Paper Citation Record · LEDGER

Learning adaptive planning representations with natural language guidance

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2312.08566.

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

pith.paper-citation-record.v1
2312.08566 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 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 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:12:09.617627Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-11T00:27:51.785853Z

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 2e9300cf-4d68-4bbc-ab71-dae6b0c1bc08 · 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 adaptive planning representations with natural language guidance

Reference 277

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:09.617627Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 576e9fd0-5872-4415-8a0e-28d4b7da5efd · inbound

PartInstruct: Part-level Instruction Following for Fine-grained Robot Manipulation cites this paper.

PartInstruct: Part-level Instruction Following for Fine-grained Robot Manipulation Learning adaptive planning representations with natural language guidance

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-07T13:35:54.445779Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 75a08234-8fc3-4997-bbd2-9b28c98996e4 · inbound

Analogy making as amortised model construction cites this paper.

Analogy making as amortised model construction Learning adaptive planning representations with natural language guidance

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-06T15:12:51.979423Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 553e5317-f2cd-4ed8-b54a-dc619fbff0fa · inbound

Rollout Cards: A Reproducibility Standard for Agent Research cites this paper.

Rollout Cards: A Reproducibility Standard for Agent Research Learning adaptive planning representations with natural language guidance

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-13T06:02:23.578723Z

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.

Observation 16ddd92d-0fa8-4230-b812-3ad5632aa157 · inbound

SCOPE: Evolving Symbolic World for Planning in Open-Ended Environments cites this paper.

SCOPE: Evolving Symbolic World for Planning in Open-Ended Environments Learning adaptive planning representations with natural language guidance

Reference 16

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T08:49:42.277629Z

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.

Observation c11f3004-7cb2-4b4d-8548-57e73a25f3cf · inbound

Hypothesis-driven Model Expansion under Uncertainty for Open-World Robot Planning cites this paper.

Hypothesis-driven Model Expansion under Uncertainty for Open-World Robot Planning Learning adaptive planning representations with natural language guidance

Reference 68

Resolution: verified exact; local_arxiv, observed 2026-07-11T00:27:51.811128Z

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.