Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-21T04:45:54.313310Z
Paper Citation Record · LEDGER
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training
As of 6 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 0 inbound Pith citation observations for arXiv:2605.21372.
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 2026-08-06T06:34:29.942622+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
53 of 53 outbound references displayed
- verified exact12
- verified fuzzy40
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch1
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 64265045-e14a-4678-bbde-a7fd3f8250be · outbound
This paper cites Scaling Laws of Motion Forecasting and Planning -- Technical Report.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training Scaling Laws of Motion Forecasting and Planning -- Technical Report
Reference 1
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T04:49:35.589839Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 85a84617-335c-45b5-933b-db4546a58b53 · outbound
This paper cites Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets
Reference 2
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T04:49:35.586707Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 3d31a965-4d60-44ed-8756-6fd343e8eddf · outbound
This paper cites Language models are few-shot learners.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training Language models are few-shot learners
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T09:44:58.136082Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 92f1fd2f-05a2-4cd0-a85e-54720df3b96b · outbound
This paper cites Pseudo-simulation for autonomous driving.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training Pseudo-simulation for autonomous driving
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T09:44:58.198209Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation bfe97b1f-0e11-4350-847c-8ff4fe1929b0 · outbound
This paper cites End-to-end autonomous driving: Challenges and frontiers.IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI).
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training End-to-end autonomous driving: Challenges and frontiers.IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T09:44:58.192847Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation b50e2bee-f3b9-4629-a143-8038b1ad4d02 · outbound
This paper cites A simple framework for contrastive learning of visual representations.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training A simple framework for contrastive learning of visual representations
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T09:44:58.157947Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 802b3247-0831-4a39-ac6e-9550f0745826 · outbound
This paper cites Transfuser: Imitation with transformer-based sensor fusion for autonomous driving.IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI).
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training Transfuser: Imitation with transformer-based sensor fusion for autonomous driving.IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T09:44:58.200756Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation a0d78aa3-b7da-4797-9727-ecb25241d706 · outbound
This paper cites Navsim: Data-driven non-reactive autonomous vehicle simulation and benchmarking.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training Navsim: Data-driven non-reactive autonomous vehicle simulation and benchmarking
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T09:44:58.244931Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 35b183bd-e7bf-431f-8f41-c62f7f667bc1 · outbound
This paper cites Nemotron-climb: Clustering-based iterative data mixture bootstrapping for language model pre-training.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training Nemotron-climb: Clustering-based iterative data mixture bootstrapping for language model pre-training
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T09:44:58.173945Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation d663c0d7-b87d-4e7b-a32c-7d2d225413d5 · outbound
This paper cites Realgen: Retrieval augmented generation for controllable traffic scenarios.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training Realgen: Retrieval augmented generation for controllable traffic scenarios
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T09:44:58.189998Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 918dbd34-5c53-4471-af1d-96448978b5d2 · outbound
This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training An image is worth 16x16 words: Transformers for image recognition at scale
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T09:44:58.195633Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 650b894e-c551-4600-97a5-875b93f8299e · outbound
This paper cites Doge: Domain reweighting with generalization estimation.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training Doge: Domain reweighting with generalization estimation
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T09:44:58.179817Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 91dc94ab-6df6-4a29-90b6-0ce87f7dfbaa · outbound
This paper cites Magicdrive- v2: High-resolution long video generation for autonomous driving with adaptive control.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training Magicdrive- v2: High-resolution long video generation for autonomous driving with adaptive control
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T09:44:58.166685Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 1b3a00b7-6264-4aa5-b79f-75b46766217b · outbound
This paper cites MagicDrive: Street view generation with diverse 3d geometry control.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training MagicDrive: Street view generation with diverse 3d geometry control
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T09:44:58.187741Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 831c8813-926b-48fd-a1b5-220159d8fa8e · outbound
This paper cites Vista: A generalizable driving world model with high fidelity and versatile controllability.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training Vista: A generalizable driving world model with high fidelity and versatile controllability
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T09:44:58.203050Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation ac98dc40-3101-4620-8cc6-58d023626ed5 · outbound
This paper cites Road: Rollouts as demonstrations for closed-loop supervised fine-tuning of autonomous driving policies.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training Road: Rollouts as demonstrations for closed-loop supervised fine-tuning of autonomous driving policies
Reference 16
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T04:49:35.572172Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 20f3db34-3468-4b24-a7ac-871a49901ea9 · outbound
This paper cites Unraveling the effects of synthetic data on end-to-end autonomous driving.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training Unraveling the effects of synthetic data on end-to-end autonomous driving
