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Paper Citation Record · LEDGER

Learning to Plan with Natural Language

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2304.10464.

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

pith.paper-citation-record.v1
2304.10464 v4

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 2026-08-17T06:30:58.91139+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T14:58:10.724460Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-16T06:11:49.639634Z

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 2c66dc3c-464e-4957-b524-655058264fd6 · inbound

EvoPrompt: Connecting LLMs with Evolutionary Algorithms Yields Powerful Prompt Optimizers cites this paper.

EvoPrompt: Connecting LLMs with Evolutionary Algorithms Yields Powerful Prompt Optimizers Learning to Plan with Natural Language

Reference 125

Resolution
verified exact
arxiv_id, observed 2026-05-16T06:11:49.641010Z

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=arxiv_source observed=2026-05-16T06:11:49.475825Z digest=sha256:f27bfd4d5641cde784c1aecb80cdac6a904af45b346774fe2d99b7e60d7b2ae3

Observation 0dde9b68-81ba-42ed-9dfd-ffb295cdfb59 · inbound

PACE: Adaptive Budget Allocation for Time-Efficient Embodied Planning cites this paper.

PACE: Adaptive Budget Allocation for Time-Efficient Embodied Planning Learning to Plan with Natural Language

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-15T14:58:10.724460Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T14:58:10.724460Z digest=sha256:c6a780fe7e8dc1093fab223eded4b96536c3dbccac27a9a395028adcb8aba547