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Paper Citation Record · LEDGER

A Comparative Evaluation of Large Vision-Language Models for 2D Object Detection under SOTIF Conditions

As of 8 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2601.22830.

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

pith.paper-citation-record.v1
2601.22830 v2

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T06:24:27.477404Z

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

16 of 16 outbound references displayed

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  • verified fuzzy0
  • unresolved16
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 356bafe3-53a3-4550-9a7e-bd01fbe8184f · outbound

This paper cites A review of sensor technologies for perception in automated driving,.

A Comparative Evaluation of Large Vision-Language Models for 2D Object Detection under SOTIF Conditions A review of sensor technologies for perception in automated driving,

Reference 1

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T06:24:26.726674Z digest=sha256:a595ee79bdb333f750c170c989befe27f5fcd7c028f0c2e39d2a18f35fa0bce3

Observation 9f620751-3073-4210-9546-52d4620dabc7 · outbound

This paper cites ISO 21 448:2022, Jun.

A Comparative Evaluation of Large Vision-Language Models for 2D Object Detection under SOTIF Conditions ISO 21 448:2022, Jun

Reference 2

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source=pdf_text observed=2026-08-03T06:24:26.768278Z digest=sha256:e2c94e3abe004c0de04a2fac76f9bf8dec6cb2b12bc2f1146ad4b2004a8ad085

Observation a91e091f-6510-4aa0-ad22-23547fc229c3 · outbound

This paper cites PeSOTIF: A challenging visual dataset for perception SOTIF problems in long-tail traffic scenarios,.

A Comparative Evaluation of Large Vision-Language Models for 2D Object Detection under SOTIF Conditions PeSOTIF: A challenging visual dataset for perception SOTIF problems in long-tail traffic scenarios,

Reference 3

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no resolver link, observed 2026-08-03T06:24:26.817360Z

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source=pdf_text observed=2026-08-03T06:24:26.817360Z digest=sha256:270ddfe4233eb3663be09cfe78ed3fec4bbf5d38fbac07dc38d594936ad0a9c8

Observation db01f6fa-8a0e-43c1-8d71-8a8990e017e8 · outbound

This paper cites Are we ready for autonomous driving? the KITTI vision benchmark suite,.

A Comparative Evaluation of Large Vision-Language Models for 2D Object Detection under SOTIF Conditions Are we ready for autonomous driving? the KITTI vision benchmark suite,

Reference 4

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source=pdf_text observed=2026-08-03T06:24:26.862528Z digest=sha256:94a0b94851c7afa7b9c601ca3fe71829321eca4a8f8b50d4966a112f883c2527

Observation eaba0d5c-a992-497f-abfb-6434ba0637d7 · outbound

This paper cites nuScenes: A multi- modal dataset for autonomous driving,.

A Comparative Evaluation of Large Vision-Language Models for 2D Object Detection under SOTIF Conditions nuScenes: A multi- modal dataset for autonomous driving,

Reference 5

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source=pdf_text observed=2026-08-03T06:24:26.944411Z digest=sha256:bcaf6584440df5bb4c7b07122294a9820af3b340d41679571bc44a3b9e091ee7

Observation fee05175-e874-46aa-b81e-3d8e9485d9e9 · outbound

This paper cites Bdd100k: A diverse driving dataset for heterogeneous multitask learning,.

A Comparative Evaluation of Large Vision-Language Models for 2D Object Detection under SOTIF Conditions Bdd100k: A diverse driving dataset for heterogeneous multitask learning,

Reference 6

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source=pdf_text observed=2026-08-03T06:24:26.987686Z digest=sha256:5a2815d8955311c2b9294b2485156c62786ae6a43ec8854739864c3d5363df44

Observation 132b2dd2-3c1c-4c7d-9ec5-106f450d62a8 · outbound

This paper cites Uncertainty evaluation of object detection algorithms for autonomous vehicles,.

A Comparative Evaluation of Large Vision-Language Models for 2D Object Detection under SOTIF Conditions Uncertainty evaluation of object detection algorithms for autonomous vehicles,

Reference 7

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source=pdf_text observed=2026-08-03T06:24:27.039041Z digest=sha256:72f51d54d8ec1c80a476e831351218a3e2fdd08f3b88c032fb43984fad46434c

Observation 41d44069-5a4a-4f7b-a8a1-24e418a21247 · outbound

This paper cites Ensuring SOTIF: Enhanced object detection techniques for autonomous driving,.

