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Paper Citation Record · LEDGER

Towards General-Purpose Model-Free Reinforcement Learning

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2501.16142.

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

pith.paper-citation-record.v1
2501.16142 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 2026-08-09T06:31:02.800959+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:34:35.620176Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T22:54:01.397668Z

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 d4b0f8b5-cc20-45b9-bed2-1406b5bfb2b8 · inbound

A Survey of State Representation Learning for Deep Reinforcement Learning cites this paper.

A Survey of State Representation Learning for Deep Reinforcement Learning Towards General-Purpose Model-Free Reinforcement Learning

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-06T23:34:35.620176Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:34:35.620176Z digest=sha256:b7eb629ef9e46ea5e1305ee26a2654776d2909a7b06c6d9c28ff6b707bad387a

Observation 78751558-57a8-4f6f-9f27-cee1e22bede0 · inbound

Robust Remote Reinforcement Learning over Unreliable Communication Channels using Homomorphic State Encoding cites this paper.

Robust Remote Reinforcement Learning over Unreliable Communication Channels using Homomorphic State Encoding Towards General-Purpose Model-Free Reinforcement Learning

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-05-19T00:02:54.114134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-19T00:02:34.789456Z digest=sha256:d00616c180a4f8d2fd84fec1a0751224de50ffae9962f48cd2ef8ceb558b9f2e

Observation 224dae12-cb9e-4f19-9dc1-922bb7978849 · inbound

FlashSAC: Fast and Stable Off-Policy Reinforcement Learning for High-Dimensional Robot Control cites this paper.

FlashSAC: Fast and Stable Off-Policy Reinforcement Learning for High-Dimensional Robot Control Towards General-Purpose Model-Free Reinforcement Learning

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-10T22:15:49.810765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T20:04:56.512544Z digest=sha256:b736cb199afe4c99c3471db7061eae8e852c6f70a770a6a91251dd9c29dd94cc

Observation 8e72612d-7013-49e4-ae5d-03c0f891f155 · inbound

FlashSAC: Fast and Stable Off-Policy Reinforcement Learning for High-Dimensional Robot Control cites this paper.

FlashSAC: Fast and Stable Off-Policy Reinforcement Learning for High-Dimensional Robot Control Towards General-Purpose Model-Free Reinforcement Learning

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-19T17:12:41.367305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-19T17:08:31.770889Z digest=sha256:d0f6c88c0ca551e9342db1d55886be04f9e30f08fb4c856ec8ebc3086c3e0872

Observation 56777634-5fe2-48d5-b82e-f07986761865 · inbound

Multi-scale Predictive Representations for Goal-conditioned Reinforcement Learning cites this paper.

Multi-scale Predictive Representations for Goal-conditioned Reinforcement Learning Towards General-Purpose Model-Free Reinforcement Learning

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-12T07:16:26.229076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-12T03:35:37.739085Z digest=sha256:f11d53f06206fd0ef70684648b9b40a958152b8e8d73f58ad557d021b9e436c9

Observation 018082ce-955c-4b11-a1d0-466a6b4f75dc · inbound

When Does Non-Uniform Replay Matter in Reinforcement Learning? cites this paper.

When Does Non-Uniform Replay Matter in Reinforcement Learning? Towards General-Purpose Model-Free Reinforcement Learning

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-05-12T05:36:24.537453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-12T05:33:19.038889Z digest=sha256:1e38e258050dae419fadc3cb45da0f923b187f598108aeeaaabe3b8d945ed046

Observation cdb25e8e-926f-48ff-9237-033d92ef4e1c · inbound

When Does Non-Uniform Replay Matter in Reinforcement Learning? cites this paper.

When Does Non-Uniform Replay Matter in Reinforcement Learning? Towards General-Purpose Model-Free Reinforcement Learning

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-05-13T06:32:24.816786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-13T06:27:38.643667Z digest=sha256:5237ba70550883fb13b3d3041e9e84c4b4a5060cea418d5376db93902b1fab53

Observation 1b15abf1-53d9-4035-9293-9efffa9d1491 · inbound

When Does Non-Uniform Replay Matter in Reinforcement Learning? cites this paper.

When Does Non-Uniform Replay Matter in Reinforcement Learning? Towards General-Purpose Model-Free Reinforcement Learning

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-05-20T23:09:12.776405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-20T23:04:12.943222Z digest=sha256:9aa47f4e4079e5d4ac3424bc307ef3ba9fa1866bdc5b55e8f4faec04d692fe3c

Observation 0caa2f9d-b828-4b0f-b5c5-9d8d72ff4b46 · inbound

Scaling World-Model Reinforcement Learning Through Diffusion Policy Optimization cites this paper.

Scaling World-Model Reinforcement Learning Through Diffusion Policy Optimization Towards General-Purpose Model-Free Reinforcement Learning

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-06-29T22:54:01.399916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-29T22:46:27.179341Z digest=sha256:9584bd1cfe00ea22bba1609571dd6d49a12c35fd3c1a97c02efb2e8086d67d52