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Paper Citation Record · LEDGER

ObsDriveBench: Benchmarking Multimodal Understanding under Adverse Weather with Observability Awareness

As of 12 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2607.23537.

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

pith.paper-citation-record.v1
2607.23537 v1

Coverage vector

measured 34 of 34 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-07-30T19:51:03.678678Z

measured 34 of 34 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 0 of 0 inbound itemization

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34 of 34 outbound references displayed

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Outbound references

Observation 826050b8-f231-44f1-84df-5c730aef8168 · outbound

This paper cites Qwen3-VL Technical Report.

ObsDriveBench: Benchmarking Multimodal Understanding under Adverse Weather with Observability Awareness Qwen3-VL Technical Report

Reference 1

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Observation d20067a0-6e99-439d-b890-6cb36e537607 · outbound

This paper cites Qwen2.5-VL Technical Report.

ObsDriveBench: Benchmarking Multimodal Understanding under Adverse Weather with Observability Awareness Qwen2.5-VL Technical Report

Reference 2

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Observation 14b162a3-efd6-4f7f-b0c2-22ca8c15f826 · outbound

This paper cites Reasondrive: Ef- ficient visual question answering for autonomous vehicles with reasoning-enhanced small vision-language models.

ObsDriveBench: Benchmarking Multimodal Understanding under Adverse Weather with Observability Awareness Reasondrive: Ef- ficient visual question answering for autonomous vehicles with reasoning-enhanced small vision-language models

Reference 3

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Observation 1104f001-42e8-4baa-8cdc-fab390a6e4f6 · outbound

This paper cites Probing the reliability of driving vlms: From inconsistent responses to grounded temporal reason- ing.arXiv preprint arXiv:2603.09512, 2026.

ObsDriveBench: Benchmarking Multimodal Understanding under Adverse Weather with Observability Awareness Probing the reliability of driving vlms: From inconsistent responses to grounded temporal reason- ing.arXiv preprint arXiv:2603.09512, 2026

Reference 4

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Observation 08f65b89-79f3-498f-a1a9-131b12075dc3 · outbound

This paper cites Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling.

ObsDriveBench: Benchmarking Multimodal Understanding under Adverse Weather with Observability Awareness Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling

Reference 5

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Observation 939df4d4-3ab6-4e49-92ad-882ca70daf48 · outbound

This paper cites Survey on lidar perception in adverse weather conditions.

ObsDriveBench: Benchmarking Multimodal Understanding under Adverse Weather with Observability Awareness Survey on lidar perception in adverse weather conditions

Reference 6

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Observation 13b4fbaf-9454-4e66-91ec-dc9f651d025f · outbound

This paper cites STSBench: A Spatio-temporal Scenario Benchmark for Multi-modal Large Language Models in Autonomous Driving.

ObsDriveBench: Benchmarking Multimodal Understanding under Adverse Weather with Observability Awareness STSBench: A Spatio-temporal Scenario Benchmark for Multi-modal Large Language Models in Autonomous Driving

Reference 7

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Observation 2aba17cf-01aa-49d9-8655-f6aa2c5882a8 · outbound

This paper cites Gemini 3.1 pro, 2026.

ObsDriveBench: Benchmarking Multimodal Understanding under Adverse Weather with Observability Awareness Gemini 3.1 pro, 2026

Reference 8

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Observation b4f9531a-997b-424d-94fa-b814535d2dfe · outbound

This paper cites 4D Millimeter-Wave Radar in Autonomous Driving: A Survey.

ObsDriveBench: Benchmarking Multimodal Understanding under Adverse Weather with Observability Awareness 4D Millimeter-Wave Radar in Autonomous Driving: A Survey

Reference 9

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Observation 512c026b-4035-45af-b642-a6af0a649979 · outbound

This paper cites Drivelmm-o1: A step-by-step reasoning dataset and large multimodal model for driving scenario understanding.

ObsDriveBench: Benchmarking Multimodal Understanding under Adverse Weather with Observability Awareness Drivelmm-o1: A step-by-step reasoning dataset and large multimodal model for driving scenario understanding

Reference 10

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Observation 499bfb5a-46c5-4781-bd0d-f79f0e6b7018 · outbound

This paper cites The RoboDrive Challenge: Drive Anytime Anywhere in Any Condition.

ObsDriveBench: Benchmarking Multimodal Understanding under Adverse Weather with Observability Awareness The RoboDrive Challenge: Drive Anytime Anywhere in Any Condition

Reference 11

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Observation e87870bc-79d1-4d41-96a0-e4a63916b880 · outbound

This paper cites SpaceDrive: Infusing Spatial Awareness into VLM-based Autonomous Driving.

ObsDriveBench: Benchmarking Multimodal Understanding under Adverse Weather with Observability Awareness SpaceDrive: Infusing Spatial Awareness into VLM-based Autonomous Driving

Reference 12

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Observation 44148cad-4379-4704-9057-c8863cec035e · outbound

This paper cites Recogdrive: A reinforced cogni- tive framework for end-to-end autonomous driving.

