Paper Citation Record · LEDGER

Large Language Models for Planning: A Comprehensive and Systematic Survey

As of 31 July 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2505.19683.

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

pith.paper-citation-record.v1
2505.19683 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-07-31T06:34:12.847434+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-31T06:59:14.883715Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-08T00:34:22.691865Z

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 a88a508c-ee05-4de8-ae13-ed008a16499c · inbound

A Survey of Context Engineering for Large Language Models cites this paper.

A Survey of Context Engineering for Large Language Models Large Language Models for Planning: A Comprehensive and Systematic Survey

Reference 117

Resolution: verified exact; arxiv_id, observed 2026-05-13T20:58:45.538912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 7902bac0-afe3-45bd-9f5e-6118078da194 · inbound

Agentic World Modeling: Foundations, Capabilities, Laws, and Beyond cites this paper.

Agentic World Modeling: Foundations, Capabilities, Laws, and Beyond Large Language Models for Planning: A Comprehensive and Systematic Survey

Reference 43

Resolution: verified exact; arxiv_id, observed 2026-05-11T19:26:07.655990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 5a7bb717-a37d-4ca1-bdc2-6f37e8061a87 · inbound

Agentic World Modeling: Foundations, Capabilities, Laws, and Beyond cites this paper.

Agentic World Modeling: Foundations, Capabilities, Laws, and Beyond Large Language Models for Planning: A Comprehensive and Systematic Survey

Reference 43

Resolution: verified exact; arxiv_id, observed 2026-07-04T17:29:59.532638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 30809969-4b0f-4ca2-8e11-6218e699da00 · inbound

From Coarse to Fine: Self-Adaptive Hierarchical Planning for LLM Agents cites this paper.

From Coarse to Fine: Self-Adaptive Hierarchical Planning for LLM Agents Large Language Models for Planning: A Comprehensive and Systematic Survey

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:46:10.439768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation a3438d75-d87b-43de-b86a-b4ec6e412ae4 · inbound

Agentic Environment Engineering for Large Language Models: A Survey of Environment Modeling, Synthesis, Evaluation, and Application cites this paper.

Agentic Environment Engineering for Large Language Models: A Survey of Environment Modeling, Synthesis, Evaluation, and Application Large Language Models for Planning: A Comprehensive and Systematic Survey

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-07-03T10:58:02.840441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 71e3cae7-5e63-431d-9b0a-c7fb66c4cc62 · inbound

DocArena: Turning Raw Documents into Controllable Training Environments for Document Search Agents cites this paper.

DocArena: Turning Raw Documents into Controllable Training Environments for Document Search Agents Large Language Models for Planning: A Comprehensive and Systematic Survey

Reference 3

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T12:53:26.583135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 8b6a8e26-52f8-4808-a2a4-3b02510d2e4b · inbound

Empowering GUI Agents via Autonomous Experience Exploration and Hindsight Experience Utilization for Task Planning cites this paper.

Empowering GUI Agents via Autonomous Experience Exploration and Hindsight Experience Utilization for Task Planning Large Language Models for Planning: A Comprehensive and Systematic Survey

Reference 13

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T14:29:53.335307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 6ca52f5a-ba45-472c-9185-5ea5f62b7514 · inbound

ClassicLogic: A Knowledge-Driven Benchmark of Classic Puzzle Games for Evaluating Compositional Generalization cites this paper.

ClassicLogic: A Knowledge-Driven Benchmark of Classic Puzzle Games for Evaluating Compositional Generalization Large Language Models for Planning: A Comprehensive and Systematic Survey

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-07-08T00:34:22.693840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 8d3b0e49-3111-4c1c-bbee-1b090868200d · inbound

Information-seeking failures of large language models in agentic clinical reasoning cites this paper.

Information-seeking failures of large language models in agentic clinical reasoning Large Language Models for Planning: A Comprehensive and Systematic Survey

Reference 19

Resolution: unresolved; no resolver link, observed 2026-07-14T12:59:50.759055Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6c4888ed-fc61-4432-b14c-145e9db723cc · inbound

The Physics of Multi-Turn Long-Horizon Planning: From Pre-training to Post-training via Single- and Multi-Teacher On-Policy Agentic Distillation cites this paper.

The Physics of Multi-Turn Long-Horizon Planning: From Pre-training to Post-training via Single- and Multi-Teacher On-Policy Agentic Distillation Large Language Models for Planning: A Comprehensive and Systematic Survey

Reference 4

Resolution: unresolved; no resolver link, observed 2026-07-31T06:59:14.883715Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.