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Paper Citation Record · LEDGER

SR-Reward: Taking The Path More Traveled

As of 11 August 2026, this Paper Citation Record lists 56 of 56 outbound references and 0 inbound Pith citation observations for arXiv:2501.02330.

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

pith.paper-citation-record.v1
2501.02330 v3

Coverage vector

measured 56 of 56 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:21:23.104750Z

measured 56 of 56 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+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

56 of 56 outbound references displayed

  • verified exact0
  • verified fuzzy35
  • unresolved21
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4b67c23e-9c47-49c7-b547-a4314e23899c · outbound

This paper cites an unresolved cited work.

SR-Reward: Taking The Path More Traveled Unresolved cited work

Reference 1

Resolution
unresolved
raw_fallback, observed 2026-08-10T22:21:23.873760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T22:21:22.905224Z digest=sha256:e47ea605560033a07a83805161313ffd4f9b376f1b8c0f5343652892d16b99f3

Observation 45d5f5d2-17b0-41d4-b5d2-1f7abf21edcc · outbound

This paper cites Holo-Dex: Teaching Dexterity with Immersive Mixed Reality.

SR-Reward: Taking The Path More Traveled Holo-Dex: Teaching Dexterity with Immersive Mixed Reality

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-10T22:21:22.909253Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T22:21:22.909253Z digest=sha256:724732ce975845ef631d15096eb060abe16f032b7cb7aad697a491ae8fca3f84

Observation 9f446d9b-6532-41f4-8b6f-d4dfe2c7474c · outbound

This paper cites Ball, Laura Smith, Ilya Kostrikov, and Sergey Levine.

SR-Reward: Taking The Path More Traveled Ball, Laura Smith, Ilya Kostrikov, and Sergey Levine

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:21:23.861331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T22:21:22.913041Z digest=sha256:e7e47cabeeb704a164c247b793d5f5ae7f23a963306299a2df1619a2ba4bafa4

Observation 3b7a34cf-ab4a-4c77-94ff-d057352f0d79 · outbound

This paper cites Successor features for transfer in reinforcement learning.

SR-Reward: Taking The Path More Traveled Successor features for transfer in reinforcement learning

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:21:23.848412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T22:21:22.917077Z digest=sha256:6e9b3c2395aabc4b5d481578275f205a7b94bb04088c82fd1001b1afa450b379

Observation a7c0a29f-cc80-4f15-871b-1ead3ef0b752 · outbound

This paper cites Mankowitz, Hado van Hasselt, R \' e mi Munos, David Silver, and Tom Schaul.

SR-Reward: Taking The Path More Traveled Mankowitz, Hado van Hasselt, R \' e mi Munos, David Silver, and Tom Schaul

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:21:23.836204Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T22:21:22.920685Z digest=sha256:e5d99350767ad0ab4777501082189a18971964104ef7e391def405c1b45b64e6

Observation 53128db3-72b6-48c0-a928-6b2bbb6b5244 · outbound

This paper cites an unresolved cited work.

SR-Reward: Taking The Path More Traveled Unresolved cited work

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-10T22:21:22.924202Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T22:21:22.924202Z digest=sha256:17cdf0f906cf291955196a228241ab123ac1c55698b39821298006559e8f9ec7

Observation ddb19ae1-8db5-4144-90dd-99d09d2097cf · outbound

This paper cites Successor feature sets: Generalizing successor representations across policies.

SR-Reward: Taking The Path More Traveled Successor feature sets: Generalizing successor representations across policies

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:21:23.823412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T22:21:22.928212Z digest=sha256:de1139ba68fc69eece5428b199478f50b50b17d763ef9ec6ff11eaebad939a8c

Observation a06bce04-d870-4e87-9cfb-a7701e64f92b · outbound

This paper cites Deep reinforcement learning from human preferences.

SR-Reward: Taking The Path More Traveled Deep reinforcement learning from human preferences

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-10T22:21:22.931667Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T22:21:22.931667Z digest=sha256:acce023e8241fedec5ace25cb78607cd68e2e6e5b33d23995689044f829ca07c

Observation ccafeb6d-ad73-414e-928c-1ca7945b7ecb · outbound

This paper cites Improving generalization for temporal difference learning: The successor representation.

