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Paper Citation Record · LEDGER

URLB: Unsupervised Reinforcement Learning Benchmark

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2110.15191.

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

pith.paper-citation-record.v1
2110.15191 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 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 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T23:27:10.227715Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T06:09:37.568122Z

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 9675307c-0b74-414e-988a-e6618eb45ad2 · inbound

Ring Attention with Blockwise Transformers for Near-Infinite Context cites this paper.

Ring Attention with Blockwise Transformers for Near-Infinite Context URLB: Unsupervised Reinforcement Learning Benchmark

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-05-12T19:28:28.264291Z

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=2026-05-12T19:28:28.201789Z digest=sha256:99f3cfd94a172db75eb93fe3a5573b55a276020260352a7bbd6fe46301c3e391

Observation 35c863d3-95c4-454e-86e3-360a5b546cc0 · inbound

Test-Time Alignment via Hypothesis Reweighting cites this paper.

Test-Time Alignment via Hypothesis Reweighting URLB: Unsupervised Reinforcement Learning Benchmark

Reference 39

Resolution
verified exact
arxiv_id, observed 2026-05-23T06:57:40.508112Z

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=arxiv_source observed=2026-05-23T06:55:54.051821Z digest=sha256:5c17f50c0b261b55d874188c786d75ed8bea41da487ded6fc00865c6c6c0fe10

Observation 8ec95f17-9622-4bb3-9f8f-e81737bb8dd6 · inbound

Behavioral Entropy-Guided Dataset Generation for Offline Reinforcement Learning cites this paper.

Behavioral Entropy-Guided Dataset Generation for Offline Reinforcement Learning URLB: Unsupervised Reinforcement Learning Benchmark

Reference 2020

Resolution
unresolved
no resolver link, observed 2026-08-08T23:27:10.227715Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T23:27:10.227715Z digest=sha256:26635b313e84e02c6e56e1bf55b15a09ed7e6a5bce37172dc255e80a8054eff0

Observation 0ab1fa87-310f-4571-ad83-a3e2d187c08c · inbound

RedRFT: A Light-Weight Benchmark for Reinforcement Fine-Tuning-Based Red Teaming cites this paper.

RedRFT: A Light-Weight Benchmark for Reinforcement Fine-Tuning-Based Red Teaming URLB: Unsupervised Reinforcement Learning Benchmark

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-07T10:55:20.212381Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:55:20.212381Z digest=sha256:f40596bec3a327ebd66b6560d719f0a9965582cfce9e6aeb27eba80dc8abf549

Observation 6a562b5b-dfad-4cdb-bdee-9306df3dcf24 · inbound

Epistemically-guided forward-backward exploration cites this paper.

Epistemically-guided forward-backward exploration URLB: Unsupervised Reinforcement Learning Benchmark

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-06T19:32:33.850798Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:32:33.850798Z digest=sha256:a23e45797443819901945990133c0410897a7dfb71b1abc4e19d2de87af34d1b

Observation f8ff49ef-a2ff-469f-a26a-7272292de7a0 · inbound

Scaling DRL for Decision Making: A Survey on Data, Network, and Training Budget Strategies cites this paper.

Scaling DRL for Decision Making: A Survey on Data, Network, and Training Budget Strategies URLB: Unsupervised Reinforcement Learning Benchmark

Reference 1989

Resolution
unresolved
no resolver link, observed 2026-08-06T04:39:02.796315Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:39:02.796315Z digest=sha256:b3c1ad546753561ca688ed3bf3238a27474a401835cb4febab93d016f36f856b

Observation c662e91e-b9de-431d-99c9-cec0a371241d · inbound

NaP-Control: Navigating Diffusion Prior for Versatile and Fast Character Control cites this paper.

NaP-Control: Navigating Diffusion Prior for Versatile and Fast Character Control URLB: Unsupervised Reinforcement Learning Benchmark

Reference 60

Resolution
metadata mismatch
arxiv_id, observed 2026-05-21T09:44:05.598956Z

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=2026-05-21T09:43:07.291649Z digest=sha256:30405fa561fc77e18eb452280b0967023d888ef03b03a3c64251fa72f518f71d

Observation cce5b212-7792-4d4a-8d61-97c5ff9c5260 · inbound

NaP-Control: Navigating Diffusion Prior for Versatile and Fast Character Control cites this paper.

NaP-Control: Navigating Diffusion Prior for Versatile and Fast Character Control URLB: Unsupervised Reinforcement Learning Benchmark

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-02T16:17:15.518662Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T16:17:15.518662Z digest=sha256:dd5256a4bf67f524c21cf35a00a695a2efce438fe5643de2d5c6de684ad55892

Observation a0e6834c-c95c-428e-a270-b8a75fc44efd · inbound

Reward-free Pretraining for Reinforcement Learning via Occupancy Coverage Maximization cites this paper.

Reward-free Pretraining for Reinforcement Learning via Occupancy Coverage Maximization URLB: Unsupervised Reinforcement Learning Benchmark

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-07-04T06:09:37.570048Z

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=2026-06-26T14:48:19.683101Z digest=sha256:2fc34ccf3a4a104ca08f93320244e2e856848c21e34bfcc6637fb0aa222c21cc