Paper Citation Record · LEDGER

Revisiting Design Choices in Proximal Policy Optimization

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2009.10897.

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

pith.paper-citation-record.v1
2009.10897 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:52:35.555023Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T10:49:45.563057Z

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 7447214d-7e81-4771-b36b-9bdd8b70b765 · inbound

CORE: Constraint-Aware One-Step Reinforcement Learning for Simulation-Guided Neural Network Accelerator Design cites this paper.

CORE: Constraint-Aware One-Step Reinforcement Learning for Simulation-Guided Neural Network Accelerator Design Revisiting Design Choices in Proximal Policy Optimization

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T11:07:21.350107Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb34228b-9a45-42b7-aca3-fc385ac9f6c7 · inbound

Inverse Design in Distributed Circuits Using Single-Step Reinforcement Learning cites this paper.

Inverse Design in Distributed Circuits Using Single-Step Reinforcement Learning Revisiting Design Choices in Proximal Policy Optimization

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T11:52:35.555023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c44ddcf7-6bee-48a6-af64-bdda314cd99a · inbound

Does Synthetic Data Help? Empirical Evidence from Deep Learning Time Series Forecasters cites this paper.

Does Synthetic Data Help? Empirical Evidence from Deep Learning Time Series Forecasters Revisiting Design Choices in Proximal Policy Optimization

Reference 262

Resolution: verified exact; arxiv_id, observed 2026-05-11T18:41:12.424999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d279ee8d-3619-45d0-a63d-418f3cbae076 · inbound

LogNEO: A GPT-Neo Reinforcement Learning Framework for Accurate Real-Time Log Anomaly Detection cites this paper.

LogNEO: A GPT-Neo Reinforcement Learning Framework for Accurate Real-Time Log Anomaly Detection Revisiting Design Choices in Proximal Policy Optimization

Reference 23

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T20:27:22.334873Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 9c2a93da-45fb-40ff-8bb9-8f768257e4bc · inbound

KLip-PPO: A per-sample KL perspective on PPO-Clip cites this paper.

KLip-PPO: A per-sample KL perspective on PPO-Clip Revisiting Design Choices in Proximal Policy Optimization

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-07-04T10:49:45.565074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.