Pith. sign in

Paper Citation Record · LEDGER

CaRL: Learning Scalable Planning Policies with Simple Rewards

As of 11 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 2026-08-10T06:31:04.303077+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:f80873b381b85e6bddbeb367120c0eb102c1db62280a185b0b687cd3795159a7

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:ec95321d35ce6cf703624a15e770e5caa5bc2eac9a6bd1baa2c5782ad2a6355d

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-15T00:55:01.446865Z digest=sha256:2f1ba98ea8861971dc47769107ae054bae6ca8b832c6ea8a639feffcc3f75c99

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-13T17:05:06.300013Z digest=sha256:be5c52d2f26333aeb3e1011a7ea763bc72e25839cc2d2163e21476c79a5a7dd5

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:beb26da8cf7e4e1181ee18b8ba56e5a160357ccb054ed39aaa1a0016cc822c3d

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T17:19:01.704384Z digest=sha256:5de591494cd3c4958351f78009459d14f8546de7fb6fb144bfcdb3001c6c235e

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-12T03:31:25.453515Z digest=sha256:32804c9c16e13c78c5c1f9f4d715f62c37f6777151d001cc6b5b4dd4048cb194

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-15T04:41:07.402168Z digest=sha256:d2866020480acfa2f7b898d96e837caeacc389a3d2e7740864048d279d689d3a

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-21T07:48:52.168457Z digest=sha256:76a005a11cd441c36eb36940fc513ffd20d024f2de221ea0f1fcf6b8c985b780

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-19T21:43:25.406524Z digest=sha256:1d51bc6b589bcb9f7381d90db8673f487a9e9331eee971778b0fa8538deefe12

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-26T20:22:03.938518Z digest=sha256:5c0dcf18a1fb74b150602061a7dea7ad5d746aac25a77ddbe6f57fcdd779c550

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-26T04:44:08.377384Z digest=sha256:8ef3b4389e5f24596e2c716bba840736dae3c7a9666863f7426bd6ee60f9c7c5

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=sha256:0fec676b8f72efb7c1b864019bdc06bf2cfc3c810000a5c7dbb90aae3171a66a