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Paper Citation Record · LEDGER

Domain-Aware Machine Learning for Accelerating MILP-Based Motion Planning with Temporal Logic and Chance Constraints

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2508.07515.

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

pith.paper-citation-record.v1
2508.07515 v3

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 2026-08-10T06:31:04.303077+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T08:19:20.308277Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-05-17T00:01:22.833543Z

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 45ec94ce-4b2d-405a-bcf0-63547f99b10a · inbound

ID-PaS+ : Identity-Aware Predict-and-Search for General Mixed-Integer Linear Programs cites this paper.

ID-PaS+ : Identity-Aware Predict-and-Search for General Mixed-Integer Linear Programs Domain-Aware Machine Learning for Accelerating MILP-Based Motion Planning with Temporal Logic and Chance Constraints

Reference 8

Resolution
metadata mismatch
local_arxiv, observed 2026-05-17T00:01:22.839891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-17T00:00:17.759979Z digest=sha256:0e3a62c7786448160d3180906331ebdb7e5080aa7736e3f55f2046d02c997954

Observation ff80655f-07de-4c17-9b0b-c2df770e7a7f · inbound

FunL2O: LLM-Guided Feature Function Design for Learning to Optimize cites this paper.

FunL2O: LLM-Guided Feature Function Design for Learning to Optimize Domain-Aware Machine Learning for Accelerating MILP-Based Motion Planning with Temporal Logic and Chance Constraints

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-01T08:19:20.308277Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T08:19:20.308277Z digest=sha256:4ee1ae369dbe97109b3fd4948a6e8f82b1b5203889cd430c3d944437947da353