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Paper Citation Record · LEDGER

Learning to Plan for Retrieval-Augmented Large Language Models from Knowledge Graphs

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2406.14282.

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

pith.paper-citation-record.v1
2406.14282 v3

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 2026-08-08T06:32:00.761636+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T19:12:42.406669Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-10T05:51:10.616521Z

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 5bae7c66-f8d1-4f57-8a20-1af6abdd951e · inbound

OntoTune: Ontology-Driven Self-training for Aligning Large Language Models cites this paper.

OntoTune: Ontology-Driven Self-training for Aligning Large Language Models Learning to Plan for Retrieval-Augmented Large Language Models from Knowledge Graphs

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-08T19:12:42.406669Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T19:12:42.406669Z digest=sha256:5c22abaf0fe2505160b0d28f8e9543ef330f7d8bc594015564f88d19712a6de7

Observation a4abe563-3de0-4b2c-8839-c8de8dc4320f · inbound

Large Language Models for Planning: A Comprehensive and Systematic Survey cites this paper.

Large Language Models for Planning: A Comprehensive and Systematic Survey Learning to Plan for Retrieval-Augmented Large Language Models from Knowledge Graphs

Reference 247

Resolution
unresolved
no resolver link, observed 2026-08-07T14:12:07.743331Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:12:07.743331Z digest=sha256:1fd67fc32833a9a403e3ecf49193aaec53dc5a5bce63689a4e37678f7cfdee76

Observation dc98b0a4-14bf-4b29-91a1-eea9959bfa67 · inbound

From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies cites this paper.

From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies Learning to Plan for Retrieval-Augmented Large Language Models from Knowledge Graphs

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-07T04:48:08.738187Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:48:08.738187Z digest=sha256:5e007d129842d43acde804c50c9a7729bd8d87dbc8fe7ebc76f930a7507a485b

Observation 4cbaa5cb-cefd-46fe-9f72-40d211984451 · inbound

EHRAG: Bridging Semantic Gaps in Lightweight GraphRAG via Hybrid Hypergraph Construction and Retrieval cites this paper.

EHRAG: Bridging Semantic Gaps in Lightweight GraphRAG via Hybrid Hypergraph Construction and Retrieval Learning to Plan for Retrieval-Augmented Large Language Models from Knowledge Graphs

Reference 174

Resolution
verified exact
arxiv_id, observed 2026-05-10T05:51:10.617746Z

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=2026-05-10T05:43:04.813867Z digest=sha256:aee2ce17c2a73252b6c13ef9a68c958674c27dca2c9b2b2f8ef35616531c4dda