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Paper Citation Record · LEDGER

DeepLTL: Learning to Efficiently Satisfy Complex LTL Specifications for Multi-Task RL

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2410.04631.

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

pith.paper-citation-record.v1
2410.04631 v2

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 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T00:21:00.789293Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T18:00:01.579190Z

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 b0557c9d-dbb0-4581-9f16-45d2cc02ea83 · inbound

Automata-Conditioned Cooperative Multi-Agent Reinforcement Learning cites this paper.

Automata-Conditioned Cooperative Multi-Agent Reinforcement Learning DeepLTL: Learning to Efficiently Satisfy Complex LTL Specifications for Multi-Task RL

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-04T00:21:00.789293Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:21:00.789293Z digest=sha256:1569a6f9935538f766963ae89d8b492badc8ae7f6ed9033a85fb31a0c7f959e0

Observation 4b190ab5-f8a4-4dec-97d8-c8049758a57f · inbound

World Models in Pieces: Structural Certification for General Agents cites this paper.

World Models in Pieces: Structural Certification for General Agents DeepLTL: Learning to Efficiently Satisfy Complex LTL Specifications for Multi-Task RL

Reference 101

Resolution
verified exact
arxiv_id, observed 2026-07-04T18:00:01.580863Z

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=arxiv_source observed=2026-06-25T23:04:11.950176Z digest=sha256:b90e15e780a7498041858a2bda5db8cf51e26a1713a1f47e6be553650f0dff71