering with Selective Token Routing for Autonomous Driving Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models

Reference 10

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source=pdf_text observed=2026-08-07T15:17:57.745932Z digest=sha256:90b7e2556e595037c6835a8731bc8ba648beec17bfafa08d357fe69831e1b1d7

Observation d2070f02-8942-400b-9e08-059f04560599 · outbound

This paper cites Rouge: A package for automatic evaluation of summaries.

TinyDrive: Multiscale Visual Question Answering with Selective Token Routing for Autonomous Driving Rouge: A package for automatic evaluation of summaries

Reference 11

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source=pdf_text observed=2026-08-07T15:17:57.847632Z digest=sha256:4bf256902604c79934ddc4def87ef40ce7d130d432dbdaaa05b223f3e6b7157f

Observation 0a2f6351-13b5-45ad-b891-946d01fd4e1a · outbound

This paper cites GPT-Driver: Learning to Drive with GPT.

TinyDrive: Multiscale Visual Question Answering with Selective Token Routing for Autonomous Driving GPT-Driver: Learning to Drive with GPT

Reference 12

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source=pdf_text observed=2026-08-07T15:17:57.963862Z digest=sha256:edc193ed23e6e30f50434457c6ce09df36f500b85eccc2bf8989d8f5b0e63ff9

Observation ec07915b-3b97-4055-9e13-3edc38e08fb6 · outbound

This paper cites Bleu: a method for automatic evaluation of machine translation.

TinyDrive: Multiscale Visual Question Answering with Selective Token Routing for Autonomous Driving Bleu: a method for automatic evaluation of machine translation

Reference 13

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source=pdf_text observed=2026-08-07T15:17:58.079631Z digest=sha256:3e7aa9021fc3e6cc69bc0a35efadbf3785feaf02399ff83b39615119d1406e81

Observation e5cecba8-b8b8-4b7f-ab72-1511ade3589c · outbound

This paper cites Learning transferable visual models from natural language supervision.

TinyDrive: Multiscale Visual Question Answering with Selective Token Routing for Autonomous Driving Learning transferable visual models from natural language supervision

Reference 14

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source=pdf_text observed=2026-08-07T15:17:58.166227Z digest=sha256:3253ae9ebecb85bd8ccb94ba10a9bc9cab00cc5efcd1ce10d82384f614befe0d

Observation 854273ff-82f1-4696-8c80-7089090e3d75 · outbound

This paper cites Exploring the limits of transfer learning with a unified text-to-text transformer.Journal of machine learning research, 21(140):1–67, 2020.

TinyDrive: Multiscale Visual Question Answering with Selective Token Routing for Autonomous Driving Exploring the limits of transfer learning with a unified text-to-text transformer.Journal of machine learning research, 21(140):1–67, 2020

Reference 15

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source=pdf_text observed=2026-08-07T15:17:58.253854Z digest=sha256:83718bae3d50fae062ceb97d568b962b6f85150ad8c628024aee955e42ad687f

Observation 4cf5fb0e-f5f1-4926-b229-8a9391362416 · outbound

This paper cites LanguageMPC: Large Language Models as Decision Makers for Autonomous Driving.

TinyDrive: Multiscale Visual Question Answering with Selective Token Routing for Autonomous Driving LanguageMPC: Large Language Models as Decision Makers for Autonomous Driving

Reference 16

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source=pdf_text observed=2026-08-07T15:17:58.371824Z digest=sha256:2f0c817571584a365f56f544c440a9b16695697456c2563fbb8a72581ee42bc5

Observation 8e0f5c14-2aa7-4af8-94d3-8c6fac8f143c · outbound

This paper cites Drivelm: Driving with graph visual question answering.