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T09:44:58.238890Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 99ba222a-7431-42d2-b400-953905d5c8e4 · outbound
This paper cites Deep residual learning for image recognition.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training Deep residual learning for image recognition
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T09:44:58.151875Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 9fc23e7a-059d-40be-beed-eaf725f95173 · outbound
This paper cites GAIA-1: A Generative World Model for Autonomous Driving.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training GAIA-1: A Generative World Model for Autonomous Driving
Reference 19
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T04:49:35.577799Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation b31e1256-0573-4b69-9764-073f9c200712 · outbound
This paper cites Planning-oriented autonomous driving.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training Planning-oriented autonomous driving
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T09:44:58.221544Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation f1acb195-7585-4296-bcf1-bda06bb9c7e5 · outbound
This paper cites Étude comparative de la distribution florale dans une portion des alpes et des jura.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training Étude comparative de la distribution florale dans une portion des alpes et des jura
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T09:44:58.235912Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 1eccb2dd-1cdc-4d4f-bd87-de732888a67d · outbound
This paper cites Vad: Vectorized scene representation for efficient autonomous driving.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training Vad: Vectorized scene representation for efficient autonomous driving
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T09:44:58.148636Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 502f7406-2098-4c48-9adc-f2d2c4499225 · outbound
This paper cites Scaling Laws for Neural Language Models.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training Scaling Laws for Neural Language Models
Reference 23
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T04:49:35.583776Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation f46085e8-6b58-47b2-a0be-80f89e3da013 · outbound
This paper cites 3d gaussian splatting for real-time radiance field rendering.ACM Transactions on Graphics (ToG).
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training 3d gaussian splatting for real-time radiance field rendering.ACM Transactions on Graphics (ToG)
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T09:44:58.215303Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 54b9e7e9-afb2-4c8f-9ac4-f755600f0f48 · outbound
This paper cites Supervised contrastive learning.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training Supervised contrastive learning
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T09:44:58.133148Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 4351f408-3d61-4eb7-b346-64ab84b95c7a · outbound
This paper cites Adam: a method for stochastic optimization.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training Adam: a method for stochastic optimization
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T09:44:58.226884Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 23620f23-7f46-418b-bff4-f7d5c9d7a9aa · outbound
This paper cites MTGS: Multi-Traversal Gaussian Splatting.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training MTGS: Multi-Traversal Gaussian Splatting
Reference 27
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T04:49:35.580853Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation fc0d95d1-e342-4a7a-b848-0998ea54d11c · outbound
This paper cites Recogdrive: A reinforced cognitive framework for end-to-end autonomous driving.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training Recogdrive: A reinforced cognitive framework for end-to-end autonomous driving
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T09:44:58.209314Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation d7100caf-b645-413a-a1df-46e7d48259ec · outbound
This paper cites Diffusiondrive: Truncated diffusion model for end-to-end autonomous driving.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training Diffusiondrive: Truncated diffusion model for end-to-end autonomous driving
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T09:44:58.248252Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 5a65fd01-bf28-4643-b22e-f85d1bb9314b · outbound
This paper cites Model-based policy adaptation for closed-loop end-to-end autonomous driving.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training Model-based policy adaptation for closed-loop end-to-end autonomous driving
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T09:44:58.145505Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 2fdd2f68-9f97-4b03-8ee5-9d41b8e39912 · outbound
This paper cites Regmix: Data mixture as regression for language model pre-training.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training Regmix: Data mixture as regression for language model pre-training
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T09:44:58.212247Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation cb9950c1-4fc4-4c60-876a-4072868dc554 · outbound
This paper cites Decoupled weight decay regularization.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training Decoupled weight decay regularization
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T09:44:58.232568Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 3e3bc285-494d-4540-bf29-3613fbf07669 · outbound
This paper cites Unleashing Generalization of End-to-End Autonomous Driving with Controllable Long Video Generation.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training Unleashing Generalization of End-to-End Autonomous Driving with Controllable Long Video Generation
Reference 33
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T04:49:35.575214Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation c6d96e05-f3a8-4099-9a5e-8ba870172a86 · outbound
This paper cites Sim-and-real co-training: A simple recipe for vision-based robotic manipulation.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training Sim-and-real co-training: A simple recipe for vision-based robotic manipulation
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T09:44:58.206354Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 6c61a8e2-5b97-4fb9-b30c-b50150b157fd · outbound
This paper cites Robocasa: Large-scale simulation of everyday tasks for generalist robots.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training Robocasa: Large-scale simulation of everyday tasks for generalist robots
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T09:44:58.155001Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 82159065-d40a-46f9-b1fa-f1db11e60d8c · outbound
This paper cites GR00T N1: An Open Foundation Model for Generalist Humanoid Robots.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training GR00T N1: An Open Foundation Model for Generalist Humanoid Robots
