Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-06-30T16:40:22.441025Z
Paper Citation Record · LEDGER
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving
As of 19 August 2026, this Paper Citation Record lists 100 of 111 outbound references and 0 inbound Pith citation observations for arXiv:2605.23176.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
100 of 111 outbound references displayed
- verified exact47
- verified fuzzy53
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 4124a936-85e4-479c-b649-9b33c7e313a0 · outbound
This paper cites Studies in spatial learning.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Studies in spatial learning
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.742607Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 4908d26a-f4f6-452a-88d4-23c0b5221b75 · outbound
This paper cites Cognitive maps in rats and men.Psychological review, 55(4):189.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Cognitive maps in rats and men.Psychological review, 55(4):189
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.796120Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 46ad2d0d-0406-4c71-b866-80c32161dc59 · outbound
This paper cites The hippocampus and context revisited.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving The hippocampus and context revisited
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.747734Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation fdcd4ef5-bed5-4f43-bab2-81c653fdd9e4 · outbound
This paper cites The effect of vehicle navigation systems on the formation of cognitive maps.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving The effect of vehicle navigation systems on the formation of cognitive maps
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.755008Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation db2ce18a-30d3-4a8d-a831-f291b7ef0e26 · outbound
This paper cites Omnidrive: A holistic vision-language dataset for autonomous driving with counterfactual reasoning.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Omnidrive: A holistic vision-language dataset for autonomous driving with counterfactual reasoning
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.793920Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 2e812598-d752-44f9-bf5f-43d0e654119c · outbound
This paper cites Is ego status all you need for open-loop end-to-end autonomous driving? InProceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 14864–14873.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Is ego status all you need for open-loop end-to-end autonomous driving? InProceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 14864–14873
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.773907Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 018ae19c-0741-41cc-a8af-aa4579592b00 · outbound
This paper cites Holistic autonomous driving understanding by bird’s-eye-view injected multi-modal large models.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Holistic autonomous driving understanding by bird’s-eye-view injected multi-modal large models
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.802326Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 7e1c8a1d-1d24-46fc-ba36-c8f34e5f375b · outbound
This paper cites Are vlms ready for autonomous driving? an empirical study from the reliability, data and metric perspectives.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Are vlms ready for autonomous driving? an empirical study from the reliability, data and metric perspectives
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.769424Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 5f0159d9-0918-494f-a48c-fed2b967c682 · outbound
This paper cites Vlm-ad: End-to-end autonomous driving through vision-language model supervision.Conference on Robot Learning (CoRL).
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Vlm-ad: End-to-end autonomous driving through vision-language model supervision.Conference on Robot Learning (CoRL)
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.708689Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 7d9f6ce7-ba05-4d31-a037-fa46e9da8f87 · outbound
This paper cites Robotron-drive: All-in-one large multimodal model for autonomous driving.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Robotron-drive: All-in-one large multimodal model for autonomous driving
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.720240Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 8057aeb5-bcdc-4243-9d22-c010fc6826e3 · outbound
This paper cites Fastdrivevla: Efficient end-to-end driving via plug-and-play reconstruction- based token pruning.the Association for the Advancement of Artificial Intelligence (AAAI).