SR-Reward: Taking The Path More Traveled Improving generalization for temporal difference learning: The successor representation

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:21:23.811217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T22:21:22.935625Z digest=sha256:8fcb6589febb5c64adb9fe347005d154d24742819fe80cfd28b0bc170db5744e

Observation 6fef980f-accc-4aa1-85d1-54d43be59acb · outbound

This paper cites Model alignment as prospect theoretic optimization.

SR-Reward: Taking The Path More Traveled Model alignment as prospect theoretic optimization

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:21:23.798882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T22:21:22.939240Z digest=sha256:421d1cbc0395b5ed7c0df145429d41a5ecb54330065246d5349d3b70e584aca4

Observation bb78bb06-bbcf-4b1d-b8dd-9e76232d41a9 · outbound

This paper cites Psiphi-learning: Reinforcement learning with demonstrations using successor features and inverse temporal difference learning.

SR-Reward: Taking The Path More Traveled Psiphi-learning: Reinforcement learning with demonstrations using successor features and inverse temporal difference learning

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:21:23.785507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T22:21:22.942905Z digest=sha256:9ce323e2e2c7d7a7cc1849d7d14c68c50fe4d0951a0d33060f2b7291a1ad1b07

Observation 5b84edfd-463f-457d-8b94-7a7ee6b92a03 · outbound

This paper cites Learning robust rewards with adverserial inverse reinforcement learning.

SR-Reward: Taking The Path More Traveled Learning robust rewards with adverserial inverse reinforcement learning

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:21:23.772900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T22:21:22.946811Z digest=sha256:daf1b8d47b0089de25e78e3dfdc657423848f2f7c5f4f4992a5c283e9d93258b

Observation a38220d3-3d03-43c0-93af-1d0600590a04 · outbound

This paper cites D4rl: Datasets for deep data-driven reinforcement learning, 2020.

SR-Reward: Taking The Path More Traveled D4rl: Datasets for deep data-driven reinforcement learning, 2020

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-10T22:21:22.950147Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T22:21:22.950147Z digest=sha256:7ee4938289e4f0bfefb9a08082236210476f1f63935adafc388ba5f35d0cd455

Observation b032dc46-b8d2-47ed-ac25-587239e7229f · outbound

This paper cites Addressing function approximation error in actor-critic methods.

SR-Reward: Taking The Path More Traveled Addressing function approximation error in actor-critic methods

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:21:23.753908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T22:21:22.953505Z digest=sha256:6833d51aad04ed51de263ea1b164a61484923c0c5e10731e0b7245911eba40ec

Observation c21cba52-019b-4603-8f2b-5b543a75985c · outbound

This paper cites Off-policy deep reinforcement learning without exploration.

SR-Reward: Taking The Path More Traveled Off-policy deep reinforcement learning without exploration

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:21:23.742706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T22:21:22.957005Z digest=sha256:8f442f37f91e796f0cd948e3490cb91827310e8a19a6225603e28839a58d2ce8

Observation 0473402f-a42b-4a25-8cc5-9fb1d6d03623 · outbound

This paper cites For sale: State-action representation learning for deep reinforcement learning.

SR-Reward: Taking The Path More Traveled For sale: State-action representation learning for deep reinforcement learning

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:21:23.731061Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T22:21:22.960390Z digest=sha256:cdf0d1a89dd2840e53ea79f6615aa57d5dbe456cb3f6cb97188b602c0c05b09e

Observation e5b6a7b7-ba45-4839-b6a0-fbc48437ce4d · outbound

This paper cites Iq-learn: Inverse soft-q learning for imitation.

SR-Reward: Taking The Path More Traveled Iq-learn: Inverse soft-q learning for imitation

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:21:23.718243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T22:21:22.963975Z digest=sha256:a661009b0387a046b85bc1eba2c7223f46fed0b941d566852de6bcd22a518bbb

Observation ec67118d-7084-4e4e-9012-c5b25488bf0a · outbound

This paper cites Extreme q-learning: Maxent RL without entropy.

