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Paper Citation Record · LEDGER

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case

As of 17 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 1 inbound Pith citation observation for arXiv:2508.04642.

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

pith.paper-citation-record.v1
2508.04642 v1

Coverage vector

measured 48 of 48 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T23:53:50.298671Z

measured 49 of 49 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T08:57:15.573913Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

48 of 48 outbound references displayed

  • verified exact2
  • verified fuzzy29
  • unresolved17
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4c1cdc81-27de-4493-b2b5-04650ec04480 · outbound

This paper cites Planning-oriented au- tonomous driving,.

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case Planning-oriented au- tonomous driving,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:53:59.248469Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-05T23:53:44.166589Z digest=sha256:1382074daaa5707247681f76967a937a55d00843706da915b2b23685d8c8f63b

Observation c3e4872d-09c7-48fb-9dfb-9fd480606a35 · outbound

This paper cites Rethinking the Open-Loop Evaluation of End-to-End Autonomous Driving in nuScenes.

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case Rethinking the Open-Loop Evaluation of End-to-End Autonomous Driving in nuScenes

Reference 2

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unresolved
no resolver link, observed 2026-08-05T23:53:44.251428Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T23:53:44.251428Z digest=sha256:ad21dc752d754df05d6f2d8f5e5ae4ac12f53063fe89236f7b54ad8e3d22b97f

Observation ced822f1-deb0-4a35-9fe0-5dfc4c41d92c · outbound

This paper cites Is ego status all you need for open-loop end-to-end au- tonomous driving?.

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case Is ego status all you need for open-loop end-to-end au- tonomous driving?

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:53:58.839800Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-05T23:53:44.356862Z digest=sha256:0fd3dbd1e3d5258d196f4552b8fb3211ea1985647bb3f72f8670bdff56deb897

Observation e9f6ab17-4453-40cc-9847-fa747a5803cc · outbound

This paper cites EMMA: End-to-End Multimodal Model for Autonomous Driving.

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case EMMA: End-to-End Multimodal Model for Autonomous Driving

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-05T23:53:44.445075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T23:53:44.445075Z digest=sha256:675bf3d090d3a39f8fca14d8dc4b9791acb6d1154c4391beec3be8b5c3f823af

Observation 5f29f085-1695-4681-a35a-5484ca269ce9 · outbound

This paper cites Visual instruction tuning,.

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case Visual instruction tuning,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:53:58.611283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-05T23:53:44.519433Z digest=sha256:c514d5a081a9232517cfc3a47258b157d7feeba72db72581a6d3ae2a33df927c

Observation 87647c5d-e949-48da-9307-0dfb9e9b4099 · outbound

This paper cites Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality, march 2023,.

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality, march 2023,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:53:58.436500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-05T23:53:44.580609Z digest=sha256:2a0336f62531c2aaefffc3be0863fe98e1e62dc8c766bcf506232603db08e5b9

Observation 7d933895-8da9-42e4-9716-7004763d702d · outbound

This paper cites Merlin: Empowering mul- timodal llms with foresight minds,.

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case Merlin: Empowering mul- timodal llms with foresight minds,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:53:58.150099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-05T23:53:44.678531Z digest=sha256:a17238e6ea383a49aea88ec7f42663d68971de5842d68af0955b44592a160cba

Observation bd2a675b-6f7d-451d-929b-2794b41746fb · outbound

This paper cites Think2drive: Efficient reinforcement learning by thinking with latent world model for autonomous driving (in carla-v2),.

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case Think2drive: Efficient reinforcement learning by thinking with latent world model for autonomous driving (in carla-v2),

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:53:57.868905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-05T23:53:44.768369Z digest=sha256:14cecf5b12e4e1cb7cd6f21bdc2c6947a051189655fd519ec9a82bad4e4d61b0

Observation b4cd62eb-68d1-4bfd-b57b-22ba6b55a59a · outbound

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

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case nuscenes: A multimodal dataset for autonomous driving,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:53:57.562127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-05T23:53:44.899805Z digest=sha256:2addbceb205a0bd12effb0a8c082377ea666d24975612f1f1e165c18df3757f9

Observation c1b3f1a3-3275-47fc-8d0e-ec2f9d91f36f · outbound

This paper cites Carla: An open urban driving simulator,.

