ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving | Paper Citation Record

Observation 5a873005-05e9-4b7b-813c-35631c17d155 · outbound

This paper cites Autonomous driving: cognitive construction and situation understanding.Science China Information Sciences, 62(8):81101.

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving Autonomous driving: cognitive construction and situation understanding.Science China Information Sciences, 62(8):81101

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:26:55.542442Z

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No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation ebc3e750-90d1-49cb-9dd8-b146b1426fe6 · outbound

This paper cites Advanced trajectory prediction framework integrating diverse driving styles for autonomous vehicles.Science China Information Sciences, 69(3):1–16.

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving Advanced trajectory prediction framework integrating diverse driving styles for autonomous vehicles.Science China Information Sciences, 69(3):1–16

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:26:55.855557Z

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Observation 2a1a8c28-bf03-462c-8bda-659fc0f91b0d · outbound

This paper cites Trajectory planning and tracking control for vehicles with tire blowout in complex traffic flows.Science China Information Sciences, 68(3):132202.

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving Trajectory planning and tracking control for vehicles with tire blowout in complex traffic flows.Science China Information Sciences, 68(3):132202

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:26:55.857714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 2fab4fc4-011c-4ac3-ac09-a160969784d9 · outbound

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

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving Vision language models in autonomous driving: A survey and outlook.IEEE Transactions on Intelligent Vehicles

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:26:55.850630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 8756bb6c-2b7a-454f-bc60-687ed67c2fc8 · outbound

This paper cites Large (vision) language models for autonomous vehicles: Current trends and future directions.IEEE Transactions on Intelligent Transportation Systems, 27(1):187–210.

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving Large (vision) language models for autonomous vehicles: Current trends and future directions.IEEE Transactions on Intelligent Transportation Systems, 27(1):187–210

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:26:55.546866Z

Source-reported events for the cited work

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Observation aaf81770-112c-4d77-a7e2-34056e4069fa · outbound

This paper cites Enhancing scene understanding based on deep learning for end-to-end autonomous driving.Engineering Applications of Artificial Intelligence, 116:105474.

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving Enhancing scene understanding based on deep learning for end-to-end autonomous driving.Engineering Applications of Artificial Intelligence, 116:105474

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:26:55.544611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 712660e6-c267-44f3-9962-fe3950ba111a · outbound

This paper cites Predicting the road ahead: A knowledge graph based foundation model for scene understanding in autonomous driving.

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving Predicting the road ahead: A knowledge graph based foundation model for scene understanding in autonomous driving

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:26:55.853387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation a4b0a072-c135-417d-b920-d2358c51e479 · outbound

This paper cites an unresolved cited work.

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-05-22T18:26:55.879536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation f4f995cb-3056-4bf7-a758-59ee6d0ea0df · outbound

This paper cites Rethinking closed-loop training for autonomous driving.

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving Rethinking closed-loop training for autonomous driving

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:26:55.881723Z

Source-reported events for the cited work

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Observation 614c26da-7a16-48d4-a955-66b8eb2ddb1e · outbound

This paper cites Bench2drive: Towards multi-ability benchmarking of closed-loop end-to-end autonomous driving.Advances in Neural Information Processing Systems, 37:819–844.

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving Bench2drive: Towards multi-ability benchmarking of closed-loop end-to-end autonomous driving.Advances in Neural Information Processing Systems, 37:819–844

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:26:55.895812Z

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Observation d200f5b3-fd86-4953-94e1-98f9fdad2570 · outbound

This paper cites Neuroncap: Photorealistic closed-loop safety testing for autonomous driving.

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving Neuroncap: Photorealistic closed-loop safety testing for autonomous driving

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:26:55.877496Z

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Observation 70d6f7f8-50e3-45b2-b148-7a5b8c620499 · outbound

This paper cites A peek into Tesla’s autonomous future: Core tech revealed at ICCV 2025 WDFM-AD.

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving A peek into Tesla’s autonomous future: Core tech revealed at ICCV 2025 WDFM-AD

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:26:55.871526Z

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Observation 508d202f-0fe8-4141-b1ec-52fb6908b9a2 · outbound

This paper cites Marius Zöllner.

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving Marius Zöllner

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:26:55.908822Z

Source-reported events for the cited work

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Observation bd02eec9-22d0-4b10-9aac-7fa6ab207456 · outbound

This paper cites An image is worth 1/2 tokens after layer 2: Plug-and-play inference acceleration for large vision-language models.