SR-Reward: Taking The Path More Traveled Extreme q-learning: Maxent RL without entropy

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:21:23.707137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T22:21:22.967608Z digest=sha256:dc41c2cbf0c40b53c55dd48bff10ad3825d634dda38ead23755f9352444e0709

Observation e466d414-70cd-49ac-8deb-ff3198d53b83 · outbound

This paper cites A divergence minimization perspective on imitation learning methods, 2019.

SR-Reward: Taking The Path More Traveled A divergence minimization perspective on imitation learning methods, 2019

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:21:23.694803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T22:21:22.970922Z digest=sha256:95cdf52bfd9a4521cece66a29d183604288cbc63256fd6a95a535d7ffde35d37

Observation 46076099-306e-4647-a5f8-2df7d07e80b5 · outbound

This paper cites Generative Adversarial Networks.

SR-Reward: Taking The Path More Traveled Generative Adversarial Networks

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-10T22:21:22.974806Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T22:21:22.974806Z digest=sha256:859c5595c40334926d434d5432de25e4fb9c91145ee92e69f4c7fff0ec1013d8

Observation fb4d58a3-5be3-460b-9b16-11712bd38b1f · outbound

This paper cites Maniskill2: A unified benchmark for generalizable manipulation skills.

SR-Reward: Taking The Path More Traveled Maniskill2: A unified benchmark for generalizable manipulation skills

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:21:23.682125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T22:21:22.978934Z digest=sha256:8c60161be64c915c724383f6d25a33658a3140268b26f9602433444380b1f893

Observation 5125191d-55c1-4633-aa9a-5761f45d6a23 · outbound

This paper cites Generative adversarial imitation learning.

SR-Reward: Taking The Path More Traveled Generative adversarial imitation learning

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:21:23.670608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T22:21:22.982372Z digest=sha256:7c90d711a3340c627eeb95d53774d8d3f88c2460f73bbb617b2afc9290afffe8

Observation 824744c3-32a9-4835-a5e6-916791ccd87a · outbound

This paper cites Revisiting successor features for inverse reinforcement learning.

SR-Reward: Taking The Path More Traveled Revisiting successor features for inverse reinforcement learning

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:21:23.655636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T22:21:22.986249Z digest=sha256:9a719af3fcee4077e431ffd4e25677bd5287a41d29565630e2033e49504b1e1c

Observation 5c12df2f-4ff4-44f1-a3ad-67a9b76dc95d · outbound

This paper cites Deep inverse q-learning with constraints.

SR-Reward: Taking The Path More Traveled Deep inverse q-learning with constraints

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:21:23.642876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T22:21:22.989954Z digest=sha256:dc37b99c368064c33aead6d1c736f0857da06231afed9c7d6afdc579c26579b7

Observation e9a365a7-5379-48fd-83c1-7445ac51e84b · outbound

This paper cites Imitation learning as f -divergence minimization, 2020.

SR-Reward: Taking The Path More Traveled Imitation learning as f -divergence minimization, 2020

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:21:23.627879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T22:21:22.993525Z digest=sha256:7035cab6e49052e2d919170b527fef56fbb01c7276180695c3e441e4e2e17824

Observation 51b6f6ec-49d9-46ed-afd8-cfba2e80545e · outbound

This paper cites Discriminator-actor-critic: Addressing sample inefficiency and reward bias in adversarial imitation learning.

SR-Reward: Taking The Path More Traveled Discriminator-actor-critic: Addressing sample inefficiency and reward bias in adversarial imitation learning

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:21:23.614989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T22:21:22.996926Z digest=sha256:a740d730c399d1072e58a528a8306e1e753aa5f5edc9993d8fa031937cf86d66

Observation f40d1fbc-6f00-4ca6-9c75-cf8a8a4fd187 · outbound

This paper cites Imitation learning via off-policy distribution matching.

SR-Reward: Taking The Path More Traveled Imitation learning via off-policy distribution matching

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:21:23.603124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T22:21:23.000416Z digest=sha256:ac21caafcb64f49ec79c525e0dd7bcd090f3b193d005ffa1271fe01f5dfa61f4

Observation d38b1494-317b-4fb6-9020-d3801ac98c92 · outbound

This paper cites Offline reinforcement learning with implicit q-learning.

