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Paper Citation Record · LEDGER

Learning to rank quantum circuits for hardware-optimized performance enhancement

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2404.06535.

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

pith.paper-citation-record.v1
2404.06535 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 2026-08-10T06:31:04.303077+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T22:59:01.279153Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T05:33:46.982585Z

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 d37ddccf-1c15-485c-a722-58684b52bea3 · inbound

Learning to Rank Tensor Network Contraction Plans for GPU-Accelerated Quantum Circuit Simulation cites this paper.

Learning to Rank Tensor Network Contraction Plans for GPU-Accelerated Quantum Circuit Simulation Learning to rank quantum circuits for hardware-optimized performance enhancement

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-07T22:59:01.279153Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T22:59:01.279153Z digest=sha256:56cd4d6a69177fee356dfefd358726c60e891f1831a41c4233c86e7f6769eefc

Observation 72dd2d3f-b258-4bd9-a2ce-e0897d08676b · inbound

Breaking Memory Bottlenecks in Quantum Control Systems for More Precise Experiments and Higher Throughput Computing cites this paper.

Breaking Memory Bottlenecks in Quantum Control Systems for More Precise Experiments and Higher Throughput Computing Learning to rank quantum circuits for hardware-optimized performance enhancement

Reference 16

Resolution
verified exact
local_arxiv, observed 2026-08-07T05:33:47.077428Z

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=2026-08-07T05:33:41.947874Z digest=sha256:6b6558ac56333ed723a06bc9d1aabe654c3b851b80cd47cc6cbee771783c7200