Pith. sign in

Paper Citation Record · LEDGER

Survey on Large Language Model-Enhanced Reinforcement Learning: Concept, Taxonomy, and Methods

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2404.00282.

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

pith.paper-citation-record.v1
2404.00282 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:24:59.577571Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T18:16:11.560912Z

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 fe683cb7-9a2a-4882-8a66-49e4a15e6b1d · inbound

Multiple Weaks Win Single Strong: Large Language Models Ensemble Weak Reinforcement Learning Agents into a Supreme One cites this paper.

Multiple Weaks Win Single Strong: Large Language Models Ensemble Weak Reinforcement Learning Agents into a Supreme One Survey on Large Language Model-Enhanced Reinforcement Learning: Concept, Taxonomy, and Methods

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-07T15:24:59.577571Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:24:59.577571Z digest=sha256:24022781815c23696161e8217b816c5ad7615e05cb887774e96ce07277bbb968

Observation 3942b9c3-ad8e-4511-bde0-883b6885be11 · inbound

Is Inter-Seed Cross-Play Enough? Evaluating the Robustness of Zero-Shot Coordination Algorithms to Implementation Details cites this paper.

Is Inter-Seed Cross-Play Enough? Evaluating the Robustness of Zero-Shot Coordination Algorithms to Implementation Details Survey on Large Language Model-Enhanced Reinforcement Learning: Concept, Taxonomy, and Methods

Reference 234

Resolution
verified exact
local_arxiv, observed 2026-08-05T15:25:41.498673Z

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.

source=arxiv_source observed=2026-08-05T15:25:40.412842Z digest=sha256:546210fe461ff4b03a9207e523f1d6e058f327309a8a26f1faa1b8451257c75d