SR-Reward: Taking The Path More Traveled Offline reinforcement learning with implicit q-learning

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-10T22:21:23.004356Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T22:21:23.004356Z digest=sha256:b7763d9fa292d84b73c14e0cdbd0ce0bd18139c5c26d34deb220a5dd87fe2cb9

Observation 492e82f3-6417-4ea7-8bec-4a96a47cb649 · outbound

This paper cites Deep Successor Reinforcement Learning.

SR-Reward: Taking The Path More Traveled Deep Successor Reinforcement Learning

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-10T22:21:23.007879Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T22:21:23.007879Z digest=sha256:5d826ccfaccabd2bdb17b07e1b8c22a58708b222ecb5851d64277f03df8f49fc

Observation baaab7a1-1292-4b63-995c-c19ef609b95e · outbound

This paper cites Conservative q-learning for offline reinforcement learning.

SR-Reward: Taking The Path More Traveled Conservative q-learning for offline reinforcement learning

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:21:23.584257Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T22:21:23.011851Z digest=sha256:d5301932936ebf73034d5306eea8f6a30243954d3ba11209e498552b4b265f74

Observation 2c855f70-6c92-4a1e-bf3a-4bbb17246f83 · outbound

This paper cites Batch Reinforcement Learning, pp.\ 45--73.

SR-Reward: Taking The Path More Traveled Batch Reinforcement Learning, pp.\ 45--73

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-10T22:21:23.015503Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T22:21:23.015503Z digest=sha256:c9457cdf4602e301ad5c714479763df6198d4dfe518ec759c5503aec527e1b4f

Observation cfdfbf27-39bf-4cad-b1e2-d51bb413f8c2 · outbound

This paper cites Energy-based imitation learning.

SR-Reward: Taking The Path More Traveled Energy-based imitation learning

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:21:23.572467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T22:21:23.019228Z digest=sha256:d4745ab54aa9a4e6c956e18bee811ea95b7bd75d334084c32f70a13e0dba506b

Observation 82b1b85c-db3f-4e4f-bcbc-7d1f4e203a34 · outbound

This paper cites Learning self-correctable policies and value functions from demonstrations with negative sampling.

SR-Reward: Taking The Path More Traveled Learning self-correctable policies and value functions from demonstrations with negative sampling

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:21:23.560852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T22:21:23.022851Z digest=sha256:c8c2b2150956348c4d9c5bbbf13577bbd10b34b365c7dc68503be4da8cf9f2a0

Observation fb73b68b-b885-4d72-b167-9fca4ae69a4b · outbound

This paper cites Count-based exploration with the successor representation.

SR-Reward: Taking The Path More Traveled Count-based exploration with the successor representation

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-10T22:21:23.026552Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T22:21:23.026552Z digest=sha256:fed341423aad126108abc7a5672656afae98fec931842bce7f043f40bf843dec

Observation 7c904107-37ba-4b24-875a-57b4b6dc007b · outbound

This paper cites Rusu, Joel Veness, Marc G.

SR-Reward: Taking The Path More Traveled Rusu, Joel Veness, Marc G

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-10T22:21:23.030323Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T22:21:23.030323Z digest=sha256:fe6bd8dbd954c36d79c3781fc775b7594a41b8463c08a851ea12b74afa286945

Observation 95d98138-d117-444a-a2db-4837b87d4b78 · outbound

This paper cites A first-occupancy representation for reinforcement learning.

SR-Reward: Taking The Path More Traveled A first-occupancy representation for reinforcement learning

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:21:23.542158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T22:21:23.034464Z digest=sha256:9bc5a8f4c341446128e5661b14508115780c669784d8706759005cf75a9cc243

Observation 385f08cf-0c36-4d1d-82dc-29d1e280304d · outbound

This paper cites Dualdice: Behavior-agnostic estimation of discounted stationary distribution corrections, 2019.

