RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding | Paper Citation Record

Observation 94e0dc85-9490-4b6c-88e5-a152c6778516 · outbound

This paper cites Did we test all scenarios for automated and autonomous driving systems?.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Did we test all scenarios for automated and autonomous driving systems?

Reference 1

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Observation 32e2e67f-ae1a-40a0-9939-30e7c26eb3be · outbound

This paper cites Safeshift: Safety-informed distribution shifts for robust trajectory pre- diction in autonomous driving,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Safeshift: Safety-informed distribution shifts for robust trajectory pre- diction in autonomous driving,

Reference 2

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Observation e2f63b6d-ace2-4478-bc08-b8d61f475dda · outbound

This paper cites Scenario-based test automation for highly automated vehicles: A review and paving the way for systematic safety assurance,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Scenario-based test automation for highly automated vehicles: A review and paving the way for systematic safety assurance,

Reference 3

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Observation 50422c5b-8330-4a2e-82da-735bcb6def95 · outbound

This paper cites Waymo's Safety Methodologies and Safety Readiness Determinations.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Waymo's Safety Methodologies and Safety Readiness Determinations

Reference 4

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Observation a1a6a886-4c42-441c-ac61-91e08a7d906a · outbound

This paper cites Driving to safety: How many miles of driving would it take to demonstrate autonomous vehicle reliability?.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Driving to safety: How many miles of driving would it take to demonstrate autonomous vehicle reliability?

Reference 5

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Observation 07d01bd1-3831-4103-becb-556f00be3239 · outbound

This paper cites Large scale interactive motion forecasting for autonomous driving: The waymo open motion dataset,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Large scale interactive motion forecasting for autonomous driving: The waymo open motion dataset,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T17:34:03.348587Z

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Observation f7405654-aef9-4503-83f3-cbfe5edfcb35 · outbound

This paper cites NuPlan: A closed-loop ML-based planning benchmark for autonomous vehicles.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding NuPlan: A closed-loop ML-based planning benchmark for autonomous vehicles

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T17:34:03.445497Z

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Observation 23e30394-4db7-4c78-98e6-50f9d4c4e84e · outbound

This paper cites Argoverse 2: Next Generation Datasets for Self-Driving Perception and Forecasting.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Argoverse 2: Next Generation Datasets for Self-Driving Perception and Forecasting

Reference 8

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Observation cd382344-556e-4901-88e8-fe1add1487b2 · outbound

This paper cites Curse of rarity for autonomous vehicles,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Curse of rarity for autonomous vehicles,

Reference 9

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Observation b21230a0-c75b-4ee2-b7bd-5efa1d654a37 · outbound

This paper cites Cadre: Controllable and diverse generation of safety-critical driving scenarios using real-world trajectories,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Cadre: Controllable and diverse generation of safety-critical driving scenarios using real-world trajectories,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:34:06.904435Z

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Observation 4daf9536-9192-4cb5-975d-558c0dff15bc · outbound

This paper cites A survey on safety-critical driving scenario generation—a methodological perspec- tive,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding A survey on safety-critical driving scenario generation—a methodological perspec- tive,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T17:34:03.765847Z

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Observation d1aaf07d-44d2-4e13-83fd-07cfe5f2570d · outbound

This paper cites Cat: Closed-loop adversarial training for safe end-to-end driving,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Cat: Closed-loop adversarial training for safe end-to-end driving,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T17:34:03.865531Z

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Observation d4565253-c832-4f8f-b83f-fb14308ac522 · outbound

This paper cites Goose: Goal-conditioned reinforcement learning for safety-critical scenario generation,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Goose: Goal-conditioned reinforcement learning for safety-critical scenario generation,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:34:06.710263Z

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Observation 0ffcf8e4-8f97-478e-8c8e-a71b03a3646f · outbound

This paper cites SEAL: Towards Safe Autonomous Driving via Skill-Enabled Adversary Learning for Closed-Loop Scenario Generation.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding SEAL: Towards Safe Autonomous Driving via Skill-Enabled Adversary Learning for Closed-Loop Scenario Generation

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T17:34:04.026942Z

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Observation bca64264-3a0d-4cff-87e0-bded54bc7d6d · outbound

This paper cites Tads: a novel dataset for road traffic accident detection from a surveillance perspective,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Tads: a novel dataset for road traffic accident detection from a surveillance perspective,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:34:06.494009Z

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Observation 55abcde2-fb48-4e04-b3e8-b84c2a0b5120 · outbound

This paper cites Sutd-trafficqa: A question answering benchmark and an efficient network for video reasoning over traffic events,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Sutd-trafficqa: A question answering benchmark and an efficient network for video reasoning over traffic events,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T17:34:04.171885Z