A Comparative Evaluation of Large Vision-Language Models for 2D Object Detection under SOTIF Conditions Ensuring SOTIF: Enhanced object detection techniques for autonomous driving,

Reference 8

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source=pdf_text observed=2026-08-03T06:24:27.099041Z digest=sha256:9f6f16737ad86ba96c4ae9b50dd230a4ae090f17a8647606abdffb6080ab5c06

Observation 34f1f560-8bd4-4631-906a-fced57f6882b · outbound

This paper cites You only look once: Unified, real-time object detection,.

A Comparative Evaluation of Large Vision-Language Models for 2D Object Detection under SOTIF Conditions You only look once: Unified, real-time object detection,

Reference 9

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source=pdf_text observed=2026-08-03T06:24:27.141189Z digest=sha256:18127f4895376fda9a73eab07525c6a645de0430f82db742558efd3e9b6e30a8

Observation fe6d911d-e8a8-4fb8-b549-ae85de49c4a7 · outbound

This paper cites Semantic understanding of traffic scenes with large vision language models,.

A Comparative Evaluation of Large Vision-Language Models for 2D Object Detection under SOTIF Conditions Semantic understanding of traffic scenes with large vision language models,

Reference 10

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source=pdf_text observed=2026-08-03T06:24:27.174985Z digest=sha256:4df09891651fb6c199acc261b217868a3ca70df57cf887543278207a02941a01

Observation ff491f0e-f830-4a0c-a6ae-a982940bd795 · outbound

This paper cites DriveSOTIF: Advancing SOTIF through multimodal large language models,.

A Comparative Evaluation of Large Vision-Language Models for 2D Object Detection under SOTIF Conditions DriveSOTIF: Advancing SOTIF through multimodal large language models,

Reference 11

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source=pdf_text observed=2026-08-03T06:24:27.235777Z digest=sha256:f19d78bb114efa185e2965c270e2f12ecaf1ceeebfc0c690c09e028ad92c8f36

Observation b6c7092f-b097-45cf-9661-ea0f6af0c991 · outbound

This paper cites LLM-DiffAug: Enhancing few-shot object detection via LLM-guided diffusion augmentation,.

A Comparative Evaluation of Large Vision-Language Models for 2D Object Detection under SOTIF Conditions LLM-DiffAug: Enhancing few-shot object detection via LLM-guided diffusion augmentation,

Reference 12

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source=pdf_text observed=2026-08-03T06:24:27.269139Z digest=sha256:b35af7af07b1cc2bfdd58f2fcb37d723c3c774db41c82182295a260a4f20de5a

Observation 84fa26cd-ec98-4e62-9e33-ca426133761e · outbound

This paper cites Filters for common resampling tasks,.

A Comparative Evaluation of Large Vision-Language Models for 2D Object Detection under SOTIF Conditions Filters for common resampling tasks,

Reference 13

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source=pdf_text observed=2026-08-03T06:24:27.332494Z digest=sha256:d64b142befe95b0072d1ed74517571ba5b21a36a4e216b63b7b8054f50a31137

Observation f9dc3583-4315-435a-a8f9-e069be0fb362 · outbound

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

A Comparative Evaluation of Large Vision-Language Models for 2D Object Detection under SOTIF Conditions Chain-of-thought prompting elicits reasoning in large language models,

Reference 14

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source=pdf_text observed=2026-08-03T06:24:27.369427Z digest=sha256:6b6524e13987cf39c919bbd78aa87fca5ce9a986995d3a9f2d16939950b2448b

Observation f66a1820-df0a-41b9-b733-1594855db30f · outbound

This paper cites YOLO Evolution: A Comprehensive Benchmark and Architectural Review of YOLOv12, YOLO11, and Their Previous Versions.

A Comparative Evaluation of Large Vision-Language Models for 2D Object Detection under SOTIF Conditions YOLO Evolution: A Comprehensive Benchmark and Architectural Review of YOLOv12, YOLO11, and Their Previous Versions

Reference 15

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source=pdf_text observed=2026-08-03T06:24:27.422784Z digest=sha256:a119330b26a9fc06a8f12ca7cc948fab1ca85e5513c836072a8c0dcca33f7cee

Observation 80a1c32b-1ed3-4ac7-aa27-0492b5cc5677 · outbound

This paper cites Microsoft COCO: Common objects in context,.

A Comparative Evaluation of Large Vision-Language Models for 2D Object Detection under SOTIF Conditions Microsoft COCO: Common objects in context,

Reference 16

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source=pdf_text observed=2026-08-03T06:24:27.477404Z digest=sha256:52775a5031c160a2a7a6fa635dea4b8c10c4d45060543c93d581a8ac269c0253

Pith citing papers

No inbound Pith citation observations are available.