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Paper Citation Record · LEDGER

Automating Potential-based Reward Shaping with Vision Language Model Guidance

As of 8 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2606.27180.

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

pith.paper-citation-record.v1
2606.27180 v1

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-26T05:00:24.832807Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

45 of 45 outbound references displayed

  • verified exact4
  • verified fuzzy0
  • unresolved38
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch3

External citation measurements

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Outbound references

Observation c5a90018-f627-4a2d-8490-71addaefe7c7 · outbound

This paper cites Proceedings of the 41st International Conference on Machine Learning , articleno =.

Automating Potential-based Reward Shaping with Vision Language Model Guidance Proceedings of the 41st International Conference on Machine Learning , articleno =

Reference 1

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source=arxiv_source observed=2026-06-26T05:00:24.832807Z digest=sha256:f83937ccd3bc12127a3b8e12ba90a3cd3a683a61108755f84ef77bde09c74145

Observation 6981270d-cbc8-481b-a0f7-da6af31aac9d · outbound

This paper cites Deep Reinforcement Learning from Human Preferences , url =.

Automating Potential-based Reward Shaping with Vision Language Model Guidance Deep Reinforcement Learning from Human Preferences , url =

Reference 2

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Observation 23be9d0d-b064-4325-ab50-958c4c30b540 · outbound

This paper cites A Survey of Preference-Based Reinforcement Learning Methods , journal =.

Automating Potential-based Reward Shaping with Vision Language Model Guidance A Survey of Preference-Based Reinforcement Learning Methods , journal =

Reference 3

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Observation b1ae4516-c97a-481a-af77-bb406bcd624c · outbound

This paper cites Proceedings of the 38th International Conference on Machine Learning , pages =.

Automating Potential-based Reward Shaping with Vision Language Model Guidance Proceedings of the 38th International Conference on Machine Learning , pages =

Reference 4

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Observation 91273504-5c0b-465b-8ed0-93d367baa1ce · outbound

This paper cites 2024 , journal=.

Automating Potential-based Reward Shaping with Vision Language Model Guidance 2024 , journal=

Reference 5

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source=arxiv_source observed=2026-06-26T05:00:24.832807Z digest=sha256:d3a1ca840216a624268bbf5d337afe3a1c61ec03bbcb1beb05bde03c088b4d47

Observation 507c7217-fbd6-4830-a670-b58b2b84591f · outbound

This paper cites Qwen3 Technical Report.

Automating Potential-based Reward Shaping with Vision Language Model Guidance Qwen3 Technical Report

Reference 6

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local_arxiv, observed 2026-07-04T13:39:51.077061Z

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Observation f2a50467-37fc-4ff8-8496-081b61827013 · outbound

This paper cites Proceedings of the Conference on Robot Learning , pages =.

Automating Potential-based Reward Shaping with Vision Language Model Guidance Proceedings of the Conference on Robot Learning , pages =

Reference 7

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source=arxiv_source observed=2026-06-26T05:00:24.832807Z digest=sha256:e7259b3338da1df7c4e3ddad4607b5c890a796c654a6e5a1ab2876e529fa7d6c

Observation 619cd848-645e-45ef-9a86-fcc2a7408db6 · outbound

This paper cites Relay Policy Learning: Solving Long-Horizon Tasks via Imitation and Reinforcement Learning.

Automating Potential-based Reward Shaping with Vision Language Model Guidance Relay Policy Learning: Solving Long-Horizon Tasks via Imitation and Reinforcement Learning

Reference 8

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arxiv_id, observed 2026-07-04T13:39:51.080320Z

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source=arxiv_source observed=2026-06-26T05:00:24.832807Z digest=sha256:81cd41da843dce535160cc4ca0a73ed0b5f0fb2d03a79b39dc3872dc57ec2141

Observation e9326da5-3079-404c-8930-155851c2dbd2 · outbound

This paper cites 2020 , eprint=.

Automating Potential-based Reward Shaping with Vision Language Model Guidance 2020 , eprint=

Reference 9

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Observation a761fe09-d5e9-477a-8dcc-baadca97aec1 · outbound

This paper cites Proceedings of the 35th International Conference on Machine Learning , pages =.

Automating Potential-based Reward Shaping with Vision Language Model Guidance Proceedings of the 35th International Conference on Machine Learning , pages =

Reference 10

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Observation 568a160a-c8c9-406a-a55c-0cfb24db285e · outbound

This paper cites International Conference on Learning Representations , year=.