SR-Reward: Taking The Path More Traveled Dualdice: Behavior-agnostic estimation of discounted stationary distribution corrections, 2019

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:21:23.530228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T22:21:23.037537Z digest=sha256:23c2ed4de96ed7d8a2d99382d82d5866d27646cdf9bd95587e96c7217361b19f

Observation ed1cd8c7-c50a-4591-b519-1eaf0f81858e · outbound

This paper cites Ng and Stuart Russell.

SR-Reward: Taking The Path More Traveled Ng and Stuart Russell

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:21:23.518989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T22:21:23.040286Z digest=sha256:31b44f5034e6cd4cb5d2a0cbfee42dd44ac365c10684d42e622b16b8ad9503b7

Observation 920dbc8a-5536-4cb4-8ad1-5217836fdb9a · outbound

This paper cites Bridging state and history representations: Understanding self-predictive rl, 2024.

SR-Reward: Taking The Path More Traveled Bridging state and history representations: Understanding self-predictive rl, 2024

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:21:23.507422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T22:21:23.043526Z digest=sha256:dfb7fc197092d4ccf3db8c73ea79d58a5ab9172aed4b7a7c6d4f6d749705b55d

Observation 270bce38-e486-4197-8d02-1701a146b962 · outbound

This paper cites Efficient training of artificial neural networks for autonomous navigation.

SR-Reward: Taking The Path More Traveled Efficient training of artificial neural networks for autonomous navigation

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-10T22:21:23.046666Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T22:21:23.046666Z digest=sha256:3970ecdcd1aef9b5f9b1d74725c1740ba88738137a832c763a370141f83e1ef0

Observation ffc88be0-7288-4e31-8794-233f4ad09433 · outbound

This paper cites Puterman.

SR-Reward: Taking The Path More Traveled Puterman

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-10T22:21:23.050183Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T22:21:23.050183Z digest=sha256:76a69a6b2b3e4a4ba8ac60f5ed5a2fa5aa887624e9d767ee81ce463d397e25be

Observation cbc410ba-2fc0-4486-ad18-38a88682a827 · outbound

This paper cites Direct Preference Optimization: Your Language Model is Secretly a Reward Model.

SR-Reward: Taking The Path More Traveled Direct Preference Optimization: Your Language Model is Secretly a Reward Model

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-10T22:21:23.053264Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T22:21:23.053264Z digest=sha256:7b06f9163830ef36e7b8375df1c9e496001e4decd5c1196a4bf3bcf1f4fe58b8

Observation 638f87b3-4306-490b-a380-387fc0236d02 · outbound

This paper cites Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations.

SR-Reward: Taking The Path More Traveled Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-10T22:21:23.056451Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T22:21:23.056451Z digest=sha256:80221e557f6970efb48d2fd50020e846503b14e91187f9b270e8919f5e8ec47d

Observation 302cd67a-e909-4572-b325-0ddc319b4d27 · outbound

This paper cites A motion retargeting method for effective mimicry-based teleoperation of robot arms.

SR-Reward: Taking The Path More Traveled A motion retargeting method for effective mimicry-based teleoperation of robot arms

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:21:23.481317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T22:21:23.059814Z digest=sha256:e336731413a639ebcac2d37b722ce5450fb93b18c648479f2ce2d2b46f632a99

Observation e0b5629e-d842-44e3-b7a8-11593c3bcab7 · outbound

This paper cites Dragan, and Sergey Levine.

SR-Reward: Taking The Path More Traveled Dragan, and Sergey Levine

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:21:23.470428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T22:21:23.062855Z digest=sha256:31d1902666c9cdc134c7c1ad173f311cb21fe8ceb6afc30ec2afe94547b41e6c

Observation 5f7a51b9-4a93-49ee-bd76-ff0481931ac2 · outbound

This paper cites A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning.

SR-Reward: Taking The Path More Traveled A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-10T22:21:23.066567Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T22:21:23.066567Z digest=sha256:c7452d378df585c427abcdd09d66a0178db7d8d0d83141e68435adf212fba6c8

Observation 6826ce05-3b2d-4427-a5dd-9fa7d11300d1 · outbound

This paper cites Dual rl: Unification and new methods for reinforcement and imitation learning, 2023.

