Paper Citation Record · LEDGER

Is Optimal Transport Necessary for Inverse Reinforcement Learning?

As of 8 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 0 inbound Pith citation observations for arXiv:2506.06793.

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

pith.paper-citation-record.v1
2506.06793 v1

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:55:44.334634Z

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

13 of 13 outbound references displayed

verified exact1
verified fuzzy3
unresolved8
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e00c7b65-fed7-47c7-9acb-f49ab039ab0a · outbound

This paper cites an unresolved cited work.

Is Optimal Transport Necessary for Inverse Reinforcement Learning? Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:55:44.614493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1e6b7ae8-f902-410b-bfd4-0a46f9427fd7 · outbound

This paper cites Offline Reinforcement Learning with Implicit Q-Learning.

Is Optimal Transport Necessary for Inverse Reinforcement Learning? Offline Reinforcement Learning with Implicit Q-Learning

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T05:55:44.291109Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 33d38b5f-2ef3-4ce6-a9fc-309048e84cce · outbound

This paper cites Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems.

Is Optimal Transport Necessary for Inverse Reinforcement Learning? Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T05:55:44.296509Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac0c0899-2adc-44ed-9c23-c200a1f69bee · outbound

This paper cites Optimal Transport for Offline Imitation Learning.

Is Optimal Transport Necessary for Inverse Reinforcement Learning? Optimal Transport for Offline Imitation Learning

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T05:55:44.302372Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 34932914-3c75-4170-85db-6e569ae1e674 · outbound

This paper cites This transformation helps mitigate the implicit penalization of longer traject ories and controls the variance of reward magnitudes.

Is Optimal Transport Necessary for Inverse Reinforcement Learning? This transformation helps mitigate the implicit penalization of longer traject ories and controls the variance of reward magnitudes

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:55:44.664487Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d7ac83e7-0801-4781-af36-a68f2f3574b1 · outbound

This paper cites Eventually, their total scores match each other.

Is Optimal Transport Necessary for Inverse Reinforcement Learning? Eventually, their total scores match each other

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:55:44.648391Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 61d668e3-97b6-43b9-b8bf-b03268dc2109 · outbound

This paper cites To address this, we adopt the same reward scaling proce- dure used in Temporal OT [Fu et al., 2024].

Is Optimal Transport Necessary for Inverse Reinforcement Learning? To address this, we adopt the same reward scaling proce- dure used in Temporal OT [Fu et al., 2024]

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:55:44.631748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 95a653d2-c636-46e1-a1dc-60f029a4753d · outbound

This paper cites Wasserstein Adversarial Imitation Learning.

Is Optimal Transport Necessary for Inverse Reinforcement Learning? Wasserstein Adversarial Imitation Learning

Reference 2019

Resolution: metadata mismatch; local_arxiv, observed 2026-08-07T05:55:44.386000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 97dffea0-2565-4375-bbcf-0238739a0749 · outbound

This paper cites A Survey of Inverse Reinforcement Learning: Challenges, Methods and Progress.

Is Optimal Transport Necessary for Inverse Reinforcement Learning? A Survey of Inverse Reinforcement Learning: Challenges, Methods and Progress

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-07T05:55:44.260548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ebb58a68-9bcf-4418-82a2-e2ef00d5b0eb · outbound

This paper cites D4RL: Datasets for Deep Data-Driven Reinforcement Learning.

Is Optimal Transport Necessary for Inverse Reinforcement Learning? D4RL: Datasets for Deep Data-Driven Reinforcement Learning

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-07T05:55:44.278167Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0101bfc7-b943-441a-ba66-150e96fa0e21 · outbound

This paper cites Justin Fu, Aviral Kumar, Oﬁr Nachum, George Tucker, and Serg ey Levine.

Is Optimal Transport Necessary for Inverse Reinforcement Learning? Justin Fu, Aviral Kumar, Oﬁr Nachum, George Tucker, and Serg ey Levine

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-07T05:55:44.272514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35c51995-73be-4d59-977e-3b74123d9851 · outbound

This paper cites Teach a Robot to FISH: Versatile Imitation from One Minute of Demonstrations.

Is Optimal Transport Necessary for Inverse Reinforcement Learning? Teach a Robot to FISH: Versatile Imitation from One Minute of Demonstrations

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-07T05:55:44.285682Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 935be607-bb07-4486-8390-0f5eb70bd440 · outbound

This paper cites Align Your Intents: Offline Imitation Learning via Optimal Transport.

Is Optimal Transport Necessary for Inverse Reinforcement Learning? Align Your Intents: Offline Imitation Learning via Optimal Transport

Reference 2024

Resolution: verified exact; local_arxiv, observed 2026-08-07T05:55:44.580075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Pith citing papers

No inbound Pith citation observations are available.