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Paper Citation Record · LEDGER

CaRL: Learning Scalable Planning Policies with Simple Rewards

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2504.17838.

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

pith.paper-citation-record.v1
2504.17838 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T15:45:50.027870Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T13:59:52.270237Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 3d9169d7-3c53-4a64-88db-feb5ee5545d1 · inbound

End-to-End Crop Row Navigation via LiDAR-Based Deep Reinforcement Learning cites this paper.

End-to-End Crop Row Navigation via LiDAR-Based Deep Reinforcement Learning CaRL: Learning Scalable Planning Policies with Simple Rewards

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-04T15:45:50.027870Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T15:45:50.027870Z digest=sha256:d713035d120c1bb974864b25c1e2a79edf2a155155d54675c444666c34864aaa

Observation a6d06704-b62d-4783-bba3-83f3ecb3e0eb · inbound

Zero-Human Demonstration End-to-end Autonomous Driving with Trajectory Scorer cites this paper.

Zero-Human Demonstration End-to-end Autonomous Driving with Trajectory Scorer CaRL: Learning Scalable Planning Policies with Simple Rewards

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-04T07:54:31.437962Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T07:54:31.437962Z digest=sha256:c38c28ba6682b1d59a57686c423f74f7709cb33e102e529decf9240168b653ad

Observation 7f28dc87-b3fd-4a13-b102-b31572796698 · inbound

Goal-Oriented Reactive Simulation for Closed-Loop Trajectory Prediction cites this paper.

Goal-Oriented Reactive Simulation for Closed-Loop Trajectory Prediction CaRL: Learning Scalable Planning Policies with Simple Rewards

Reference 23

Resolution
metadata mismatch
arxiv_id, observed 2026-05-15T00:58:26.219951Z

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.

source=pdf_text observed=2026-05-15T00:55:01.446865Z digest=sha256:ba4b55cacac2cace429af474799c05516bd2ca67357ab9c5d83d90c6729fd673

Observation ec35f504-c895-4d74-a3db-f860c52472a3 · inbound

Learning Dexterous Grasping from Sparse Taxonomy Guidance cites this paper.

Learning Dexterous Grasping from Sparse Taxonomy Guidance CaRL: Learning Scalable Planning Policies with Simple Rewards

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-13T17:08:00.975998Z

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.

source=pdf_text observed=2026-05-13T17:05:06.300013Z digest=sha256:28b57932051eacc34667a69d464f8d8dde8f5827b07b91910d43f18e45b1e147

Observation 13fe5e58-3f3d-4f22-b7b3-69418b13313e · inbound

On Data Thinning for Model Validation in Small Area Estimation cites this paper.

On Data Thinning for Model Validation in Small Area Estimation CaRL: Learning Scalable Planning Policies with Simple Rewards

Reference 24

Resolution
unresolved
no resolver link, observed 2026-07-13T11:14:37.619203Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T11:14:37.619203Z digest=sha256:69f5b10354d9495a8ca6426d340967c4e42927dcd0323f6a1564f35e9d918b09

Observation 9b6d7338-4464-4b64-8677-b4786c7c01b3 · inbound

Fail2Drive: Benchmarking Closed-Loop Driving Generalization cites this paper.

Fail2Drive: Benchmarking Closed-Loop Driving Generalization CaRL: Learning Scalable Planning Policies with Simple Rewards

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-11T07:06:00.592800Z

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.

source=pdf_text observed=2026-05-10T17:19:01.704384Z digest=sha256:62e7778d9462c894e83a1712e7b31dd0b26bd1517571d87601de22bbed5e5701

Observation 9d25453d-cff1-442c-88d1-99b20e707ad9 · inbound

Beyond Self-Play and Scale: A Behavior Benchmark for Generalization in Autonomous Driving cites this paper.

Beyond Self-Play and Scale: A Behavior Benchmark for Generalization in Autonomous Driving CaRL: Learning Scalable Planning Policies with Simple Rewards

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-05-12T07:16:30.361471Z

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.

source=pdf_text observed=2026-05-12T03:31:25.453515Z digest=sha256:544f1272b42afb1bc76d3ecc6653125fb16c79c257b7c4fc0f8a5aee610a7977

Observation 813d3636-a4bb-4489-ae9d-6ceeb22c4fbb · inbound

MAPLE: Latent Multi-Agent Play for End-to-End Autonomous Driving cites this paper.

MAPLE: Latent Multi-Agent Play for End-to-End Autonomous Driving CaRL: Learning Scalable Planning Policies with Simple Rewards

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-15T04:45:01.098432Z

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.

source=pdf_text observed=2026-05-15T04:41:07.402168Z digest=sha256:9cf75ffc6834c05bc00bb16b7f708292ed8dcfede4cb1839f4ba18ed1a033fe7

Observation e01fa9b1-c60b-4ba6-b6f7-05985bb9b51d · inbound

MAPLE: Latent Multi-Agent Play for End-to-End Autonomous Driving cites this paper.

MAPLE: Latent Multi-Agent Play for End-to-End Autonomous Driving CaRL: Learning Scalable Planning Policies with Simple Rewards

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-21T07:49:49.990219Z

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.

source=pdf_text observed=2026-05-21T07:48:52.168457Z digest=sha256:e4f1730c3f91b37f43db945c54e8b6b396d5a05b8a075b8a4df0a1f304bc6833

Observation f7174094-d128-4f74-a8bf-b9a81d72064f · inbound

DriveSafer: End-to-End Autonomous Driving with Safety Guidance cites this paper.

DriveSafer: End-to-End Autonomous Driving with Safety Guidance CaRL: Learning Scalable Planning Policies with Simple Rewards

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-19T21:47:48.699813Z

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.

source=pdf_text observed=2026-05-19T21:43:25.406524Z digest=sha256:24e839aaae439389382f95ff9df13aed57b083d3dfbf0344bae0484106948fec

Observation 29775f65-6292-45d0-95d9-c0df84ef79d6 · inbound

Scaling Self-Play for End-to-End Driving cites this paper.

Scaling Self-Play for End-to-End Driving CaRL: Learning Scalable Planning Policies with Simple Rewards

Reference 26

Resolution
verified exact
arxiv_id, observed 2026-07-04T01:29:22.337007Z

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.

source=pdf_text observed=2026-06-26T20:22:03.938518Z digest=sha256:1eca375ac77493ccea841173537e46eefbe241a895ee3a12e756c36cf47bf128

Observation efe9097f-183a-45b2-9ca0-f806f1d146e0 · inbound

PlanRL: A Trajectory Planning Architecture for Reinforcement Learning-based Driving Experts cites this paper.

PlanRL: A Trajectory Planning Architecture for Reinforcement Learning-based Driving Experts CaRL: Learning Scalable Planning Policies with Simple Rewards

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-07-04T13:59:52.271864Z

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.

source=pdf_text observed=2026-06-26T04:44:08.377384Z digest=sha256:ff845cccaa2767989f6ccec3c6d606f8c59dafdfe765c95bb1359e217115458c

Observation e2ac9611-57a9-4f69-8dca-5daa9c4378b3 · inbound

CLEAR: Closed-Loop Reinforcement Learning at Scale for End-to-End Autonomous Driving cites this paper.

CLEAR: Closed-Loop Reinforcement Learning at Scale for End-to-End Autonomous Driving CaRL: Learning Scalable Planning Policies with Simple Rewards

Reference 33

Resolution
unresolved
no resolver link, observed 2026-07-12T06:40:47.686215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T06:40:47.686215Z digest=sha256:509b77a0762257b72b4ec47d9d49a01e2bf0b613b08dcc951a7a3d53c78145ac