Automating Potential-based Reward Shaping with Vision Language Model Guidance International Conference on Learning Representations , year=

Reference 11

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source=arxiv_source observed=2026-06-26T05:00:24.832807Z digest=sha256:2e5fb32105072b74dc70c6b788286f360c546b640424a18e71e9566fb9c0a067

Observation 3b361828-4e66-4f61-a989-0fd6e44cf6b6 · outbound

This paper cites Navigating Noisy Feedback: Enhancing Reinforcement Learning with Error-Prone Language Models.

Automating Potential-based Reward Shaping with Vision Language Model Guidance Navigating Noisy Feedback: Enhancing Reinforcement Learning with Error-Prone Language Models

Reference 12

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source=arxiv_source observed=2026-06-26T05:00:24.832807Z digest=sha256:dadddf777d80a934c3a90d804e75acccc7271c3b4bf9bd2a30f4d210ca89ab5a

Observation ec931f19-77bc-4c06-98e6-31b64e5b2350 · outbound

This paper cites Second Agent Learning in Open-Endedness Workshop , year=.

Automating Potential-based Reward Shaping with Vision Language Model Guidance Second Agent Learning in Open-Endedness Workshop , year=

Reference 13

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source=arxiv_source observed=2026-06-26T05:00:24.832807Z digest=sha256:9016ff8736383006ba15be363fcb942270254d4711f46d21848a02eeb66fd313

Observation a184794b-8381-46d1-a956-b7522a02836f · outbound

This paper cites The Thirteenth International Conference on Learning Representations , year=.

Automating Potential-based Reward Shaping with Vision Language Model Guidance The Thirteenth International Conference on Learning Representations , year=

Reference 14

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Observation 8619dc0a-1e57-4ddb-b9e9-37e600f60c77 · outbound

This paper cites Forty-second International Conference on Machine Learning , year=.

Automating Potential-based Reward Shaping with Vision Language Model Guidance Forty-second International Conference on Machine Learning , year=

Reference 15

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Observation 8ce25427-aa6e-4fe4-af0e-4b484e5a3d2c · outbound

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Automating Potential-based Reward Shaping with Vision Language Model Guidance Unresolved cited work

Reference 16

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Observation d37a5270-4a73-48a5-81ad-dcfbd3fb0fab · outbound

This paper cites Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) , month =.

Automating Potential-based Reward Shaping with Vision Language Model Guidance Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) , month =

Reference 17

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Observation 5f6f4cef-035a-4d35-8bc7-192c8eb364b3 · outbound

This paper cites The method of paired comparisons , author=.

Automating Potential-based Reward Shaping with Vision Language Model Guidance The method of paired comparisons , author=

Reference 18

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Observation 7693c820-ee64-4f6d-858d-252be6415899 · outbound

This paper cites Learning to Drive a Bicycle Using Reinforcement Learning and Shaping , year =.

Automating Potential-based Reward Shaping with Vision Language Model Guidance Learning to Drive a Bicycle Using Reinforcement Learning and Shaping , year =

Reference 19

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source=arxiv_source observed=2026-06-26T05:00:24.832807Z digest=sha256:a85caa443fd7ae260f48142ae75bc4511aa593733200008875bd6a95a2214cdd

Observation 43f57327-18ea-4bb6-a865-4c1829936b7b · outbound

This paper cites Learning to Utilize Shaping Rewards: A New Approach of Reward Shaping , url =.

Automating Potential-based Reward Shaping with Vision Language Model Guidance Learning to Utilize Shaping Rewards: A New Approach of Reward Shaping , url =

Reference 20

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Observation c26c4d52-df70-46d4-b757-921c16f9d546 · outbound

This paper cites Self-Supervised Online Reward Shaping in Sparse-Reward Environments , year=.

Automating Potential-based Reward Shaping with Vision Language Model Guidance Self-Supervised Online Reward Shaping in Sparse-Reward Environments , year=

Reference 21

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Observation 4df8d470-7027-4d1f-aa4d-e0de242dd854 · outbound

This paper cites Exploration-Guided Reward Shaping for Reinforcement Learning under Sparse Rewards , url =.

Automating Potential-based Reward Shaping with Vision Language Model Guidance Exploration-Guided Reward Shaping for Reinforcement Learning under Sparse Rewards , url =

Reference 22

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Observation 98e120fe-9577-4797-8c9f-c0a6c00aa4c5 · outbound

This paper cites Keeping Your Distance: Solving Sparse Reward Tasks Using Self-Balancing Shaped Rewards , url =.