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Observation 44afc685-8f87-4cab-90ae-f291ec381ea2 · outbound

This paper cites Prototypical contrastive learning of unsupervised representations,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Prototypical contrastive learning of unsupervised representations,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:34:06.387425Z

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Observation b3d9652d-82d5-4615-a2da-b91ddda56b50 · outbound

This paper cites Scalability in perception for autonomous driving: Waymo open dataset,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Scalability in perception for autonomous driving: Waymo open dataset,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T17:34:04.287461Z

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Observation a8e5a201-9879-46bb-946e-327a4c441d9e · outbound

This paper cites Openmpd: An open multimodal perception dataset for autonomous driving,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Openmpd: An open multimodal perception dataset for autonomous driving,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:34:06.359205Z

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Observation de3156bb-a7b8-44de-828b-839b81e67219 · outbound

This paper cites nuscenes: A multimodal dataset for autonomous driving,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding nuscenes: A multimodal dataset for autonomous driving,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T17:34:04.414163Z

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Observation 1598ddfa-5c94-4f66-9763-a7c9b0be4377 · outbound

This paper cites The highd dataset: A drone dataset of naturalistic vehicle trajectories on german highways for validation of highly automated driving systems,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding The highd dataset: A drone dataset of naturalistic vehicle trajectories on german highways for validation of highly automated driving systems,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T17:34:04.475832Z

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Observation 3abe68af-b870-4aa4-9443-7e3a3c848f10 · outbound

This paper cites Abductive ego-view accident video understanding for safe driving perception,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Abductive ego-view accident video understanding for safe driving perception,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:34:06.335614Z

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Observation e590b075-77d0-4954-b6a0-866821f98b29 · outbound

This paper cites Cadp: A novel dataset for cctv traffic camera based accident analysis,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Cadp: A novel dataset for cctv traffic camera based accident analysis,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:34:06.327786Z

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Observation a213febd-3a50-4a57-88f8-f164ce8f62bc · outbound

This paper cites Learning naturalistic driving environment with statistical realism,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Learning naturalistic driving environment with statistical realism,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-06T17:34:04.647354Z

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Observation f6da2031-5418-4245-b8f6-b44c2b212c1d · outbound

This paper cites Mixsim: A hierarchical framework for mixed reality traffic simulation,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Mixsim: A hierarchical framework for mixed reality traffic simulation,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T17:34:04.694508Z

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Observation 0b846678-a6d7-4d6f-9b8d-76b7d9ccc717 · outbound

This paper cites Bits: Bi-level imitation for traffic simulation,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Bits: Bi-level imitation for traffic simulation,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T17:34:04.749893Z

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Observation 33635e75-24fc-4de9-936e-daa1c26958c8 · outbound

This paper cites Task- driven controllable scenario generation framework based on aog,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Task- driven controllable scenario generation framework based on aog,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:34:06.302592Z

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Observation 094375c4-ea4e-4cf1-bae6-a89c7c56f7d2 · outbound

This paper cites Waymo simulated driving behavior in reconstructed fatal crashes within an autonomous vehicle operating domain,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Waymo simulated driving behavior in reconstructed fatal crashes within an autonomous vehicle operating domain,

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T17:34:04.845365Z

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Observation 2a794bdf-a07e-4def-9ac9-2d35f415d960 · outbound

This paper cites Hazardous scenario enhanced generation for automated vehicle testing based on optimization searching method,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Hazardous scenario enhanced generation for automated vehicle testing based on optimization searching method,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:34:06.288987Z

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Observation a282b135-9dd0-46ae-a024-fbf0a3d06377 · outbound

This paper cites Advanced sce- nario generation for calibration and verification of autonomous vehicles,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Advanced sce- nario generation for calibration and verification of autonomous vehicles,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:34:06.280459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b788cc14-5818-4abe-90f0-f42a4992cad2 · outbound

This paper cites Realgen: Retrieval augmented generation for controllable traffic scenarios,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Realgen: Retrieval augmented generation for controllable traffic scenarios,

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-06T17:34:05.018082Z

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Observation 25c84c90-cca9-4487-8f3a-db17c04657b8 · outbound

This paper cites Diffscene: Diffusion-based safety-critical scenario generation for autonomous vehi- cles,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Diffscene: Diffusion-based safety-critical scenario generation for autonomous vehi- cles,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:34:06.268319Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 66f69409-b260-4a93-a6c9-88a2421ac6f7 · outbound

This paper cites SAFE-SIM: Safety-Critical Closed-Loop Traffic Simulation with Diffusion-Controllable Adversaries.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding SAFE-SIM: Safety-Critical Closed-Loop Traffic Simulation with Diffusion-Controllable Adversaries

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-06T17:34:05.147241Z

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Observation 6e31d16c-e513-4931-be35-8e83adb0be41 · outbound

