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Paper Citation Record · LEDGER

Distributionally Robust and Safe Imitation Learning

As of 16 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:2607.13436.

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

pith.paper-citation-record.v1
2607.13436 v1

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T05:17:10.467104Z

measured 20 of 20 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 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.

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Reference resolution

20 of 20 outbound references displayed

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External citation measurements

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Outbound references

Observation 9c77aebe-c69b-4a5e-a323-d2ba100c55ae · outbound

This paper cites Recent advances in robot learning from demonstration,.

Distributionally Robust and Safe Imitation Learning Recent advances in robot learning from demonstration,

Reference 1

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source=pdf_text observed=2026-08-02T05:17:08.814273Z digest=sha256:271dc69fdf474ac754026d6ed3c28590f488fa6f1b9ad600b9b704edc87770de

Observation 31722a91-2e1e-4d4f-a5b7-2f90a91e5d86 · outbound

This paper cites A survey of imitation learning: Algorithms, recent developments, and challenges,.

Distributionally Robust and Safe Imitation Learning A survey of imitation learning: Algorithms, recent developments, and challenges,

Reference 2

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source=pdf_text observed=2026-08-02T05:17:08.903460Z digest=sha256:0dc0ba0c689bc44130944a834c523eb2ec7ff0a931e95c025a1fb759a80c30b8

Observation 73160f41-2e54-4c56-ac33-086c00e92cf2 · outbound

This paper cites Survey of imitation learning for robotic manipulation: B. fang et al.,.

Distributionally Robust and Safe Imitation Learning Survey of imitation learning for robotic manipulation: B. fang et al.,

Reference 3

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source=pdf_text observed=2026-08-02T05:17:08.975034Z digest=sha256:6a6f10926c14cd9cf3b0a42b3cbe1db7feaa5afa44017b009945c37429ca53d5

Observation e6491680-61e8-423c-93a6-8bcbad76aa6d · outbound

This paper cites A survey on imitation learning techniques for end-to-end autonomous vehicles,.

Distributionally Robust and Safe Imitation Learning A survey on imitation learning techniques for end-to-end autonomous vehicles,

Reference 4

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Observation 42cb1645-b45c-4b8e-a63d-c63515748b85 · outbound

This paper cites Imitation learning for legged robot loco- motion: a survey,.

Distributionally Robust and Safe Imitation Learning Imitation learning for legged robot loco- motion: a survey,

Reference 5

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source=pdf_text observed=2026-08-02T05:17:09.081260Z digest=sha256:5880b86eb8e2648dc6f8cedcaa40c2d44095d58af986a70c7016035511931011

Observation c3518350-c214-48c6-bb0e-79d563431e22 · outbound

This paper cites Recent Advances in Imitation Learning from Observation.

Distributionally Robust and Safe Imitation Learning Recent Advances in Imitation Learning from Observation

Reference 6

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source=pdf_text observed=2026-08-02T05:17:09.157959Z digest=sha256:6d5bc2b7407f0f0eb8d80c581f7cf0579dcba4966391504df9571b1ef9394c35

Observation 2aa850d2-872c-4c40-9aa5-f51752403458 · outbound

This paper cites Data quality in imitation learning,.

Distributionally Robust and Safe Imitation Learning Data quality in imitation learning,

Reference 7

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source=pdf_text observed=2026-08-02T05:17:09.247313Z digest=sha256:316029481beaff366985779e063687527a52af027ac2439c6b776ea00b1a0fcc

Observation f90a81fe-40e0-41b3-bce9-6b1469d64fb5 · outbound

This paper cites Efficient deep learning of robust policies from mpc using imitation and tube-guided data augmentation,.

Distributionally Robust and Safe Imitation Learning Efficient deep learning of robust policies from mpc using imitation and tube-guided data augmentation,

Reference 8

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source=pdf_text observed=2026-08-02T05:17:09.334089Z digest=sha256:df14cf574f160d04683d62e2c773ddecff8b1958c185179050c392a58e439572

Observation 7063a7ac-bbe0-48b0-b77d-1c01622ac16c · outbound

This paper cites Distributionally robust imi- tation learning: Layered control architecture for certifiable autonomy,.

Distributionally Robust and Safe Imitation Learning Distributionally robust imi- tation learning: Layered control architecture for certifiable autonomy,

Reference 9

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source=pdf_text observed=2026-08-02T05:17:09.395227Z digest=sha256:2fa5b800e257cf5b4fcf817945a85de48b671e01467afe83504ffea92af2247a

Observation 0145e3ec-21d7-4ce8-831e-0d9b13eef63e · outbound

This paper cites A reduction of imitation learning and structured prediction to no-regret online learning,.