Reference 36
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T04:49:35.562547Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 7ba7ee51-f5c9-46b0-b31f-f393a1971a17 · outbound
This paper cites Learning transferable visual models from natural language supervision.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training Learning transferable visual models from natural language supervision
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T09:44:58.241866Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation ccd65f61-3722-44d9-9a76-3dedc2d74859 · outbound
This paper cites Cosmos-Drive-Dreams: Scalable Synthetic Driving Data Generation with World Foundation Models.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training Cosmos-Drive-Dreams: Scalable Synthetic Driving Data Generation with World Foundation Models
Reference 38
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-21T04:49:35.592880Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 6e96e01d-d43a-44c8-96e5-4ca05cd6950e · outbound
This paper cites Sparsedrive: End-to-end autonomous driving via sparse scene representation.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training Sparsedrive: End-to-end autonomous driving via sparse scene representation
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T09:44:58.160501Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 3cb7f739-3359-4fd9-aa91-9b64e558862e · outbound
This paper cites Gigaworld-0: World models as data engine to empower embodied ai.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training Gigaworld-0: World models as data engine to empower embodied ai
Reference 40
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T04:49:35.566382Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation a7a31758-487e-4a74-a732-be44192c53a9 · outbound
This paper cites Simscale: Learning to drive via real-world simulation at scale.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training Simscale: Learning to drive via real-world simulation at scale
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T09:44:58.251569Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation fdcb70e7-5771-4b97-b1f9-98fbcd699b4a · outbound
This paper cites Interndata-a1: Pioneering high-fidelity synthetic data for pre-training generalist policy.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training Interndata-a1: Pioneering high-fidelity synthetic data for pre-training generalist policy
Reference 42
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T04:49:35.559632Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 4ddf4e6a-35cb-4d02-a127-028050dce3f7 · outbound
This paper cites LLaMA: Open and Efficient Foundation Language Models.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training LLaMA: Open and Efficient Foundation Language Models
Reference 43
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T04:49:35.556167Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation fd94d73f-081f-4ec1-843b-c5de2ef15986 · outbound
This paper cites Attention is all you need.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training Attention is all you need
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T09:44:58.163515Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 2e0640ad-43d1-4cbc-9938-6ccd8543a8c5 · outbound
This paper cites Drive- dreamer: Towards real-world-drive world models for autonomous driving.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training Drive- dreamer: Towards real-world-drive world models for autonomous driving
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T09:44:58.182554Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 79825f66-b709-401c-bda8-bab802815dcc · outbound
This paper cites Panacea: Panoramic and controllable video generation for autonomous driving.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training Panacea: Panoramic and controllable video generation for autonomous driving
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T09:44:58.224249Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 1423d0cf-daea-4ea1-8ed7-f3c55f847fc3 · outbound
This paper cites Data retrieval with importance weights for few-shot imitation learning.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training Data retrieval with importance weights for few-shot imitation learning
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T09:44:58.185347Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation da1819d7-a96e-48a2-8798-3eab6662dcba · outbound
This paper cites Doremi: Optimizing data mixtures speeds up language model pretraining.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training Doremi: Optimizing data mixtures speeds up language model pretraining
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T09:44:58.218260Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 229af693-a085-4e49-8d45-f1ed47266e90 · outbound
This paper cites Chameleon: A flexible data-mixing framework for language model pretraining and finetuning.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training Chameleon: A flexible data-mixing framework for language model pretraining and finetuning
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T09:44:58.176961Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation bd88e4db-9a8b-42a9-8e47-a64e9522e3c9 · outbound
This paper cites Goalflow: Goal-driven flow matching for multimodal trajectories generation in end-to-end autonomous driving.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training Goalflow: Goal-driven flow matching for multimodal trajectories generation in end-to-end autonomous driving
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T09:44:58.170046Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 2907162d-144d-40a3-bce9-f94e38b556ee · outbound
This paper cites Data mixing laws: Optimizing data mixtures by predicting language modeling performance.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training Data mixing laws: Optimizing data mixtures by predicting language modeling performance
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T09:44:58.229526Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 5d93bb34-6e75-4fce-875f-c343aa133110 · outbound
This paper cites Diffusion-based planning for autonomous driving with flexible guidance.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training Diffusion-based planning for autonomous driving with flexible guidance
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T09:44:58.129967Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation e9adbb1b-2400-4bca-9e57-1e0f07628536 · outbound
This paper cites Data scaling laws for imitation learning-based end-to-end autonomous driving.
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training Data scaling laws for imitation learning-based end-to-end autonomous driving
Reference 53
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T04:49:35.569293Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Pith citing papers
No inbound Pith citation observations are available.