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Fastdrivevla: Efficient end-to-end driving via plug-and-play reconstruction- based token pruning.the Association for the Advancement of Artificial Intelligence (AAAI)
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.782249Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 8ff366c2-099d-45d1-af50-29ca9c812ee1 · outbound
This paper cites Drivegpt4: Interpretable end-to-end autonomous driving via large language model.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Drivegpt4: Interpretable end-to-end autonomous driving via large language model
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.710479Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation ee46642e-49ac-4018-a940-0eefe3c6dff2 · outbound
This paper cites Covla: Comprehensive vision-language-action dataset for autonomous driving.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Covla: Comprehensive vision-language-action dataset for autonomous driving
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.706881Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 95333992-8ce8-431a-98af-e4f85118f85e · outbound
This paper cites Emma: End-to-end multimodal model for autonomous driving.TMLR.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Emma: End-to-end multimodal model for autonomous driving.TMLR
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.759266Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 7f698644-b9af-4646-aa19-6420fa57ad1d · outbound
This paper cites Drivelm: Driving with graph visual question answering.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Drivelm: Driving with graph visual question answering
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.784193Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation c46774f7-2fba-4f9a-bfec-b3732d1293be · outbound
This paper cites DriveVLM: The convergence of autonomous driving and large vision-language models.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving DriveVLM: The convergence of autonomous driving and large vision-language models
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.790101Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation c98558d8-d110-42c0-bf32-aebc48894778 · outbound
This paper cites Futuresightdrive: Thinking visually with spatio-temporal cot for autonomous driving.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Futuresightdrive: Thinking visually with spatio-temporal cot for autonomous driving
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.788154Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 656104bb-f775-47b5-86da-31557de501c6 · outbound
This paper cites NuScenes-SpatialQA: A Spatial Understanding and Reasoning Benchmark for Vision-Language Models in Autonomous Driving.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving NuScenes-SpatialQA: A Spatial Understanding and Reasoning Benchmark for Vision-Language Models in Autonomous Driving
Reference 18
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T16:44:56.038675Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 0f352cc1-80c3-42c5-9de3-9c991e2e7446 · outbound
This paper cites Maplm: A real-world large-scale vision-language benchmark for map and traffic scene understanding.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Maplm: A real-world large-scale vision-language benchmark for map and traffic scene understanding
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.765343Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 0083e1b5-e35f-4800-8570-49436f921f03 · outbound
This paper cites Spatial reasoning with vision-language models in ego-centric multi-view scenes.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Spatial reasoning with vision-language models in ego-centric multi-view scenes
Reference 20
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T16:44:56.035595Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 9431909e-311e-4b96-983b-43e5332e90e8 · outbound
This paper cites Surds: Benchmarking spatial understanding and reasoning in driving scenarios with vision language models.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Surds: Benchmarking spatial understanding and reasoning in driving scenarios with vision language models
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.722106Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 4d30be20-c9bc-4ae0-9817-4dc6fbea3db5 · outbound
This paper cites Automated evaluation of large vision-language models on self-driving corner cases.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Automated evaluation of large vision-language models on self-driving corner cases
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.753145Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 1a14d964-bc55-4fe0-8344-ab1fc1d163a0 · outbound
This paper cites Lingoqa: Visual question answering for autonomous driving.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Lingoqa: Visual question answering for autonomous driving
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.699401Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation fd719db5-702f-4167-a61d-1fba9ea4d46d · outbound
This paper cites Towards physics- informed spatial intelligence with human priors: An autonomous driving pilot study.International Conference on Learning Representations (ICLR).
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Towards physics- informed spatial intelligence with human priors: An autonomous driving pilot study.International Conference on Learning Representations (ICLR)
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.771422Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation a979584e-9127-45f6-a598-6709d97ce2f0 · outbound
This paper cites Stsbench: A spatio-temporal scenario benchmark for multi-modal large language models in autonomous driving.Conference and Workshop on Neural Information Processing Systems.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Stsbench: A spatio-temporal scenario benchmark for multi-modal large language models in autonomous driving.Conference and Workshop on Neural Information Processing Systems
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.718326Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 0bd6d633-47d7-4f8a-912f-e55b4bacd336 · outbound