Automating Potential-based Reward Shaping with Vision Language Model Guidance Keeping Your Distance: Solving Sparse Reward Tasks Using Self-Balancing Shaped Rewards , url =

Reference 23

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Observation a23f3c94-5d39-4a6e-80ca-29feec58832f · outbound

This paper cites The Twelfth International Conference on Learning Representations , year=.

Automating Potential-based Reward Shaping with Vision Language Model Guidance The Twelfth International Conference on Learning Representations , year=

Reference 24

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Observation fd52d7c2-a247-4c49-bd5c-1d16c946ba82 · outbound

This paper cites Accelerating Reinforcement Learning of Robotic Manipulations via Feedback from Large Language Models.

Automating Potential-based Reward Shaping with Vision Language Model Guidance Accelerating Reinforcement Learning of Robotic Manipulations via Feedback from Large Language Models

Reference 25

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arxiv_id, observed 2026-07-04T13:39:51.073951Z

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Observation a88b0f3f-f24b-4c11-8718-6619ae567290 · outbound

This paper cites International Conference on Machine Learning , pages=.

Automating Potential-based Reward Shaping with Vision Language Model Guidance International Conference on Machine Learning , pages=

Reference 26

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Observation 0d45ac87-37cd-4c73-b645-7a5a8785d060 · outbound

This paper cites International Conference on Machine Learning , pages=.

Automating Potential-based Reward Shaping with Vision Language Model Guidance International Conference on Machine Learning , pages=

Reference 27

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Observation de7751f6-c5ec-46d1-a46c-398ca12c479c · outbound

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Automating Potential-based Reward Shaping with Vision Language Model Guidance 2023 , editor =

Reference 28

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Observation 99bcef9c-aaf9-4e29-be44-215ed3fe687b · outbound

This paper cites RoboCLIP: one demonstration is enough to learn robot policies , year =.

Automating Potential-based Reward Shaping with Vision Language Model Guidance RoboCLIP: one demonstration is enough to learn robot policies , year =

Reference 29

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Observation 1d2ab594-3d93-47ae-a6b7-a7d8f4f522b6 · outbound

This paper cites NeurIPS 2023 Foundation Models for Decision Making Workshop , year=.

Automating Potential-based Reward Shaping with Vision Language Model Guidance NeurIPS 2023 Foundation Models for Decision Making Workshop , year=

Reference 30

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Observation 790d57bd-0f69-43d0-baf0-34a365e02681 · outbound

This paper cites 2023 , eprint=.

Automating Potential-based Reward Shaping with Vision Language Model Guidance 2023 , eprint=

Reference 31

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Observation 1fe2e8a9-c4f5-4739-bc37-14f338b338dd · outbound

This paper cites Proceedings of The 4th Annual Learning for Dynamics and Control Conference , pages =.

Automating Potential-based Reward Shaping with Vision Language Model Guidance Proceedings of The 4th Annual Learning for Dynamics and Control Conference , pages =

Reference 32

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Observation 6dbe6085-588d-4ec2-b3ca-f19e83b753e2 · outbound

This paper cites and Harada, Daishi and Russell, Stuart J.

Automating Potential-based Reward Shaping with Vision Language Model Guidance and Harada, Daishi and Russell, Stuart J

Reference 33

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Observation 445c2649-885a-4bcf-988e-8065fd3e5f06 · outbound

This paper cites International Conference on Autonomous Agents and Multiagent Systems,.

Automating Potential-based Reward Shaping with Vision Language Model Guidance International Conference on Autonomous Agents and Multiagent Systems,

Reference 34

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Observation 04eae9d2-cbd7-4400-a6a0-4de99bb5443f · outbound

This paper cites Reward Shaping in Episodic Reinforcement Learning , year =.

Automating Potential-based Reward Shaping with Vision Language Model Guidance Reward Shaping in Episodic Reinforcement Learning , year =

Reference 35

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Observation 93b6797b-16f0-426a-a403-1bd2ffc41b98 · outbound

This paper cites Theoretical and Empirical Analysis of Reward Shaping in Reinforcement Learning , year=.

Automating Potential-based Reward Shaping with Vision Language Model Guidance Theoretical and Empirical Analysis of Reward Shaping in Reinforcement Learning , year=

Reference 36

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Observation 32039695-5958-4094-8a7d-25c761da30a6 · outbound

This paper cites Using incomplete and incorrect plans to shape reinforcement learning in long-sequence sparse-reward tasks , journal=.

