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Paper Citation Record · LEDGER

Reinforcement learning based recommender systems: A survey

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2101.06286.

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

pith.paper-citation-record.v1
2101.06286 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T10:59:58.956067Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-10T20:53:52.919258Z

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 a8d1d33a-5783-4593-8cd7-18365ef7bf59 · inbound

Defining the scope of AI regulations cites this paper.

Defining the scope of AI regulations Reinforcement learning based recommender systems: A survey

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-14T10:59:58.956067Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T10:59:58.956067Z digest=sha256:4909d5c138c32855a2b86d820f47e44dda44e5c66ece16a1382d40a55d946cab

Observation dd206164-e838-44c0-9098-f5c9d1487860 · inbound

PPO-Q: Proximal Policy Optimization with Parametrized Quantum Policies or Values cites this paper.

PPO-Q: Proximal Policy Optimization with Parametrized Quantum Policies or Values Reinforcement learning based recommender systems: A survey

Reference 43

Resolution
verified exact
local_arxiv, observed 2026-08-10T20:53:52.924344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-10T20:53:52.493475Z digest=sha256:70163150e9dce8da3270f2482c979e6c2e9102526396ee8a6de29358827d62f0

Observation dffe9ec5-9c19-4606-b88d-44e1e21dd763 · inbound

Self-Evolving Recommendation System: End-To-End Autonomous Model Optimization With LLM Agents cites this paper.

Self-Evolving Recommendation System: End-To-End Autonomous Model Optimization With LLM Agents Reinforcement learning based recommender systems: A survey

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-03T01:15:20.483852Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T01:15:20.483852Z digest=sha256:866830760abddc6bc3832b200d8083d09e95faeca4d79818f31ecc75890aff6c

Observation 2796e22b-1eae-4c27-b982-16717a5d4534 · inbound

Self-Evolving Recommendation System: End-To-End Autonomous Model Optimization With LLM Agents cites this paper.

Self-Evolving Recommendation System: End-To-End Autonomous Model Optimization With LLM Agents Reinforcement learning based recommender systems: A survey

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-04T06:05:26.795335Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T06:05:26.795335Z digest=sha256:7a77d789012e939f95d5f66b885a7622d45637c0ed615302514f0eadc3c5e565