TinyDrive: Multiscale Visual Question Answering with Selective Token Routing for Autonomous Driving Drivelm: Driving with graph visual question answering

Reference 17

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source=pdf_text observed=2026-08-07T15:17:58.471551Z digest=sha256:571224fbf8452e2b4534675d0642023167e149ede8295faae8ad7df88424255c

Observation 818514c7-db8a-4eb1-8b44-4a4c8fece003 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

TinyDrive: Multiscale Visual Question Answering with Selective Token Routing for Autonomous Driving LLaMA: Open and Efficient Foundation Language Models

Reference 18

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source=pdf_text observed=2026-08-07T15:17:58.583992Z digest=sha256:86ad8023fbb4271ee85f862196e1ab3a71523a80f7a3bc440867b74cfbdf6794

Observation a3677b2e-4668-492c-89d9-238c65436696 · outbound

This paper cites Labelimg.https://github.com/tzutalin/labelImg, 2015.

TinyDrive: Multiscale Visual Question Answering with Selective Token Routing for Autonomous Driving Labelimg.https://github.com/tzutalin/labelImg, 2015

Reference 19

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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=2026-08-07T15:17:58.674118Z digest=sha256:f5b557b71a056ddb9d900d5ec5be7a49da36544a8e70a82ea6bef5d7407b0e3b

Observation a7584999-7d05-4416-959c-c21d1714d41a · outbound

This paper cites Cider: Consensus-based image description evaluation.

TinyDrive: Multiscale Visual Question Answering with Selective Token Routing for Autonomous Driving Cider: Consensus-based image description evaluation

Reference 20

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source=pdf_text observed=2026-08-07T15:17:58.773109Z digest=sha256:19269b5d45639f5fb8a00571f2b0c9d3a280ee7f906ae43efa7d7d0cbfe62996

Observation 321dd4d7-77df-4d14-b9b0-03308254573f · outbound

This paper cites Drivemlm: Aligning multi-modal large language models with behavioral planning states for autonomous driving.arXiv preprint arXiv:2312.09245, 2023.

TinyDrive: Multiscale Visual Question Answering with Selective Token Routing for Autonomous Driving Drivemlm: Aligning multi-modal large language models with behavioral planning states for autonomous driving.arXiv preprint arXiv:2312.09245, 2023

Reference 21

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source=pdf_text observed=2026-08-07T15:17:58.860998Z digest=sha256:df0e08de8938df3d8d52117f91c0e7e883f15f3fa66ddc76d86638b37a506dd8

Observation 158be957-8fc6-47e6-b41e-b78894c8eee9 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models.

TinyDrive: Multiscale Visual Question Answering with Selective Token Routing for Autonomous Driving Chain-of-thought prompting elicits reasoning in large language models

Reference 22

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source=pdf_text observed=2026-08-07T15:17:58.960626Z digest=sha256:350b677a74e9ec10a94f1466ed5fe77d5c0287c04b67f2d0a3b46785283e8334

Observation 3b28f699-4774-45af-84c4-92122cd40474 · outbound

This paper cites Drivegpt4: Interpretable end-to-end autonomous driving via large language model.IEEE Robotics and Automation Letters, 2024.

TinyDrive: Multiscale Visual Question Answering with Selective Token Routing for Autonomous Driving Drivegpt4: Interpretable end-to-end autonomous driving via large language model.IEEE Robotics and Automation Letters, 2024

Reference 23

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source=pdf_text observed=2026-08-07T15:17:59.055207Z digest=sha256:57f1b244aac0f476602f4c4c83bd0f946ac71a132674675054e41c34645e7fa3

Observation 5d47526d-1234-42ab-842b-a39c6969ca53 · outbound

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

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

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

Observation 55bd7cbd-df46-461e-9fdd-0238a9df4391 · outbound

This paper cites Vision language models in autonomous driving: A survey and outlook.IEEE Transactions on Intelligent Vehicles, 2024.

TinyDrive: Multiscale Visual Question Answering with Selective Token Routing for Autonomous Driving Vision language models in autonomous driving: A survey and outlook.IEEE Transactions on Intelligent Vehicles, 2024

Reference 25

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raw_fallback, observed 2026-08-07T15:17:59.667823Z

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=2026-08-07T15:17:59.256014Z digest=sha256:bff12ae6a6c384175c58a71cd083e737b3345f0ed20b70f8969e802fb2d7b0cb

Pith citing papers

No inbound Pith citation observations are available.