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Paper Citation Record · LEDGER

LLM-Empowered State Representation for Reinforcement Learning

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2407.13237.

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

pith.paper-citation-record.v1
2407.13237 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 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 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:25:00.044677Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T02:06:27.232020Z

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 61197aeb-f728-4ac8-bfb1-da8bba5d30b2 · 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 LLM-Empowered State Representation for Reinforcement Learning

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-07T15:25:00.044677Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:25:00.044677Z digest=sha256:83d8e71d4858a737980ee32065142a95d6642f9580cf8511cdf576b8b0f9ce90

Observation 057437c3-648c-49ae-ae05-acd084c7d1a2 · inbound

MARCO: Meta-Reflection with Cross-Referencing for Code Reasoning cites this paper.

MARCO: Meta-Reflection with Cross-Referencing for Code Reasoning LLM-Empowered State Representation for Reinforcement Learning

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-07T14:49:34.579442Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:49:34.579442Z digest=sha256:fa4589bd8e76a9e21cdf5e328c934618a26baab6dd999221bf0a83ba7610463b

Observation 69417e3c-eead-4211-bfef-ef06e0ad6bcc · inbound

Prompt-Tuned LLM-Augmented DRL for Dynamic O-RAN Network Slicing cites this paper.

Prompt-Tuned LLM-Augmented DRL for Dynamic O-RAN Network Slicing LLM-Empowered State Representation for Reinforcement Learning

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-07T12:07:28.753855Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:07:28.753855Z digest=sha256:42744146be734d65f1e19cf337c18e3773b4e195da3bbd194d08c359afa2e93d

Observation cc747d0d-52cf-4ca7-a086-348a3a091fb5 · inbound

ORAN-GUIDE: RAG-Driven Prompt Learning for LLM-Augmented Reinforcement Learning in O-RAN Network Slicing cites this paper.

ORAN-GUIDE: RAG-Driven Prompt Learning for LLM-Augmented Reinforcement Learning in O-RAN Network Slicing LLM-Empowered State Representation for Reinforcement Learning

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T12:06:18.128963Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:06:18.128963Z digest=sha256:ea5c6c4eb5c19246e3e1328ed71eb53a7ba74f5e2ce01b47be32d51437ea9dbd

Observation 6c842107-86fb-4075-8f01-cf7c1137c0b6 · inbound

Learning Task-Invariant Properties via Dreamer: Enabling Efficient Policy Transfer for Quadruped Robots cites this paper.

Learning Task-Invariant Properties via Dreamer: Enabling Efficient Policy Transfer for Quadruped Robots LLM-Empowered State Representation for Reinforcement Learning

Reference 30

Resolution
verified exact
arxiv_id, observed 2026-05-13T19:53:11.805886Z

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=2026-05-13T19:49:23.086498Z digest=sha256:68253b0c4dd23a248622a952747d950c0dfc50a310f94376133395d34961f4d8

Observation 01ee8ecf-186c-427b-bbfb-d6249ca3f598 · inbound

PriorZero: Bridging Language Priors and World Models for Decision Making cites this paper.

PriorZero: Bridging Language Priors and World Models for Decision Making LLM-Empowered State Representation for Reinforcement Learning

Reference 45

Resolution
metadata mismatch
arxiv_id, observed 2026-05-13T05:27:18.613527Z

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=arxiv_source observed=2026-05-13T05:25:05.907123Z digest=sha256:1cc04d085439a30fda58c50a752654d42c6065a27a11ef512bf40a3463c65b74

Observation f4b768f0-1e6a-47a8-bdc8-7827472204c5 · inbound

Right Makes Might: Aligning Verified Hidden States Empowers RL Reasoning cites this paper.

Right Makes Might: Aligning Verified Hidden States Empowers RL Reasoning LLM-Empowered State Representation for Reinforcement Learning

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-07-02T02:06:27.233967Z

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=2026-06-28T11:13:21.565082Z digest=sha256:24f31d789acc7178f4d79b57500dd922fcef2aca30ecfe44f4ad52ae43851a33