This paper cites Generating useful accident-prone driving scenarios via a learned traffic prior,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Generating useful accident-prone driving scenarios via a learned traffic prior,

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-06T17:34:05.223478Z

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Observation 86ae7257-2a71-4a64-a882-e22a266e9bb5 · outbound

This paper cites Implicit latent variable model for scene-consistent motion forecasting,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Implicit latent variable model for scene-consistent motion forecasting,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:34:06.255342Z

Source-reported events for the cited work

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Observation b0661ce1-926b-46ee-940b-2343774eb270 · outbound

This paper cites Real-time motion prediction via heterogeneous polyline transformer with relative pose encoding,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Real-time motion prediction via heterogeneous polyline transformer with relative pose encoding,

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-06T17:34:05.415957Z

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Observation 07a07fa3-8d08-44f7-8983-19a2ed474870 · outbound

This paper cites Motion transformer with global intention localization and local movement refinement,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Motion transformer with global intention localization and local movement refinement,

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-06T17:34:05.515365Z

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Observation 2d52bf81-fb3c-4f6b-adcd-43956f475684 · outbound

This paper cites Smart: Scalable multi-agent real- time motion generation via next-token prediction,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Smart: Scalable multi-agent real- time motion generation via next-token prediction,

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-06T17:34:05.599426Z

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Observation 293a086f-cd09-4286-9f76-b32318dc7d8a · outbound

This paper cites Attention is all you need,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Attention is all you need,

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-06T17:34:05.706026Z

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Observation 83e55ae1-0635-4c74-b000-df6125d03a03 · outbound

This paper cites Tokenize the World into Object-level Knowledge to Address Long-tail Events in Autonomous Driving.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Tokenize the World into Object-level Knowledge to Address Long-tail Events in Autonomous Driving

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-06T17:34:05.773718Z

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Observation c5880936-eb9f-4085-96fd-fd5919489692 · outbound

This paper cites Skill-critic: Refining learned skills for hierarchical reinforcement learn- ing,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Skill-critic: Refining learned skills for hierarchical reinforcement learn- ing,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:34:06.227789Z

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Observation fae155ae-ef69-4bca-8b48-c5a776bfb61d · outbound

This paper cites Residual skill policies: Learning an adaptable skill-based action space for reinforce- ment learning for robotics,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Residual skill policies: Learning an adaptable skill-based action space for reinforce- ment learning for robotics,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:34:06.220074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 4a30879b-f097-499d-9fee-2563d7150010 · outbound

This paper cites Risk- aware vehicle trajectory prediction under safety-critical scenarios,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Risk- aware vehicle trajectory prediction under safety-critical scenarios,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:34:06.212171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ec9061a5-6ad0-4418-9c28-ab5986897e48 · outbound

This paper cites SafeCritic: Collision-Aware Trajectory Prediction.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding SafeCritic: Collision-Aware Trajectory Prediction

Reference 44

Resolution: verified exact; local_arxiv, observed 2026-08-06T17:34:06.021346Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 6fccd787-7505-4f2f-8f60-8633d32a506c · outbound

This paper cites A comprehensive survey on contrastive learning,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding A comprehensive survey on contrastive learning,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:34:06.204501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 6baabbf6-3855-46bb-b6e9-ff5c5283ccdc · outbound

This paper cites A survey on self-supervised learning: Algorithms, applications, and future trends,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding A survey on self-supervised learning: Algorithms, applications, and future trends,

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-06T17:34:05.878962Z

Source-reported events for the cited work

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Observation 0cc27a94-c763-480c-a124-7f149bc04085 · outbound

This paper cites Fend: A future enhanced distribution-aware contrastive learning framework for long-tail trajectory prediction,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Fend: A future enhanced distribution-aware contrastive learning framework for long-tail trajectory prediction,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:34:06.192519Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 3f29b036-d0ba-43f7-a3a7-ef240738dbc2 · outbound

This paper cites Tract: A training dynamics aware contrastive learning framework for long-tail trajectory prediction,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Tract: A training dynamics aware contrastive learning framework for long-tail trajectory prediction,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:34:06.184955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 3fbecf84-837f-4169-aa58-11961e7f666d · outbound

This paper cites Lidp: Contrastive learning of latent indi- vidual driving pattern for trajectory prediction,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Lidp: Contrastive learning of latent indi- vidual driving pattern for trajectory prediction,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:34:06.176347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 94a7c6bd-e295-403a-8a4e-787225529ac3 · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Representation Learning with Contrastive Predictive Coding

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-06T17:34:05.888739Z

Source-reported events for the cited work

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Observation d5c6f7db-9918-4ead-a84d-33196fd8a290 · outbound