This paper cites Nuscenes-qa: A multi-modal visual question answering benchmark for autonomous driving scenario.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Nuscenes-qa: A multi-modal visual question answering benchmark for autonomous driving scenario
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.729645Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 0f86d378-36a6-4ec2-a281-8b4ddeaa8f8f · outbound
This paper cites nuscenes: A multimodal dataset for autonomous driving.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving nuscenes: A multimodal dataset for autonomous driving
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.740741Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation dc1a85fc-bb8d-4ac2-b412-d6dc854221aa · outbound
This paper cites Argoverse 2: Next generation datasets for self-driving perception and forecasting.Conference on Neural Information Processing Systems, 202.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Argoverse 2: Next generation datasets for self-driving perception and forecasting.Conference on Neural Information Processing Systems, 202
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.778244Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 8aa9f8b7-4216-468e-bc81-167887f2c9c9 · outbound
This paper cites Man truckscenes: A multimodal dataset for autonomous trucking in diverse conditions.Advances in Neural Information Processing Systems, 37:62062–62082.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Man truckscenes: A multimodal dataset for autonomous trucking in diverse conditions.Advances in Neural Information Processing Systems, 37:62062–62082
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.703324Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation b05017c4-67a5-4206-a04a-9b1b87cd9f62 · outbound
This paper cites Scalability in perception for autonomous driving: Waymo open dataset.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Scalability in perception for autonomous driving: Waymo open dataset
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.786274Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation cec05ce0-68c4-434e-8f79-d9661983e896 · outbound
This paper cites One million scenes for autonomous driving: Once dataset.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving One million scenes for autonomous driving: Once dataset
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.697734Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation bf73d056-a96a-4243-9e60-ef44bd737356 · outbound
This paper cites Vision Language Models in Autonomous Driving: A Survey and Outlook.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Vision Language Models in Autonomous Driving: A Survey and Outlook
Reference 32
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T16:44:56.042065Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 2a7938e7-7066-4654-946c-825b7f270d77 · outbound
This paper cites A Survey on Multimodal Large Language Models for Autonomous Driving.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving A Survey on Multimodal Large Language Models for Autonomous Driving
Reference 33
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T16:44:56.048382Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation d32995ca-0283-4a6c-b037-500b8d4bc502 · outbound
This paper cites Qwen3-VL Technical Report.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Qwen3-VL Technical Report
Reference 34
- Resolution
- verified exact
- local_arxiv, observed 2026-06-30T16:44:56.058909Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 9655550d-5953-49d1-bf53-6d7c3ad10dff · outbound
This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Llama 2: Open Foundation and Fine-Tuned Chat Models
Reference 35
- Resolution
- verified exact
- local_arxiv, observed 2026-06-30T16:44:56.071393Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 54ed0b38-7617-458e-aef5-01720f9d8b9b · outbound
This paper cites GPT-4 Technical Report.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving GPT-4 Technical Report
Reference 36
- Resolution
- verified exact
- local_arxiv, observed 2026-06-30T16:44:56.143908Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 3ffac277-ad70-467c-b57f-62b80fb750aa · outbound
This paper cites InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency
Reference 37
- Resolution
- verified exact
- local_arxiv, observed 2026-06-30T16:44:56.029971Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation a1771ba1-042a-4573-a6a8-ab14f219d7e2 · outbound
This paper cites Kimi-VL Technical Report.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Kimi-VL Technical Report
Reference 38
- Resolution
- verified exact
- local_arxiv, observed 2026-06-30T16:44:56.005964Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation b74caffe-3ff8-41e1-ab94-d67456a15197 · outbound
This paper cites Llava-onevision: Easy visual task transfer.TMLR.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Llava-onevision: Easy visual task transfer.TMLR
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.804237Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation fcf8f26a-70fb-4723-98a8-9426b2272fe5 · outbound
This paper cites DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding
Reference 40
- Resolution
- verified exact
- local_arxiv, observed 2026-06-30T16:44:56.054097Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation fe67a38c-3f1e-4445-8eae-97c8cec5f9ea · outbound
This paper cites Gemini: A Family of Highly Capable Multimodal Models.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Gemini: A Family of Highly Capable Multimodal Models
Reference 41
- Resolution
- verified exact
- local_arxiv, observed 2026-06-30T16:44:56.101355Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 85a59b92-6efb-48bc-9707-93e9dee589eb · outbound
This paper cites Henasy: Learning to assemble scene-entities for interpretable egocentric video-language model.Advances in Neural Information Processing Systems, 37:86483–86499.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Henasy: Learning to assemble scene-entities for interpretable egocentric video-language model.Advances in Neural Information Processing Systems, 37:86483–86499
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.776006Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation d249392d-32e4-411a-8869-fa1b7a185066 · outbound
