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Paper Citation Record · LEDGER

lambeq: An Efficient High-Level Python Library for Quantum NLP

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2110.04236.

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

pith.paper-citation-record.v1
2110.04236 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 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 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:13:44.004554Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T23:46:19.208777Z

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 211eca5f-b9f5-4572-89e8-5c349143b81f · inbound

Towards a Comparative Framework for Compositional AI Models cites this paper.

Towards a Comparative Framework for Compositional AI Models lambeq: An Efficient High-Level Python Library for Quantum NLP

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-06T22:13:44.004554Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T22:13:44.004554Z digest=sha256:c6fa604e1c8b80d2e1b0bedbcee2349b2ed123c0368d9a61833e5fbd9fbc067c

Observation 9f34cc0b-71fd-4d7c-adc5-37e2e26233c7 · inbound

A Rose by Any Other Name Would Smell as Sweet: Categorical Homotopy Theory for Large Language Models cites this paper.

A Rose by Any Other Name Would Smell as Sweet: Categorical Homotopy Theory for Large Language Models lambeq: An Efficient High-Level Python Library for Quantum NLP

Reference 32

Resolution
verified exact
local_arxiv, observed 2026-08-05T23:46:19.214211Z

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=2026-08-05T23:46:18.536986Z digest=sha256:836521f1c22dc173e440ac2d9b71576bc462bb3c60a46080687bca8343871c8d

Observation cc935c7d-52ed-4778-9748-81a62a2c41ed · inbound

Compositional Concept Generalization with Variational Quantum Circuits cites this paper.

Compositional Concept Generalization with Variational Quantum Circuits lambeq: An Efficient High-Level Python Library for Quantum NLP

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-04T18:59:29.616690Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T18:59:29.616690Z digest=sha256:0bf336555abc15c2092cdc5ce7982982608f9f990a9eb56138278b99fbb3bb3e

Observation c3b39a93-a9db-443b-ba06-cda5fd7769d7 · inbound

Quantum Compositional NLP for Arabic: Grammar, Morphology, and Word Sense in Circuit Topology cites this paper.

Quantum Compositional NLP for Arabic: Grammar, Morphology, and Word Sense in Circuit Topology lambeq: An Efficient High-Level Python Library for Quantum NLP

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-02T15:09:20.252311Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T15:09:20.252311Z digest=sha256:a42fa5307b3ddf9825db56cdb6fd6063e041618899bade53de27411fe24b8804

Observation b24e75a9-9a08-4e24-9d79-5cc8666458d3 · inbound

Extending the Frontiers of QNLP Beyond English: Grammar-Sensitive Pipeline for Hindi Sentiment Classification Using Compositional Quantum Models cites this paper.

Extending the Frontiers of QNLP Beyond English: Grammar-Sensitive Pipeline for Hindi Sentiment Classification Using Compositional Quantum Models lambeq: An Efficient High-Level Python Library for Quantum NLP

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-01T20:02:44.687832Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T20:02:44.687832Z digest=sha256:52041a6867b4c95a62beea64c9d5303af2435326bfb001e5c913bae1f91b1903