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case Carla: An open urban driving simulator,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:53:57.211540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-05T23:53:45.004491Z digest=sha256:9310c23e2ba04c6a5c6ee852ed6a3cfb948da1c2297610668c4345d9d8e710ca

Observation 5d650794-b1ea-4a93-9487-b7be01e5ee0a · outbound

This paper cites Airsim: High- fidelity visual and physical simulation for autonomous ve- hicles,.

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case Airsim: High- fidelity visual and physical simulation for autonomous ve- hicles,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:53:56.899146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-05T23:53:45.140276Z digest=sha256:49188685bb8f009e41ac7d6f87493ae4947b54c3499bb94a39382f08697c3983

Observation 0fe0ba79-0c34-40df-a3ec-7a6e5e5feaa6 · outbound

This paper cites Making large language models better plan- ners with reasoning-decision alignment,.

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case Making large language models better plan- ners with reasoning-decision alignment,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:53:56.623308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-05T23:53:45.215671Z digest=sha256:cb5d06763644b0cac76dc6cb5f00ffe9cc0bcedf3320d837d91ffb1bd46740ee

Observation 1cea3738-c250-4693-9ea0-2c3376da046a · outbound

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

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case Senna: Bridging Large Vision-Language Models and End-to-End Autonomous Driving

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-05T23:53:45.292650Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T23:53:45.292650Z digest=sha256:1ca8fc637074d62b02d592cd21aac22fa73a47529c105d484ea668b1a78956cd

Observation bce6a1bc-8038-4597-ad2f-b91a728597ec · outbound

This paper cites LLaVA-OneVision: Easy Visual Task Transfer.

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case LLaVA-OneVision: Easy Visual Task Transfer

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-05T23:53:45.418885Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T23:53:45.418885Z digest=sha256:c58d436e4c150088c98f31c99c87458496d79bb4bd5d37932fd93a9bb7391d88

Observation 90c76992-5bf4-4887-b4b3-6d43bd02fd41 · outbound

This paper cites Automated Evaluation of Large Vision-Language Models on Self-driving Corner Cases.

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case Automated Evaluation of Large Vision-Language Models on Self-driving Corner Cases

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-05T23:53:45.537163Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T23:53:45.537163Z digest=sha256:5c50aab34e4d990b9b89cf5f9d285de8ee4f2b055a1947ec712e8abe6ea7246d

Observation 292da29f-7a89-43e1-a3b1-34ebbdf707f2 · outbound

This paper cites Lingoqa: Video question answering for autonomous driving,.

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case Lingoqa: Video question answering for autonomous driving,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:53:56.245424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-05T23:53:45.626586Z digest=sha256:02ca7700449d81ac6a470b4030ff06922441cb4c981fa6fd82a6a74ffe21c032

Observation 494b5508-fe05-42b7-b899-4f6da59e0612 · outbound

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

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case Holistic autonomous driving understanding by bird’s-eye- view injected multi-modal large models,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:53:55.933532Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-05T23:53:45.695465Z digest=sha256:f80da6e68b0a8db5eb51187b9bf22521f2952510fad238663e6da0edc0f5e499

Observation 2f536079-ee31-47b8-996d-0d9c331b99bb · outbound

This paper cites DriveVLM: The Convergence of Autonomous Driving and Large Vision-Language Models.

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case DriveVLM: The Convergence of Autonomous Driving and Large Vision-Language Models

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-05T23:53:45.786781Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T23:53:45.786781Z digest=sha256:df719f993a9e5abedb316409ba614e035fb4631bed8efa8322ebfc2b3860693d

Observation 4819e3fb-d6a5-42ce-ad06-aca740220228 · outbound

This paper cites GPT-4 Technical Report.

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case GPT-4 Technical Report

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-05T23:53:45.885509Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T23:53:45.885509Z digest=sha256:d06c18b547d7a601c918242e50d1ee1dbe6020d84bd4e99bc1b02c06c4ccb494

Observation 867393f6-fc0a-4c86-beed-f3381304e50d · outbound

This paper cites DiLu: A Knowledge-Driven Approach to Autonomous Driving with Large Language Models.