Automating Potential-based Reward Shaping with Vision Language Model Guidance Using incomplete and incorrect plans to shape reinforcement learning in long-sequence sparse-reward tasks , journal=

Reference 37

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doi, observed 2026-06-26T05:08:59.878566Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-26T05:00:24.832807Z digest=sha256:fd9c0678ccbd0b1b597886e4ac07c3e8b85cc15bdb964f50c2d5d7f2477b8328

Observation b89ab5e7-f2c1-450d-a43e-701396f875f7 · outbound

This paper cites Improving the Effectiveness of Potential-based Reward Shaping in Reinforcement Learning , year =.

Automating Potential-based Reward Shaping with Vision Language Model Guidance Improving the Effectiveness of Potential-based Reward Shaping in Reinforcement Learning , year =

Reference 38

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no resolver link, observed 2026-06-26T05:00:24.832807Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-26T05:00:24.832807Z digest=sha256:2fd3c07b77c0354d037a3b5a0170d64f8abe2cd6a51d7422098d55b60a2e5c06

Observation c50616e0-ff59-4aa1-8693-7b288e79c834 · outbound

This paper cites Proceedings of the AAAI Conference on Artificial Intelligence , author=.

Automating Potential-based Reward Shaping with Vision Language Model Guidance Proceedings of the AAAI Conference on Artificial Intelligence , author=

Reference 39

Resolution
verified exact
doi, observed 2026-06-26T05:08:59.880833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-26T05:00:24.832807Z digest=sha256:4428cbe5cdcd830ec5bbb59c37a59a4fd90d429926146bb0183dbddb48a20ca0

Observation fd4a9fb3-ec46-48da-9aba-7e05cf3c5a07 · outbound

This paper cites A framework for flexibly guiding learning agents , journal =.

Automating Potential-based Reward Shaping with Vision Language Model Guidance A framework for flexibly guiding learning agents , journal =

Reference 40

Resolution
unresolved
no resolver link, observed 2026-06-26T05:00:24.832807Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-26T05:00:24.832807Z digest=sha256:987ce1142c1f789aac0366a11d43bdbde337bb56d8f62d25afbb901b4a163787

Observation 1fa4428f-126d-4293-99ef-702030378617 · outbound

This paper cites and Chernova, Sonia , title =.

Automating Potential-based Reward Shaping with Vision Language Model Guidance and Chernova, Sonia , title =

Reference 41

Resolution
unresolved
no resolver link, observed 2026-06-26T05:00:24.832807Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-26T05:00:24.832807Z digest=sha256:e2d437de1aace855837e439dbae0957b37b2cf292ec7bb922b0bff01fa903f1d

Observation 0059bf1e-6a67-4d99-b79e-f5a3e533058d · outbound

This paper cites Lee, Matthew Tan, Yuke Zhu, and Jeannette Bohg.

Automating Potential-based Reward Shaping with Vision Language Model Guidance Lee, Matthew Tan, Yuke Zhu, and Jeannette Bohg

Reference 42

Resolution
metadata mismatch
arxiv_id, observed 2026-06-26T05:08:59.879962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-26T05:00:24.832807Z digest=sha256:7fe3a1d48f28e52c7f7ea81c46ac9923eb1be09ebd5ff4d744c9bfd2af7c581a

Observation e9d83790-eaf5-480d-bd1c-543495c8dbd6 · outbound

This paper cites and Now\'.

Automating Potential-based Reward Shaping with Vision Language Model Guidance and Now\'

Reference 43

Resolution
unresolved
no resolver link, observed 2026-06-26T05:00:24.832807Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-26T05:00:24.832807Z digest=sha256:fb8e67c2644d78be170878c054c39517b33224f9fe74257f80545fe73096adb3

Observation b29128ee-8241-4c6b-812b-f6f11537c1ae · outbound

This paper cites Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems , pages =.

Automating Potential-based Reward Shaping with Vision Language Model Guidance Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems , pages =

Reference 44

Resolution
unresolved
no resolver link, observed 2026-06-26T05:00:24.832807Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-26T05:00:24.832807Z digest=sha256:6ca6f4938659b177fde95814cf3e03db4d8967acf24cdb7ba4b35d2eb954386a

Observation 07dd6bc2-319e-4be8-bc45-158f495789ed · outbound

This paper cites Improving Sample Efficiency of Reinforcement Learning With Background Knowledge From Large Language Models , year=.

Automating Potential-based Reward Shaping with Vision Language Model Guidance Improving Sample Efficiency of Reinforcement Learning With Background Knowledge From Large Language Models , year=

Reference 45

Resolution
unresolved
no resolver link, observed 2026-06-26T05:00:24.832807Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-26T05:00:24.832807Z digest=sha256:9f90496d7022dcafee87c2c10bba1576979e7ae3878d46ffe740885dd52abf79

Pith citing papers

No inbound Pith citation observations are available.