This paper cites Directed- tokens: A robust multi-modality alignment approach to large language-vision models.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Directed- tokens: A robust multi-modality alignment approach to large language-vision models
Reference 43
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T16:44:56.104225Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 163974b4-f9eb-4139-8f3f-77a3e8ea6fb1 · outbound
This paper cites GAIA-1: A Generative World Model for Autonomous Driving.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving GAIA-1: A Generative World Model for Autonomous Driving
Reference 44
- Resolution
- verified exact
- local_arxiv, observed 2026-06-30T16:44:56.106523Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 75e28c7f-a03a-491c-8cdb-8b5941800416 · outbound
This paper cites Driving into the future: Multiview visual forecasting and planning with world model for autonomous driving.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Driving into the future: Multiview visual forecasting and planning with world model for autonomous driving
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.757307Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 351df3a5-d6fa-4f0f-b19a-5b3d6d918a8c · outbound
This paper cites DriveDreamer: Towards Real-world-driven World Models for Autonomous Driving.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving DriveDreamer: Towards Real-world-driven World Models for Autonomous Driving
Reference 46
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T16:44:56.117349Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation edce7211-b13f-4dcf-8bac-e9b4bcc8dd60 · outbound
This paper cites Dolphins: Multimodal language model for driving.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Dolphins: Multimodal language model for driving
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.731435Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 8f7fd824-9804-4732-93aa-f09306f1fe2f · outbound
This paper cites Rea- son2drive: Towards interpretable and chain-based reasoning for autonomous driving.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Rea- son2drive: Towards interpretable and chain-based reasoning for autonomous driving
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.705102Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation c54f2ed0-211a-4d42-ae35-2ee7899b4b08 · outbound
This paper cites Visual spatial reasoning.Transactions of the Association for Computational Linguistics, 11:635–651.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Visual spatial reasoning.Transactions of the Association for Computational Linguistics, 11:635–651
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.737175Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 7713b246-3966-4641-94a6-a2f2fbcaf864 · outbound
This paper cites An Empirical Analysis on Spatial Reasoning Capabilities of Large Multimodal Models.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving An Empirical Analysis on Spatial Reasoning Capabilities of Large Multimodal Models
Reference 50
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T16:44:56.119897Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 77b10584-e331-485b-a269-77c67ee6e5bb · outbound
This paper cites EmbSpatial-Bench: Benchmarking Spatial Understanding for Embodied Tasks with Large Vision-Language Models.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving EmbSpatial-Bench: Benchmarking Spatial Understanding for Embodied Tasks with Large Vision-Language Models
Reference 51
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T16:44:56.133446Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation ddf145be-575c-4c10-828b-04d397eae72d · outbound
This paper cites Spatialrgpt: Grounded spatial reasoning in vision-language models.Advances in Neural Information Processing Systems, 37:135062–135093.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Spatialrgpt: Grounded spatial reasoning in vision-language models.Advances in Neural Information Processing Systems, 37:135062–135093
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.735349Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 061fa39c-3333-4047-b12e-fbe3b6d5bba3 · outbound
This paper cites Spatialvlm: Endowing vision-language models with spatial reasoning capabilities.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Spatialvlm: Endowing vision-language models with spatial reasoning capabilities
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.690286Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 7ff65849-f172-4b62-a8af-23eb11dbd7a0 · outbound
This paper cites Spatialbot: Precise spatial understanding with vision language models.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Spatialbot: Precise spatial understanding with vision language models
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.806450Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation fdf4a296-7595-4a16-b8cb-82407f15c720 · outbound
This paper cites Spatialllm: A compound 3d- informed design towards spatially-intelligent large multimodal models.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Spatialllm: A compound 3d- informed design towards spatially-intelligent large multimodal models
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.714442Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 5f4702fa-09a1-4018-9624-164a1344e50f · outbound
This paper cites Robospa- tial: Teaching spatial understanding to 2d and 3d vision-language models for robotics.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Robospa- tial: Teaching spatial understanding to 2d and 3d vision-language models for robotics
Reference 56
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.725664Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 557905cf-2c09-43d6-912e-8cf1e0467720 · outbound
This paper cites Gemini Robotics: Bringing AI into the Physical World.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Gemini Robotics: Bringing AI into the Physical World
Reference 57
- Resolution
- verified exact
- local_arxiv, observed 2026-06-30T16:44:56.098982Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation c178bf64-6215-4858-8932-b616a2f27228 · outbound