This paper cites Grounding dino: Marrying dino with grounded pre-training for open-set object detection,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Grounding dino: Marrying dino with grounded pre-training for open-set object detection,

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-06T17:34:05.891227Z

Source-reported events for the cited work

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Observation 319ce2d2-71ef-4c85-bb93-2640a605f35c · outbound

This paper cites SAM 2: Segment Anything in Images and Videos.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding SAM 2: Segment Anything in Images and Videos

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-06T17:34:05.893666Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 50d31a5a-4c8d-40ee-8540-9ec124bad984 · outbound

This paper cites Associate Everything Detected: Facilitating Tracking-by-Detection to the Unknown.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Associate Everything Detected: Facilitating Tracking-by-Detection to the Unknown

Reference 53

Resolution: verified exact; local_arxiv, observed 2026-08-06T17:34:05.994125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 57301b15-e9aa-40af-a8b6-bf4e0f5dbacc · outbound

This paper cites Xfeat: Accelerated features for lightweight image matching,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Xfeat: Accelerated features for lightweight image matching,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:34:06.163511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation cbf755bd-244e-428a-9b43-5c1a9085fb48 · outbound

This paper cites Unidepth: Universal monocular metric depth estimation,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Unidepth: Universal monocular metric depth estimation,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:34:06.155524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 98217f03-2f15-440f-9424-261dcd1fb3f8 · outbound

This paper cites Video Depth Anything: Consistent Depth Estimation for Super-Long Videos.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Video Depth Anything: Consistent Depth Estimation for Super-Long Videos

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-06T17:34:05.903479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 43e91ad0-1094-4094-90e8-9be11d58b814 · outbound

This paper cites Training an open-vocabulary monocular 3d detection model without 3d data,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Training an open-vocabulary monocular 3d detection model without 3d data,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:34:06.148359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation eb4713ae-78e0-476a-886b-aec0267b5a61 · outbound

This paper cites On exposing the challenging long tail in future prediction of traffic actors,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding On exposing the challenging long tail in future prediction of traffic actors,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:34:06.141466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d19c20bf-5b31-4cc7-89b2-561d70e3c43d · outbound

This paper cites On the effectiveness of adapter-based tuning for pretrained language model adaptation,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding On the effectiveness of adapter-based tuning for pretrained language model adaptation,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:34:06.134264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d3bd287b-246f-4302-82ab-37d7c445573d · outbound

This paper cites LoRA Dropout as a Sparsity Regularizer for Overfitting Control.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding LoRA Dropout as a Sparsity Regularizer for Overfitting Control

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-06T17:34:05.918085Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0fecd650-0cc6-4f49-8448-3fad28952c76 · outbound

This paper cites Lora: Low-rank adaptation of large language models.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Lora: Low-rank adaptation of large language models

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:34:06.127173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 819e5af6-ee68-4355-82ec-7d3c7c52f114 · outbound

This paper cites Metadrive: Composing diverse driving scenarios for generalizable reinforcement learning,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Metadrive: Composing diverse driving scenarios for generalizable reinforcement learning,

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-06T17:34:05.924242Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 08e9fbdc-98b7-43ec-a41f-5d13d0c8a399 · outbound

This paper cites Unitraj: A unified framework for scalable vehicle trajectory prediction,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Unitraj: A unified framework for scalable vehicle trajectory prediction,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:34:06.114809Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 1fb1ff51-4a4c-475c-8fee-122588781583 · outbound

This paper cites Sce- narionet: Open-source platform for large-scale traffic scenario simulation and modeling,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Sce- narionet: Open-source platform for large-scale traffic scenario simulation and modeling,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:34:06.105762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 234bd696-8f6c-4491-92e9-c6ba2d3b0ffe · outbound

This paper cites Relora: High-rank training through low-rank updates,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Relora: High-rank training through low-rank updates,

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:34:06.097538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c2452173-d1a0-41c3-9373-3c5b1b69cecf · outbound

This paper cites Densetnt: End-to-end trajectory prediction from dense goal sets,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Densetnt: End-to-end trajectory prediction from dense goal sets,

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-06T17:34:05.934186Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b60cdf28-6e43-43e6-bc08-9fac573f7334 · outbound

This paper cites UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-06T17:34:05.936456Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 468ba6e8-ea15-4718-bf1e-503db731774d · outbound

This paper cites Learning successor features the simple way,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Learning successor features the simple way,

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:34:06.084890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ac034108-431e-48f9-9403-38b0af5bc627 · outbound

This paper cites Clustering algorithms and validity measures,.

RCG: Safety-Critical Scenario Generation for Robust Autonomous Driving via Real-World Crash Grounding Clustering algorithms and validity measures,

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:34:06.076806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Reference resolution

Outbound references

Pith citing papers