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case DiLu: A Knowledge-Driven Approach to Autonomous Driving with Large Language Models

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-05T23:53:45.998341Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T23:53:45.998341Z digest=sha256:bf74f0c01a74ae57e994af285010c43163a5b7f231388bfcde9dbd6d768b6fa5

Observation fcf468f2-5788-45e6-b40d-c93423f75316 · outbound

This paper cites Drivegpt4: Interpretable end-to-end au- tonomous driving via large language model,.

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case Drivegpt4: Interpretable end-to-end au- tonomous driving via large language model,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:53:55.572259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-05T23:53:46.101313Z digest=sha256:0348f32b0d4e8d43b06acc76c1c4a6177ddce309e0422f30e0ad3e8099f28623

Observation 82eb03e6-ebab-43fd-a647-cf03b03f6407 · outbound

This paper cites Making large language models better plan- ners with reasoning-decision alignment,.

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case Making large language models better plan- ners with reasoning-decision alignment,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:53:55.311600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-05T23:53:46.178666Z digest=sha256:d0a405cc420c28ed321e1c78e12c3b05cc54441e2c515626d47649ca14fa003f

Observation 34b840db-d822-4cfb-b81c-782b13c8147d · outbound

This paper cites Drive as you speak: Enabling human-like interaction with large lan- guage models in autonomous vehicles,.

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case Drive as you speak: Enabling human-like interaction with large lan- guage models in autonomous vehicles,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:53:55.046626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-05T23:53:46.289714Z digest=sha256:30f2eeee179737bce3b72949609e59b0bd9e943a2b8db824f36ad6b5bcd6aaec

Observation a7b947dd-d6a9-4424-bdc5-866108c1fb6c · outbound

This paper cites Lmdrive: Closed-loop end-to-end driving with large language models,.

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case Lmdrive: Closed-loop end-to-end driving with large language models,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:53:54.772729Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-05T23:53:46.388058Z digest=sha256:9d83c89605e7a05a1c9152e44dea1c30a65bf213ebf026df8bafb6404971c42d

Observation 4d5d7f2f-0c08-4c91-b5b8-d1dcc5433595 · outbound

This paper cites OmniDrive: A Holistic Vision-Language Dataset for Autonomous Driving with Counterfactual Reasoning.

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case OmniDrive: A Holistic Vision-Language Dataset for Autonomous Driving with Counterfactual Reasoning

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-05T23:53:46.525390Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T23:53:46.525390Z digest=sha256:ad973da0ef2f6b4212db53c0ae976148ba1196c7ff8952c0989565d19ba8a933

Observation 344d48c3-61e6-4310-8d81-938fb911dccb · outbound

This paper cites Visual instruction tuning,.

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case Visual instruction tuning,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:53:54.471860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-05T23:53:46.607425Z digest=sha256:e357f0f838b1d4b69b9ff3eb365cc5c58467b8d500de86d23f20ea68844ca20b

Observation 5d5f48f5-5d35-406e-9323-4f7d7ad12f4b · outbound

This paper cites End-to-end autonomous driving: Challenges and frontiers,.

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case End-to-end autonomous driving: Challenges and frontiers,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:53:54.204256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-05T23:53:46.842795Z digest=sha256:e2f6b60b9d2460086c7fabe9fbe4684483b67996a0aba21952c53d55c131a704

Observation a027ce57-120f-4235-84cc-de564df00ea1 · outbound

This paper cites A Survey on the Memory Mechanism of Large Language Model based Agents.

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case A Survey on the Memory Mechanism of Large Language Model based Agents

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-05T23:53:46.933179Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T23:53:46.933179Z digest=sha256:2243d57f87241e39907851f06f1acf6f7d9d14b3ddf54d5723f320bcfb1d27aa

Observation 88cad292-3c52-48c7-88d1-db4317f7fcbd · outbound

This paper cites BEVDet: High-performance Multi-camera 3D Object Detection in Bird-Eye-View.

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case BEVDet: High-performance Multi-camera 3D Object Detection in Bird-Eye-View

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-05T23:53:47.055162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T23:53:47.055162Z digest=sha256:4268d325a691247e47c4d706f743a9285e1ca761a18704f1d04eecd611352bb7

Observation 67465283-c802-413e-a93c-081fbd044f29 · outbound

This paper cites Bevfusion: A simple and robust lidar-camera fusion framework,.