This paper cites SpatialCoT: Advancing Spatial Reasoning through Coordinate Alignment and Chain-of-Thought for Embodied Task Planning.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving SpatialCoT: Advancing Spatial Reasoning through Coordinate Alignment and Chain-of-Thought for Embodied Task Planning
Reference 58
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T16:44:56.062222Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 2bd05019-9f66-47b6-9271-19ef4ba2874e · outbound
This paper cites Omnispatial: Towards comprehensive spatial reasoning benchmark for vision language models.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Omnispatial: Towards comprehensive spatial reasoning benchmark for vision language models
Reference 60
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T16:44:56.068860Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 45a9b7c3-7ce1-40dd-8ffe-f8184af67398 · outbound
This paper cites HSSBench: Benchmarking Humanities and Social Sciences Ability for Multimodal Large Language Models.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving HSSBench: Benchmarking Humanities and Social Sciences Ability for Multimodal Large Language Models
Reference 61
- Resolution
- verified exact
- arxiv_id, observed 2026-08-12T02:23:50.971990Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 12e0fb8a-c213-4825-8799-72f80972fec6 · outbound
This paper cites Spatial-dise: A unified benchmark for evaluating spatial reasoning in vision-language models.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Spatial-dise: A unified benchmark for evaluating spatial reasoning in vision-language models
Reference 62
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T16:44:56.051540Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation d18c83e4-783f-4d0f-898b-e86c4781003e · outbound
This paper cites Mind the Gap: Benchmarking Spatial Reasoning in Vision-Language Models.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Mind the Gap: Benchmarking Spatial Reasoning in Vision-Language Models
Reference 63
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T16:44:56.045464Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 1e7cab4a-e67c-4343-9651-9fc8462c1f2d · outbound
This paper cites Mmsi-video-bench: A holistic benchmark for video-based spatial intelligence.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Mmsi-video-bench: A holistic benchmark for video-based spatial intelligence
Reference 65
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T16:44:56.056684Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 4a26d7b4-17ff-41c5-920d-337d4fbb55bd · outbound
This paper cites Cambrian-S: Towards Spatial Supersensing in Video.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Cambrian-S: Towards Spatial Supersensing in Video
Reference 66
- Resolution
- verified exact
- local_arxiv, observed 2026-06-30T16:44:56.085193Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation db16a66f-347c-4084-b50b-cd9aab044778 · outbound
This paper cites Agqa: A benchmark for compositional spatio-temporal reasoning.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Agqa: A benchmark for compositional spatio-temporal reasoning
Reference 67
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.792010Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 5208b9b5-379e-47b1-a6a9-43a1855d0395 · outbound
This paper cites Next-qa: Next phase of question-answering to explaining temporal actions.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Next-qa: Next phase of question-answering to explaining temporal actions
Reference 68
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.780191Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 103f2c57-2eb0-4448-8b8c-40e713f614d9 · outbound
This paper cites Visuospatial perspective taking in multimodal language models.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Visuospatial perspective taking in multimodal language models
Reference 69
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T16:44:56.148812Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 1dc48536-9cac-4cc0-9600-e63ee7942e78 · outbound
This paper cites Egocentric Bias in Vision-Language Models.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Egocentric Bias in Vision-Language Models
Reference 70
- Resolution
- verified exact
- arxiv_id, observed 2026-07-15T02:22:00.923596Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 2c136e4f-359a-4d3b-921e-bb845528047c · outbound
This paper cites Allocentric perceiver: Disentangling allocentric reasoning from egocentric visual priors via frame instantiation.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Allocentric perceiver: Disentangling allocentric reasoning from egocentric visual priors via frame instantiation
Reference 71
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T16:44:56.019175Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 9d3240a9-9e3e-41ae-be79-769d0542c6fc · outbound
This paper cites Keep it sympl: Symbolic projective layout for allocentric spatial reasoning in vision-language models.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Keep it sympl: Symbolic projective layout for allocentric spatial reasoning in vision-language models
Reference 72
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T16:44:56.024748Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation e513a6c6-598c-42cc-946a-022c513cc61d · outbound
This paper cites CAPTURe: Evaluating Spatial Reasoning in Vision Language Models via Occluded Object Counting.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving CAPTURe: Evaluating Spatial Reasoning in Vision Language Models via Occluded Object Counting
Reference 73
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T16:44:56.124516Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation ff714df9-b2d9-4417-b1c4-c8c5723470a8 · outbound
This paper cites Beyond the Visible: Benchmarking Occlusion Perception in Multimodal Large Language Models.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Beyond the Visible: Benchmarking Occlusion Perception in Multimodal Large Language Models
Reference 74
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T16:44:56.027656Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 1656cbd0-b151-4641-bd10-ddd9d3348516 · outbound
This paper cites Mind over space: Can multimodal large language models mentally navigate?.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Mind over space: Can multimodal large language models mentally navigate?