ObsDriveBench: Benchmarking Multimodal Understanding under Adverse Weather with Observability Awareness Recogdrive: A reinforced cogni- tive framework for end-to-end autonomous driving

Reference 13

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Observation bbc0254e-0821-4097-be96-9dd9485390f1 · outbound

This paper cites Robodrivevlm: A novel benchmark and baseline towards robust vision- language models for autonomous driving.arXiv preprint arXiv:2512.01300, 2025.

ObsDriveBench: Benchmarking Multimodal Understanding under Adverse Weather with Observability Awareness Robodrivevlm: A novel benchmark and baseline towards robust vision- language models for autonomous driving.arXiv preprint arXiv:2512.01300, 2025

Reference 14

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source=pdf_text observed=2026-07-30T19:51:03.600435Z digest=sha256:672cf008f5032fae28750b94fa8e3de6f7ec2d8c8addea7b77a4440539df30e6

Observation fd704290-f41d-44c6-ab48-6c6032986a8a · outbound

This paper cites Calibrating llm-based evaluator.

ObsDriveBench: Benchmarking Multimodal Understanding under Adverse Weather with Observability Awareness Calibrating llm-based evaluator

Reference 15

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source=pdf_text observed=2026-07-30T19:51:03.604016Z digest=sha256:bbb404c0597b32e9300956f22b9737075aab6df7a4bf215edfacc56505bbb654

Observation 02d84f35-cba6-4790-90c1-d02e80052143 · outbound

This paper cites Robust object detection in adverse weather conditions: Ecl-yolov11 for automotive vision systems.Sensors, 26(1): 304, 2026.

ObsDriveBench: Benchmarking Multimodal Understanding under Adverse Weather with Observability Awareness Robust object detection in adverse weather conditions: Ecl-yolov11 for automotive vision systems.Sensors, 26(1): 304, 2026

Reference 16

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source=pdf_text observed=2026-07-30T19:51:03.607800Z digest=sha256:2496e70a4d56131fe1abe6ebebb8bd204de11421595905d41d29068a534225b8

Observation a2b23662-8c62-4d01-82dc-a540cbe27bf4 · outbound

This paper cites Dolphins: Multimodal language model for driving.

ObsDriveBench: Benchmarking Multimodal Understanding under Adverse Weather with Observability Awareness Dolphins: Multimodal language model for driving

Reference 17

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source=pdf_text observed=2026-07-30T19:51:03.611583Z digest=sha256:5f4ab573fe8cf21f74870a8b8e358ce8678d660bec956da82f6105dd443350f5

Observation e2017248-f3cc-4a76-b7fb-962cc6f113ab · outbound

This paper cites K-radar: 4d radar object detection for autonomous driving in various weather conditions.Advances in Neural Information Processing Systems, 35:3819–3829, 2022.

ObsDriveBench: Benchmarking Multimodal Understanding under Adverse Weather with Observability Awareness K-radar: 4d radar object detection for autonomous driving in various weather conditions.Advances in Neural Information Processing Systems, 35:3819–3829, 2022

Reference 19

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Observation 7e47d244-8937-418e-b7f7-90b363ed6417 · outbound

This paper cites Nuscenes-qa: A multi-modal visual ques- tion answering benchmark for autonomous driving scenario.

ObsDriveBench: Benchmarking Multimodal Understanding under Adverse Weather with Observability Awareness Nuscenes-qa: A multi-modal visual ques- tion answering benchmark for autonomous driving scenario

Reference 20

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source=pdf_text observed=2026-07-30T19:51:03.623076Z digest=sha256:bdb0f37a07c11b2b1568725acfe65a920cd9bb5b0285583cf3d579a49117dd7c

Observation 93aee83d-c8c8-4529-9cce-f0ffda256abc · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

ObsDriveBench: Benchmarking Multimodal Understanding under Adverse Weather with Observability Awareness DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 21

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Observation 1fad00e4-eb09-40dd-8ab0-3b21733f726b · outbound

This paper cites Radiate: A radar dataset for automotive perception in bad weather.

ObsDriveBench: Benchmarking Multimodal Understanding under Adverse Weather with Observability Awareness Radiate: A radar dataset for automotive perception in bad weather

Reference 22

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Observation e64b4f31-d44e-491c-a5d5-20eeeedc674c · outbound

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

ObsDriveBench: Benchmarking Multimodal Understanding under Adverse Weather with Observability Awareness Drivelm: Driving with graph visual question answering

Reference 23

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Observation 3cadff73-7b11-4347-8f7a-384a97951d6f · outbound

This paper cites OpenAI GPT-5 System Card.