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case Bevfusion: A simple and robust lidar-camera fusion framework,

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:53:53.891873Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-05T23:53:47.225647Z digest=sha256:971e0bb603c115c25d16e909e0d44c0e3db20db60c3d90728b3f07478fcd61eb

Observation cb797b2c-23c1-4171-82a6-3f970baad93b · outbound

This paper cites Bevfusion: Multi-task multi-sensor fusion with unified bird’s-eye view representation,.

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case Bevfusion: Multi-task multi-sensor fusion with unified bird’s-eye view representation,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:53:53.564910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-05T23:53:47.302704Z digest=sha256:0baf20e2629369ebf3c1f54892cfaee1a629f1adcad0b6ce5811003461cacbe6

Observation 9dceddf8-d034-4899-ae11-a6d11c3946da · outbound

This paper cites Vip3d: End-to-end visual trajectory prediction via 3d agent queries,.

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case Vip3d: End-to-end visual trajectory prediction via 3d agent queries,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:53:53.282348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-05T23:53:47.490386Z digest=sha256:ef8c5d62d7c1e9955a5e40302d1b1a4077b17c6d8430d3d80bc463a51eea6acc

Observation 70a45760-9b3a-4aa9-b8be-8aa4892bbe45 · outbound

This paper cites Vectornet: Encoding hd maps and agent dy- namics from vectorized representation,.

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case Vectornet: Encoding hd maps and agent dy- namics from vectorized representation,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:53:52.946298Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-05T23:53:47.623102Z digest=sha256:85dc1439483015d89222ac675469ca5bfad466915265d3c0683b7234c070ea73

Observation 726614ef-24fe-4760-a18d-17556c30dcf1 · outbound

This paper cites Path-aware graph attention for hd maps in motion prediction,.

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case Path-aware graph attention for hd maps in motion prediction,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:53:52.717253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-05T23:53:47.713372Z digest=sha256:35637e1a77d71805e4e2e836537cd4b57f383d523e79ce03bc13e4dada43cda4

Observation 74b53e03-d69c-4ad1-80eb-e092cdb0d689 · outbound

This paper cites Urban driver: Learning to drive from real-world demonstrations using policy gradients,.

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case Urban driver: Learning to drive from real-world demonstrations using policy gradients,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:53:52.520965Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-05T23:53:47.878592Z digest=sha256:fa5cebbcb9829527f3d85c8c02cdd8da801d329e7b4f06ac3476b6a0c8371750

Observation 38411c33-b4fa-4fc8-9410-4c81fb7a3625 · outbound

This paper cites Perceive, predict, and plan: Safe motion planning through interpretable semantic representations,.

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case Perceive, predict, and plan: Safe motion planning through interpretable semantic representations,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:53:52.348506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-05T23:53:48.092138Z digest=sha256:aa5e40a8da0595086b614a8318a1b58dc4f8f07fe678ce5faadd5b646087e83d

Observation e0fd823c-39f4-419f-bac1-4b2300a0347e · outbound

This paper cites Cola-hrl: Continuous-lattice hier- archical reinforcement learning for autonomous driving,.

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case Cola-hrl: Continuous-lattice hier- archical reinforcement learning for autonomous driving,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:53:52.191730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-05T23:53:48.282822Z digest=sha256:8d6ddca1058b6791fdb769d0686fdd5faa53a63dc9ed5537752487f4700908d6

Observation f69a4da0-bba4-4e19-8403-c3556fbe9f7e · outbound

This paper cites LLM4Drive: A Survey of Large Language Models for Autonomous Driving.

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case LLM4Drive: A Survey of Large Language Models for Autonomous Driving

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-05T23:53:48.447263Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T23:53:48.447263Z digest=sha256:5403224ed4296b23f10bd82d9289962a41c97f1cdf162c1180936a9e6245aee2

Observation 9299c620-fd67-4f25-835d-8086da1a0d6c · outbound

This paper cites Language models are few-shot learners,.

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case Language models are few-shot learners,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:53:52.044596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-05T23:53:48.584638Z digest=sha256:3407e89039396ebbc42a6f607881c9a3b70acf7ba1a6ed607bd53509ebeaaa79

Observation 37082156-d4c0-49b7-8267-d1e511c76af4 · outbound

This paper cites Policy Pre-training for Autonomous Driving via Self-supervised Geometric Modeling.