Reference 75
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T16:44:56.013763Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation dccea137-34b3-4506-8ec4-22857003cfff · outbound
This paper cites Video2layout: Recall and reconstruct metric-grounded cognitive map for spatial reasoning.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Video2layout: Recall and reconstruct metric-grounded cognitive map for spatial reasoning
Reference 76
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T16:44:56.011148Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation d13a77b8-cd58-4f65-b461-274a47f11461 · outbound
This paper cites Embodied-R: Collaborative Framework for Activating Embodied Spatial Reasoning in Foundation Models via Reinforcement Learning.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Embodied-R: Collaborative Framework for Activating Embodied Spatial Reasoning in Foundation Models via Reinforcement Learning
Reference 77
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T16:44:56.141303Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 6f4d57fd-d34d-4953-821b-dd0e4492c6de · outbound
This paper cites Talk2car: Taking control of your self-driving car.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Talk2car: Taking control of your self-driving car
Reference 78
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.749432Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 053ee545-ae35-4e97-8647-5ceb13442531 · outbound
This paper cites Textual explanations for self-driving vehicles.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Textual explanations for self-driving vehicles
Reference 79
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.763268Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 6a2d3aa1-88b4-4256-b559-2dbf53d8b5c5 · outbound
This paper cites NuScenes-MQA: Integrated Evaluation of Captions and QA for Autonomous Driving Datasets using Markup Annotations.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving NuScenes-MQA: Integrated Evaluation of Captions and QA for Autonomous Driving Datasets using Markup Annotations
Reference 80
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T16:44:56.021817Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation a55cd804-8ef1-4680-a12c-5a9d8a4e68ec · outbound
This paper cites Stride-qa: Visual question answering dataset for spatiotemporal reasoning in urban driving scenes.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Stride-qa: Visual question answering dataset for spatiotemporal reasoning in urban driving scenes
Reference 81
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T16:44:56.130871Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation caf445aa-9f86-451c-8aaa-8f277b2bfc7c · outbound
This paper cites Bench2Drive: Towards Multi-Ability Benchmarking of Closed-Loop End-To-End Autonomous Driving.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Bench2Drive: Towards Multi-Ability Benchmarking of Closed-Loop End-To-End Autonomous Driving
Reference 82
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T16:44:56.032836Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation e8b1579c-2cc9-435d-9f7b-6116c8b0ad72 · outbound
This paper cites Road scene graph: A semantic graph-based scene representation dataset for intelligent vehicles.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Road scene graph: A semantic graph-based scene representation dataset for intelligent vehicles
Reference 83
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.701165Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation a7d5b92b-9b44-4f34-8a81-b6a08b159d92 · outbound
This paper cites RS2G: Data-Driven Scene-Graph Extraction and Embedding for Robust Autonomous Perception and Scenario Understanding.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving RS2G: Data-Driven Scene-Graph Extraction and Embedding for Robust Autonomous Perception and Scenario Understanding
Reference 84
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T16:44:56.127056Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation ea6d30d4-b30e-4386-b7e3-d8cfa84120bf · outbound
This paper cites SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features
Reference 85
- Resolution
- verified exact
- local_arxiv, observed 2026-06-30T16:44:56.135972Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation f769e9eb-9f84-4297-9410-d03e38befd3a · outbound
This paper cites Qwen3 Technical Report.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Qwen3 Technical Report
Reference 86
- Resolution
- verified exact
- local_arxiv, observed 2026-06-30T16:44:56.138487Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation e8cafc9b-107a-40a8-a8f1-4980cfd7c725 · outbound
This paper cites Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Reference 87
- Resolution
- verified exact
- local_arxiv, observed 2026-06-30T16:44:56.108882Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 34a05e40-7952-4d2c-b237-17b401fe220c · outbound
This paper cites GPT-4o System Card.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving GPT-4o System Card
Reference 88
- Resolution
- verified exact
- local_arxiv, observed 2026-06-30T16:44:56.114512Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 85e50d5d-3ac4-4ad4-94a2-931b68b53dd7 · outbound
This paper cites OpenAI GPT-5 System Card.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving OpenAI GPT-5 System Card
Reference 89
- Resolution
- verified exact