Distributionally Robust and Safe Imitation Learning A reduction of imitation learning and structured prediction to no-regret online learning,

Reference 10

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source=pdf_text observed=2026-08-02T05:17:09.496085Z digest=sha256:66d1de6bbe8e3d727b9469affd660d39ba405e818623b5190eca05cb04f1195a

Observation fa38b8f5-d08b-4f91-8033-e06acdae5c0a · outbound

This paper cites Dart: Noise injection for robust imitation learning,.

Distributionally Robust and Safe Imitation Learning Dart: Noise injection for robust imitation learning,

Reference 11

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source=pdf_text observed=2026-08-02T05:17:09.569929Z digest=sha256:cb9be91d5477acf7bc4d8ca5f43ca00ea0f117be81b2948004409a437857729f

Observation 3b184ff7-7ed0-41ee-b07d-7db44e02eb03 · outbound

This paper cites A survey of inverse reinforcement learning: Challenges, methods and progress,.

Distributionally Robust and Safe Imitation Learning A survey of inverse reinforcement learning: Challenges, methods and progress,

Reference 12

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source=pdf_text observed=2026-08-02T05:17:09.695036Z digest=sha256:0ac814f964eab0c95117c235b6350a2619a9cc71e180a6336affc49087d6ab0a

Observation 6b97f706-e4ac-48db-8b88-cc7c6b3ab8cf · outbound

This paper cites Generative adversarial imitation learning,.

Distributionally Robust and Safe Imitation Learning Generative adversarial imitation learning,

Reference 13

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source=pdf_text observed=2026-08-02T05:17:09.800974Z digest=sha256:256bffb17b13e740f43f2389916dee45460eb7d4fe61ce18bd2660e9f9d98977

Observation 701a6d8d-0f93-4ba0-bb7a-e3218a261a50 · outbound

This paper cites Tasil: Taylor series im- itation learning,.

Distributionally Robust and Safe Imitation Learning Tasil: Taylor series im- itation learning,

Reference 14

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source=pdf_text observed=2026-08-02T05:17:09.882559Z digest=sha256:0b22d4abed611940964b2fbfea602f79474a2663c8b84bdbe588a29e2bba2d24

Observation 5f06ceeb-d446-4e63-815a-d7695ee70632 · outbound

This paper cites Robust imitation learning against variations in environment dynamics,.

Distributionally Robust and Safe Imitation Learning Robust imitation learning against variations in environment dynamics,

Reference 15

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source=pdf_text observed=2026-08-02T05:17:09.936106Z digest=sha256:f36bff56ec841232eacba9250a172a40df19fb5e4b78bbee522640462673595d

Observation cb417c36-967f-4935-bd30-6c59390d0bfb · outbound

This paper cites Distribution- ally robust behavioral cloning for robust imitation learning,.

Distributionally Robust and Safe Imitation Learning Distribution- ally robust behavioral cloning for robust imitation learning,

Reference 16

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source=pdf_text observed=2026-08-02T05:17:10.039503Z digest=sha256:acc457cadeee47c99af9efb8fafeeac593433128e3dc0d9d3e4836c1ab77d4aa

Observation f2e72ee6-c59c-4925-b235-9274eabb36c7 · outbound

This paper cites $\mathcal{L}_1$-DRAC: Distributionally Robust Adaptive Control.

Distributionally Robust and Safe Imitation Learning $\mathcal{L}_1$-DRAC: Distributionally Robust Adaptive Control

Reference 17

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Observation 38437692-b305-4bec-b276-2153cf2ed64c · outbound

This paper cites Wasserstein distributionally robust adap- tive covariance steering,.

Distributionally Robust and Safe Imitation Learning Wasserstein distributionally robust adap- tive covariance steering,

Reference 18

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source=pdf_text observed=2026-08-02T05:17:10.260156Z digest=sha256:7bb519368b2d22c53822e3a9562c3c851bcef21b0741e44a945d3cc16994942e

Observation 3f57ffe0-5991-48b9-b0a3-e48c1125bdc6 · outbound

This paper cites Certifying Some Distributional Robustness with Principled Adversarial Training.

Distributionally Robust and Safe Imitation Learning Certifying Some Distributional Robustness with Principled Adversarial Training

Reference 19

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Observation fd0f37d7-c463-4965-b5ea-0bdaea8ad2ea · outbound

This paper cites A Mathematical Theory of Co-Design.

Distributionally Robust and Safe Imitation Learning A Mathematical Theory of Co-Design

Reference 20

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Pith citing papers

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