SR-Reward: Taking The Path More Traveled Dual rl: Unification and new methods for reinforcement and imitation learning, 2023

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:21:23.458920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T22:21:23.070585Z digest=sha256:3f867ef97b56ba2f2e97a86f4b4c19433c9d92847edf3a9e3600ec749c005db2

Observation 313881f8-6826-4a4d-8e63-71e03ff540b7 · outbound

This paper cites Lewis, and A.

SR-Reward: Taking The Path More Traveled Lewis, and A

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:21:23.447364Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T22:21:23.074251Z digest=sha256:963844c9f9e3aaec63db9f853dbf7fa708a9daa6de4e30dd5ba1d4ee14d21d14

Observation 9b231494-24e3-4c0f-b569-5c8a1594e147 · outbound

This paper cites Issues in using function approximation for reinforcement learning.

SR-Reward: Taking The Path More Traveled Issues in using function approximation for reinforcement learning

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:21:23.436180Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T22:21:23.078004Z digest=sha256:8a96bd6dcaacbf9c78c4cf8561f235b2fe021819f98bb2c1e7def97b6a244d31

Observation 3722a0c4-167e-44aa-b916-c7e4f949d9e0 · outbound

This paper cites Mujoco: A physics engine for model-based control.

SR-Reward: Taking The Path More Traveled Mujoco: A physics engine for model-based control

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-10T22:21:23.081882Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T22:21:23.081882Z digest=sha256:5eb794d6601471688072b0e21e1baa856cb5dcfc0a759e23200c37c39bfbd458

Observation d7423c8d-55a4-4073-ad02-9f5fe3e79d43 · outbound

This paper cites Munchausen reinforcement learning.

SR-Reward: Taking The Path More Traveled Munchausen reinforcement learning

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-10T22:21:23.085538Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T22:21:23.085538Z digest=sha256:d63b0012ad8ee85275374a1d493e232cd97f612ec203a6ee71242a590d95f0ea

Observation 20523608-9296-4a7f-8d1f-f9188dde7aa6 · outbound

This paper cites Daydreamer: World models for physical robot learning.

SR-Reward: Taking The Path More Traveled Daydreamer: World models for physical robot learning

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-10T22:21:23.089529Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T22:21:23.089529Z digest=sha256:bb90de1a896d1ef262d34367df7a47bfaaac661f8af200d8923302b9ae05b1c6

Observation 47c83658-6a74-4aee-9caf-8e85680b5d09 · outbound

This paper cites Gello: A general, low-cost, and intuitive teleoperation framework for robot manipulators, 2023.

SR-Reward: Taking The Path More Traveled Gello: A general, low-cost, and intuitive teleoperation framework for robot manipulators, 2023

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-10T22:21:23.093332Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T22:21:23.093332Z digest=sha256:8e036f68b531295e20c5a676373745da67f0ba7fbcd10166f3ba0121c3e12253

Observation c06728c8-6e80-444e-9aae-d8bba8838704 · outbound

This paper cites Offline rl with no ood actions: In-sample learning via implicit value regularization.

SR-Reward: Taking The Path More Traveled Offline rl with no ood actions: In-sample learning via implicit value regularization

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:21:23.402805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T22:21:23.097383Z digest=sha256:cdbb076aabd919b0367a24b3934584e0f58d876b1ebb41272715839e8afe1084

Observation 054f9da7-b1eb-4f61-9bb6-18f39e83b3e3 · outbound

This paper cites Deep reinforcement learning with successor features for navigation across similar environments.

SR-Reward: Taking The Path More Traveled Deep reinforcement learning with successor features for navigation across similar environments

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:21:23.390055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T22:21:23.100930Z digest=sha256:82a2fd4aa9bef73b4f834b7033c5eb5d87f7123a99a15ac229b9b4abd9095f8c

Observation 93c77db1-874a-465f-8d44-05beaddeadc4 · outbound

This paper cites write newline.

SR-Reward: Taking The Path More Traveled write newline

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-10T22:21:23.104750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T22:21:23.104750Z digest=sha256:f54efe8b1c5c856cbbb416ad3f879ffd894ca69ad197ef8d9dfaae873cd279c5

Pith citing papers

No inbound Pith citation observations are available.