- local_arxiv, observed 2026-06-30T16:44:56.122000Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 51583bb9-4d59-4c0a-863f-5179e44d18ed · outbound
This paper cites Gemma 3 technical report.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Gemma 3 technical report
Reference 90
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.744293Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 4d7619c8-83e9-44ca-ae72-7264adb5a8e4 · outbound
This paper cites InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models
Reference 91
- Resolution
- verified exact
- local_arxiv, observed 2026-06-30T16:44:56.146260Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation dbf5427a-699c-44ac-9909-e24c7be5fac7 · outbound
This paper cites Long Context Transfer from Language to Vision.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Long Context Transfer from Language to Vision
Reference 92
- Resolution
- verified exact
- local_arxiv, observed 2026-06-30T16:44:56.090190Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 3379d742-13d3-4106-be51-1e142470df30 · outbound
This paper cites LLaVA-Video: Video Instruction Tuning With Synthetic Data.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving LLaVA-Video: Video Instruction Tuning With Synthetic Data
Reference 93
- Resolution
- verified exact
- local_arxiv, observed 2026-06-30T16:44:56.081947Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation f0702a1e-fb16-41ec-b180-3d71a3f1cdb4 · outbound
This paper cites Scaling spatial intelligence with multimodal foundation models.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Scaling spatial intelligence with multimodal foundation models
Reference 94
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T16:44:56.008458Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 38dfe81d-c142-4e66-b0af-0bf30c46bbe1 · outbound
This paper cites SpatialThinker: Reinforcing Scene Graph-Grounded Spatial Reasoning via Dense Rewards.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving SpatialThinker: Reinforcing Scene Graph-Grounded Spatial Reasoning via Dense Rewards
Reference 95
- Resolution
- verified exact
- arxiv_id, observed 2026-07-07T01:16:00.407423Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation f33e53a8-abdf-422a-b6a6-fafc3a2d35a6 · outbound
This paper cites Video-mme: The first-ever comprehensive evaluation benchmark of multi-modal llms in video analysis.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Video-mme: The first-ever comprehensive evaluation benchmark of multi-modal llms in video analysis
Reference 96
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.695942Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 587c41a5-2cd0-4360-a093-042a196a5092 · outbound
This paper cites Measuring massive multitask language understanding.International Conference on Learning Representations (ICLR).
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Measuring massive multitask language understanding.International Conference on Learning Representations (ICLR)
Reference 97
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.738967Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 05b314d4-1ef3-4fc2-9582-9a2ba799ee5a · outbound
This paper cites Mmmu: A massive multi-discipline multimodal understanding and reasoning benchmark for expert agi.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Mmmu: A massive multi-discipline multimodal understanding and reasoning benchmark for expert agi
Reference 98
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.723905Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 054cba32-fab1-442a-bc10-bc6f296c5a19 · outbound
This paper cites Thinking in space: How multimodal large language models see, remember, and recall spaces.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Thinking in space: How multimodal large language models see, remember, and recall spaces
Reference 99
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.712450Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation d34e47c0-cc7c-4161-843c-21f29473bc91 · outbound
This paper cites A coefficient of agreement for nominal scales.Educational and psychological measure- ment, 20(1):37–46.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving A coefficient of agreement for nominal scales.Educational and psychological measure- ment, 20(1):37–46
Reference 100
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.733472Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation b14ca13c-2e9b-4417-bc5b-f68011cbd662 · outbound
This paper cites Language models as zero-shot planners: Extracting actionable knowledge for embodied agents.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Language models as zero-shot planners: Extracting actionable knowledge for embodied agents
Reference 101
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.800274Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 2c90cc1f-c329-4edc-87a4-ed4957bc7ceb · outbound
This paper cites Swe-bench: Can language models resolve real-world github issues?The Twelfth International Conference on Learning Representations.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving Swe-bench: Can language models resolve real-world github issues?The Twelfth International Conference on Learning Representations
Reference 102
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T12:44:53.798270Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Pith citing papers
No inbound Pith citation observations are available.