Paper Citation Record · LEDGER

LLM-State: Open World State Representation for Long-horizon Task Planning with Large Language Model

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2311.17406.

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

pith.paper-citation-record.v1
2311.17406 v2

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 2026-08-07T11:50:01.342560Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T04:49:44.456653Z

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 bfd99e42-5c10-43fa-b028-5d9ee30ea70c · inbound

Agentic Episodic Control cites this paper.

Agentic Episodic Control LLM-State: Open World State Representation for Long-horizon Task Planning with Large Language Model

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-07T11:50:01.342560Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b08448d1-44ab-41dd-a36a-d330f25006b9 · inbound

Any House Any Task: Scalable Long-Horizon Planning for Abstract Human Tasks cites this paper.

Any House Any Task: Scalable Long-Horizon Planning for Abstract Human Tasks LLM-State: Open World State Representation for Long-horizon Task Planning with Large Language Model

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-04T06:05:29.269978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b2f0e68b-bcf7-44e9-960c-ff1562a273bf · inbound

Grounded Continuation: A Linear-Time Runtime Verifier for LLM Conversations cites this paper.

Grounded Continuation: A Linear-Time Runtime Verifier for LLM Conversations LLM-State: Open World State Representation for Long-horizon Task Planning with Large Language Model

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-15T04:49:44.459931Z

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.

Observation 771d3651-b048-4cc6-a8c7-a069c6a5427d · inbound

Mimir: A Neuro-Symbolic Memory System with Dynamic Grounding for Embodied Agents in Interactive Environments cites this paper.

Mimir: A Neuro-Symbolic Memory System with Dynamic Grounding for Embodied Agents in Interactive Environments LLM-State: Open World State Representation for Long-horizon Task Planning with Large Language Model

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T13:38:29.234955Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.