ObsDriveBench: Benchmarking Multimodal Understanding under Adverse Weather with Observability Awareness OpenAI GPT-5 System Card

Reference 24

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Observation 9a29c50e-77e9-4275-8a65-66c87e736e99 · outbound

This paper cites Minddrive: An all-in-one framework bridging world models and vision-language model for end-to-end au- tonomous driving.arXiv preprint arXiv:2512.04441, 2025.

ObsDriveBench: Benchmarking Multimodal Understanding under Adverse Weather with Observability Awareness Minddrive: An all-in-one framework bridging world models and vision-language model for end-to-end au- tonomous driving.arXiv preprint arXiv:2512.04441, 2025

Reference 25

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Observation 3afb1e62-aebb-44d5-8f09-75d9e8c7dd24 · outbound

This paper cites Nuscenes-spatialqa: A spatial understanding and reasoning benchmark for vision- language models in autonomous driving.

ObsDriveBench: Benchmarking Multimodal Understanding under Adverse Weather with Observability Awareness Nuscenes-spatialqa: A spatial understanding and reasoning benchmark for vision- language models in autonomous driving

Reference 26

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Observation 8567d2c9-dd6f-4d37-82ed-6d4024fc2bde · outbound

This paper cites Omnidrive: A holistic vision-language dataset for autonomous driving with counterfactual reasoning.

ObsDriveBench: Benchmarking Multimodal Understanding under Adverse Weather with Observability Awareness Omnidrive: A holistic vision-language dataset for autonomous driving with counterfactual reasoning

Reference 27

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Observation b4cd2061-ae75-4306-9188-39887a2a7c28 · outbound

This paper cites Alpamayo-R1: Bridging Reasoning and Action Prediction for Generalizable Autonomous Driving in the Long Tail.

ObsDriveBench: Benchmarking Multimodal Understanding under Adverse Weather with Observability Awareness Alpamayo-R1: Bridging Reasoning and Action Prediction for Generalizable Autonomous Driving in the Long Tail

Reference 28

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Observation 2fe3bba4-57a7-426c-bc17-feaafe6c4889 · outbound

This paper cites Perception-r1: Advancing mul- timodal reasoning capabilities of MLLMs via visual percep- tion reward.

ObsDriveBench: Benchmarking Multimodal Understanding under Adverse Weather with Observability Awareness Perception-r1: Advancing mul- timodal reasoning capabilities of MLLMs via visual percep- tion reward

Reference 29

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Observation f21b8a67-c66e-4e6c-80ce-852f5e5a1492 · outbound

This paper cites Are vlms ready for autonomous driving? an empirical study from the reliability, data and metric perspectives.

ObsDriveBench: Benchmarking Multimodal Understanding under Adverse Weather with Observability Awareness Are vlms ready for autonomous driving? an empirical study from the reliability, data and metric perspectives

Reference 30

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Observation ca8e7e79-7581-4369-a3eb-38e3f96d4a00 · outbound

This paper cites R1-vl: Learning to reason with multimodal large language models via step- wise group relative policy optimization, 2025.

ObsDriveBench: Benchmarking Multimodal Understanding under Adverse Weather with Observability Awareness R1-vl: Learning to reason with multimodal large language models via step- wise group relative policy optimization, 2025

Reference 31

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Observation eb5f3560-d9a6-4f24-8419-0a556077bb4a · outbound

This paper cites Perception and sensing for autonomous ve- hicles under adverse weather conditions: A survey.ISPRS Journal of Photogrammetry and Remote Sensing, 196:146– 177, 2023.

ObsDriveBench: Benchmarking Multimodal Understanding under Adverse Weather with Observability Awareness Perception and sensing for autonomous ve- hicles under adverse weather conditions: A survey.ISPRS Journal of Photogrammetry and Remote Sensing, 196:146– 177, 2023

Reference 32

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Observation 77a7e98e-5784-4616-913c-0a6729d7b04b · outbound

This paper cites OmniDrive-R1: Reinforcement-driven Interleaved Multi-modal Chain-of-Thought for Trustworthy Vision-Language Autonomous Driving.

ObsDriveBench: Benchmarking Multimodal Understanding under Adverse Weather with Observability Awareness OmniDrive-R1: Reinforcement-driven Interleaved Multi-modal Chain-of-Thought for Trustworthy Vision-Language Autonomous Driving

Reference 33

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Observation 720d6b8a-a8f6-4ce3-bffd-60a7ecf9ab78 · outbound

This paper cites Opendrivevla: Towards end- to-end autonomous driving with large vision language action model.arXiv preprint arXiv:2503.23463, 2025.

ObsDriveBench: Benchmarking Multimodal Understanding under Adverse Weather with Observability Awareness Opendrivevla: Towards end- to-end autonomous driving with large vision language action model.arXiv preprint arXiv:2503.23463, 2025

Reference 34

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Observation 62c24db3-3a29-4c69-9c97-7c0a884e2f27 · outbound

This paper cites InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models.

ObsDriveBench: Benchmarking Multimodal Understanding under Adverse Weather with Observability Awareness InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models

Reference 35

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