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving An image is worth 1/2 tokens after layer 2: Plug-and-play inference acceleration for large vision-language models

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:26:55.910774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b30bbe10-6d20-40c1-b655-1cd960827f52 · outbound

This paper cites Token merging: Your ViT but faster.

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving Token merging: Your ViT but faster

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:26:55.902465Z

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No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 8c707ee6-1c76-4134-bb33-7c74a24a7eed · outbound

This paper cites Sparsevlm: Visual token sparsification for efficient vision-language model inference.

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving Sparsevlm: Visual token sparsification for efficient vision-language model inference

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:26:55.883928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 826d4e66-415c-4436-b9c2-2eb961143e53 · outbound

This paper cites Stop Looking for Important Tokens in Multimodal Language Models: Duplication Matters More.

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving Stop Looking for Important Tokens in Multimodal Language Models: Duplication Matters More

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-11T12:46:05.479873Z

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Observation aa650f97-d347-4b46-90c9-bc6bdeac4abf · outbound

This paper cites Token Pruning in Multimodal Large Language Models: Are We Solving the Right Problem?.

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving Token Pruning in Multimodal Large Language Models: Are We Solving the Right Problem?

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-11T12:46:05.419065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 5a04a6f7-8b65-4c4f-ac67-0dab54ba489b · outbound

This paper cites Fastdrivevla: Efficient end-to-end driving via plug-and-play reconstruction-based token pruning.

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving Fastdrivevla: Efficient end-to-end driving via plug-and-play reconstruction-based token pruning

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:26:55.863631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b7e03b63-edac-4eb0-8c2c-bdbb44fab03c · outbound

This paper cites Prune2drive: A plug-and-play framework for accelerating vision-language models in autonomous driving.

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving Prune2drive: A plug-and-play framework for accelerating vision-language models in autonomous driving

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-11T12:46:05.426208Z

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Observation f2d06f06-1715-41ec-b3f5-f8d05f1f1e33 · outbound

This paper cites Masked autoencoders are scalable vision learners.

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving Masked autoencoders are scalable vision learners

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:26:55.873674Z

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Observation 50dcaec1-9fbf-44fa-91d3-080787456204 · outbound

This paper cites Feedback is all you need: from chatgpt to autonomous driving.Science China Information Sciences, 66(6):1–3.

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving Feedback is all you need: from chatgpt to autonomous driving.Science China Information Sciences, 66(6):1–3

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:26:55.865600Z

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Observation ada2da64-d098-43d0-8f0f-07f7c8c8f5e2 · outbound

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

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving GPT-Driver: Learning to Drive with GPT

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-15T15:05:32.082062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b9cf6316-c58c-4110-bedb-aa6ffe13d5d5 · outbound

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

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving Driving with llms: Fusing object-level vector modality for explainable autonomous driving

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:26:55.893839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b25ab475-d7e9-40ba-a71b-271181ec2bef · outbound

This paper cites Waslander, Yu Liu, and Hongsheng Li.

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving Waslander, Yu Liu, and Hongsheng Li

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:26:55.885741Z

Source-reported events for the cited work

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Observation 8d494005-0a97-4a8b-83ed-700ebf0ccb71 · outbound

This paper cites Senna: Bridging Large Vision-Language Models and End-to-End Autonomous Driving.

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving Senna: Bridging Large Vision-Language Models and End-to-End Autonomous Driving

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-05-15T15:24:24.181007Z

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Observation 9ce2ae32-ae69-4957-bb10-15472285ab45 · outbound

This paper cites Meyer, Siva Karthik Mustikovela, Siddhartha Srinivasa, Eric M.

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving Meyer, Siva Karthik Mustikovela, Siddhartha Srinivasa, Eric M

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:26:55.859576Z

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No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation e97555d7-61c7-430f-9d3a-3a14ca1ba5ae · outbound

This paper cites Orion: A holistic end-to-end autonomous driving framework by vision-language instructed action generation.

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving Orion: A holistic end-to-end autonomous driving framework by vision-language instructed action generation

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:26:55.861760Z

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No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b6737d63-492c-400d-abc0-0060355f7ca0 · outbound

This paper cites Covla: Comprehensive vision-language-action dataset for autonomous driving.

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving Covla: Comprehensive vision-language-action dataset for autonomous driving

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:26:55.904617Z

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No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 579ee4e2-ce4e-4d49-854c-ce843d13cc60 · outbound

This paper cites DriveMoE: Mixture-of-Experts for Vision-Language-Action Model in End-to-End Autonomous Driving.

