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Paper Citation Record · LEDGER

Can We Rely on LLM Agents to Draft Long-Horizon Plans? Let's Take TravelPlanner as an Example

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2408.06318.

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

pith.paper-citation-record.v1
2408.06318 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 2026-08-09T12:09:18.693370Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T11:08:27.736726Z

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 ab3cda2c-0269-4feb-8ee5-84b2931d9f5b · inbound

Large Language Model-Brained GUI Agents: A Survey cites this paper.

Large Language Model-Brained GUI Agents: A Survey Can We Rely on LLM Agents to Draft Long-Horizon Plans? Let's Take TravelPlanner as an Example

Reference 199

Resolution
verified exact
arxiv_id, observed 2026-05-19T11:08:27.738357Z

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=2026-05-19T11:08:27.472508Z digest=sha256:b38592863bccbd496cbf7b0b361c990af73082444e96c0b5739daf6af9c6c77c

Observation ba102412-81ed-451d-b514-10f05f590fb3 · inbound

LLMER: Crafting Interactive Extended Reality Worlds with JSON Data Generated by Large Language Models cites this paper.

LLMER: Crafting Interactive Extended Reality Worlds with JSON Data Generated by Large Language Models Can We Rely on LLM Agents to Draft Long-Horizon Plans? Let's Take TravelPlanner as an Example

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-09T12:09:18.693370Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T12:09:18.693370Z digest=sha256:8d4a3344d9727685ff6ee8645db4292056c4bac38889bc36f6d30be2e5ca5184

Observation 0b91cd9b-ab87-4a95-b070-b8200e55736f · inbound

Can LLM-Reasoning Models Replace Classical Planning? A Benchmark Study cites this paper.

Can LLM-Reasoning Models Replace Classical Planning? A Benchmark Study Can We Rely on LLM Agents to Draft Long-Horizon Plans? Let's Take TravelPlanner as an Example

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-06T10:45:59.509242Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T10:45:59.509242Z digest=sha256:c6844f2ed2c95d91bf1632888fde0f0816ebf58dd6e1fe4d9fff96a9c5494bcf

Observation aa0b98f1-1318-4c36-8ed9-70327ea31dc2 · inbound

LAD-VF: LLM-Automatic Differentiation Enables Fine-Tuning-Free Robot Planning from Formal Methods Feedback cites this paper.

LAD-VF: LLM-Automatic Differentiation Enables Fine-Tuning-Free Robot Planning from Formal Methods Feedback Can We Rely on LLM Agents to Draft Long-Horizon Plans? Let's Take TravelPlanner as an Example

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-04T15:47:10.833508Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T15:47:10.833508Z digest=sha256:d905b3fd6ebdad54ae3210d0a43f2f3e8ebd27524e8770457141da00e5ba32bc

Observation e9a77e71-43ce-43f9-847e-650816a47646 · inbound

Agentic AI Security: Threats, Defenses, Evaluation, and Open Challenges cites this paper.

Agentic AI Security: Threats, Defenses, Evaluation, and Open Challenges Can We Rely on LLM Agents to Draft Long-Horizon Plans? Let's Take TravelPlanner as an Example

Reference 249

Resolution
verified exact
arxiv_id, observed 2026-05-18T03:42:22.332279Z

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=2026-05-18T03:42:10.703369Z digest=sha256:6adff5855a2d116c6ce38040a1e50eb34216f3caab6eb186a6c7a3392e7b8397

Observation 0683704a-df7e-4836-a702-371e8831a05a · inbound

HiMAC: Hierarchical Macro-Micro Learning for Long-Horizon LLM Agents cites this paper.

HiMAC: Hierarchical Macro-Micro Learning for Long-Horizon LLM Agents Can We Rely on LLM Agents to Draft Long-Horizon Plans? Let's Take TravelPlanner as an Example

Reference 12

Resolution
metadata mismatch
arxiv_id, observed 2026-05-15T18:36:28.282741Z

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=2026-05-15T18:35:45.900606Z digest=sha256:14697384e1ceec59362cacd140a267d5bcc5e5976d622d3cd1897224fd1f69be

Observation f000cfeb-29fe-4f85-af88-a57b32e0228b · inbound

Decoupled Travel Planning with Behavior Forest cites this paper.

Decoupled Travel Planning with Behavior Forest Can We Rely on LLM Agents to Draft Long-Horizon Plans? Let's Take TravelPlanner as an Example

Reference 59

Resolution
verified exact
arxiv_id, observed 2026-05-09T22:54:16.259018Z

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=2026-05-09T22:52:05.428745Z digest=sha256:6e50b70c9c9da8d5b2e7a431878d4841f57e3da90cc631d63a2bdb9921a34553