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case Policy Pre-training for Autonomous Driving via Self-supervised Geometric Modeling

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-05T23:53:48.817246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T23:53:48.817246Z digest=sha256:d485a6568bc904236299db62ad8678d7e8c63e7a88d5a78e5b487b1f405d555b

Observation 5f6f3fb6-c938-4dcf-afd3-63efdd5869d9 · outbound

This paper cites Bench2Drive: Towards Multi-Ability Benchmarking of Closed-Loop End-To-End Autonomous Driving.

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case Bench2Drive: Towards Multi-Ability Benchmarking of Closed-Loop End-To-End Autonomous Driving

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-05T23:53:48.972778Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T23:53:48.972778Z digest=sha256:c5e86338c5da3b4541c4af4ae4a076cf1d37be81d55d0c9c20d5557d2b14e837

Observation b211b623-e206-4a07-8524-61c948e0670f · outbound

This paper cites OASIS: Open Agent Social Interaction Simulations with One Million Agents.

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case OASIS: Open Agent Social Interaction Simulations with One Million Agents

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-05T23:53:49.158851Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T23:53:49.158851Z digest=sha256:73f830ec7b151ae844fc52c2ac3e0c96a26702fd60940a2710732b3570a363b4

Observation 37c3a982-e2da-45dc-9610-51063a106874 · outbound

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

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case Scalability in perception for autonomous driving: Waymo open dataset,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:53:51.830385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-05T23:53:49.401287Z digest=sha256:bc2ad459f8d45438d724b955af67d105f9619b0351334a2dd36926093ee5532e

Observation 3532a42c-d570-4e04-9820-7c5df52a2464 · outbound

This paper cites Autonomy 2.0: Why is self-driving always 5 years away?.

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case Autonomy 2.0: Why is self-driving always 5 years away?

Reference 45

Resolution
verified exact
local_arxiv, observed 2026-08-05T23:53:51.163976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-05T23:53:49.558379Z digest=sha256:7760add7711442608320a2552248c095d53692287d0f87f523ee211fadf87e02

Observation 0881fcfb-0257-4341-8aad-59062318f83f · outbound

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

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case RoboTron-Drive: All-in-One Large Multimodal Model for Autonomous Driving

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-05T23:53:49.792907Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T23:53:49.792907Z digest=sha256:bd6995c6724d412ade857a5c76ff3987dc30e7edda000cbefebc45f0de08df11

Observation d8c4f036-59b1-4a82-9cf2-43815e21976b · outbound

This paper cites Robomm: All-in-one multimodal large model for robotic manipulation,.

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case Robomm: All-in-one multimodal large model for robotic manipulation,

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-05T23:53:49.998116Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T23:53:49.998116Z digest=sha256:1909411ce70b756e95e4c5baf3027a9d418b1d2b524b37ee2c4125021271abca

Observation 90ee8e54-264e-4193-b5a1-37eecc5ea06d · outbound

This paper cites RoboTron-Nav: A Unified Framework for Embodied Navigation Integrating Perception, Planning, and Prediction.

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case RoboTron-Nav: A Unified Framework for Embodied Navigation Integrating Perception, Planning, and Prediction

Reference 48

Resolution
verified exact
local_arxiv, observed 2026-08-05T23:53:50.696946Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-05T23:53:50.148533Z digest=sha256:ebb458809051de4818c95a359af08d0d2c4e43870c0d6839aaa685656f7c2336

Observation c2052511-165a-4ab1-9ea3-3c8d3561e27b · outbound

This paper cites Vad: Vector- ized scene representation for efficient autonomous driving,.

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case Vad: Vector- ized scene representation for efficient autonomous driving,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:53:51.556756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-05T23:53:50.298671Z digest=sha256:318dd23e503d69408364da5b529793148032553e37c8333f8bd564b259cb7c8c

Pith citing papers

Observation 42883488-ebd0-4d8d-b93b-bd70511f5131 · inbound

OmniNWM: Omniscient Driving Navigation World Models cites this paper.

OmniNWM: Omniscient Driving Navigation World Models RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case

Reference 87

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unresolved
no resolver link, observed 2026-08-04T08:57:15.573913Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:57:15.573913Z digest=sha256:92300ad766376293c421d0026f1963150b799628a44f472a61312c51b49043af