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving DriveMoE: Mixture-of-Experts for Vision-Language-Action Model in End-to-End Autonomous Driving

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-20T00:05:28.917220Z

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No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation d91bbb87-96c7-40e4-8f6a-878b311f790c · outbound

This paper cites arXiv preprint arXiv:2602.20794 (2026) 10.

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving arXiv preprint arXiv:2602.20794 (2026) 10

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-05-11T12:46:05.441083Z

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No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 46c5db47-f1f7-4848-9ebe-20c11a6d5583 · outbound

This paper cites Mpdrive: Improving spatial understanding with marker-based prompt learning for autonomous driving.

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving Mpdrive: Improving spatial understanding with marker-based prompt learning for autonomous driving

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:26:55.888027Z

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No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation ba834003-4110-44f5-84df-664a4c6c407a · outbound

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

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving SpaceDrive: Infusing Spatial Awareness into VLM-based Autonomous Driving

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-05-22T02:03:27.523663Z

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No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 29ef0f31-60b5-4c5c-b815-cb3677c64b37 · outbound

This paper cites Reason2drive: Towards interpretable and chain-based reasoning for autonomous driving.

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving Reason2drive: Towards interpretable and chain-based reasoning for autonomous driving

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:26:55.869686Z

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No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation cf7721f2-1a1c-4da4-b0e2-82f3090e2206 · outbound

This paper cites DynVLA: Learning world dynamics for action reasoning in autonomous driving.

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving DynVLA: Learning world dynamics for action reasoning in autonomous driving

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-05-11T12:46:05.511201Z

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No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation f095c9db-1d57-4f2d-8928-cd46f1b08821 · outbound

This paper cites Accelerating structured chain-of-thought in autonomous vehicles.arXiv preprint arXiv:2602.02864.

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving Accelerating structured chain-of-thought in autonomous vehicles.arXiv preprint arXiv:2602.02864

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-05-11T12:46:05.517998Z

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No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation cfcaa20e-9a76-4de4-82db-18d8d45e2b6c · outbound

This paper cites RoboTron-Drive: All-in-One Large Multimodal Model for Autonomous Driving.

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving RoboTron-Drive: All-in-One Large Multimodal Model for Autonomous Driving

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-05-11T12:46:05.462818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 27e5ef07-84f4-480f-999f-24b9fd66755c · outbound

This paper cites Divprune: Diversity-based visual token pruning for large multimodal models.

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving Divprune: Diversity-based visual token pruning for large multimodal models

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:26:55.915160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 7b43d87c-edab-490f-ac59-713155f0c0c1 · outbound

This paper cites Beyond text-visual attention: Exploiting visual cues for effective token pruning in vlms.

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving Beyond text-visual attention: Exploiting visual cues for effective token pruning in vlms

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:26:55.891807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation c461c981-5028-4e38-a399-77eade894741 · outbound

This paper cites Pact: Pruning and clustering-based token reduction for faster visual language models.

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving Pact: Pruning and clustering-based token reduction for faster visual language models

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:26:55.912768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 2eb060c9-00a5-4657-b91e-0886bd3e132e · outbound

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

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving Drivelm: Driving with graph visual question answering

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:26:55.867435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 3494b704-9085-405c-b089-09bdf12791f4 · outbound

This paper cites Lingoqa: Visual question answering for autonomous driving.

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving Lingoqa: Visual question answering for autonomous driving

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:26:55.897901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 5b1d436a-979e-406e-9ab3-76403a9fcfe8 · outbound

This paper cites Holistic autonomous driving understanding by bird’s-eye-view injected multi-modal large models.

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving Holistic autonomous driving understanding by bird’s-eye-view injected multi-modal large models

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:26:55.900462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation cc38bf08-196e-49b7-ab37-5ab96d1585c1 · outbound

This paper cites an unresolved cited work.

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving Unresolved cited work

Reference 44

Resolution: unresolved; raw_fallback, observed 2026-05-22T18:26:55.875436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation e2cad3b0-9673-453b-8cda-82ca2031a52a · outbound

This paper cites Sigmoid loss for language image pre-training.

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving Sigmoid loss for language image pre-training

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:26:55.906727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 7c0225dd-5366-4e44-976c-f94f2758e0d7 · outbound

This paper cites The Llama 3 Herd of Models.

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving The Llama 3 Herd of Models

Reference 46

Resolution: verified exact; local_arxiv, observed 2026-05-11T12:46:05.455242Z

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Observation 9698e0a4-9060-4735-a5ad-ab07abb6f2e1 · outbound

This paper cites Qwen3-vl technical report.

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving Qwen3-vl technical report

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T18:26:55.889852Z

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