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Paper Citation Record · LEDGER

A Deep Learning Framework for Disentangling Triangle Singularity and Pole-Based Enhancements

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2403.18265.

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

pith.paper-citation-record.v1
2403.18265 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:13:13.790199Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T17:50:00.794517Z

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 42b88a2d-e2bb-4486-87cb-4ee9153a4281 · inbound

Analysis of hidden-charm pentaquarks as triangle singularities via deep learning cites this paper.

Analysis of hidden-charm pentaquarks as triangle singularities via deep learning A Deep Learning Framework for Disentangling Triangle Singularity and Pole-Based Enhancements

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-12T15:39:34.334732Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T15:39:34.334732Z digest=sha256:096b5b7ac639661b38c4533565c99d474de54d434a9235b255e7c6c324f8ff26

Observation 33a7a4fa-98a5-49bd-9724-11c98e1aa905 · inbound

Line shape analysis of $\Lambda(1405)$ in $\gamma p \rightarrow K^+\Sigma^-\pi^+$ reaction using convolutional neural network cites this paper.

Line shape analysis of $\Lambda(1405)$ in $\gamma p \rightarrow K^+\Sigma^-\pi^+$ reaction using convolutional neural network A Deep Learning Framework for Disentangling Triangle Singularity and Pole-Based Enhancements

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T10:43:39.500667Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:43:39.500667Z digest=sha256:e696ef739f8ad7a404a01ac6477628be660d50832c580d7d8a635e62a73981db

Observation 24b3da50-e9f2-415f-beec-a2f1a24158cf · inbound

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification cites this paper.

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification A Deep Learning Framework for Disentangling Triangle Singularity and Pole-Based Enhancements

Reference 84

Resolution
unresolved
no resolver link, observed 2026-08-15T18:13:13.790199Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:13:13.790199Z digest=sha256:17822864efa695f6cf57f4cb466ed76522dc31c95902dc72d8f26576684ed749

Observation 80e6b9cd-5bb1-4127-a9cf-5ef141d4747d · inbound

Study of the molecular Properties of the $P_c$ and $P_{cs}$ States cites this paper.

Study of the molecular Properties of the $P_c$ and $P_{cs}$ States A Deep Learning Framework for Disentangling Triangle Singularity and Pole-Based Enhancements

Reference 68

Resolution
verified exact
arxiv_id, observed 2026-05-10T21:55:50.431691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-10T20:30:25.241387Z digest=sha256:4241156ce1140991f441f2ccc28b07b646356c118e59ea99b536c2bc9950f73d

Observation 25351ee1-538f-4c23-90ec-efc0c1b6d60c · inbound

The $a_1(1420)$ in a Unitary Coupled-Channel Three-Body Approach cites this paper.

The $a_1(1420)$ in a Unitary Coupled-Channel Three-Body Approach A Deep Learning Framework for Disentangling Triangle Singularity and Pole-Based Enhancements

Reference 72

Resolution
verified exact
arxiv_id, observed 2026-07-04T17:50:00.796236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-25T23:21:53.393768Z digest=sha256:c4a9bd07755cf7ba86ce4f09500d827687fa5821571282f24fd35342bf4eb6b2

Observation 753e8cc2-544d-46e0-aa35-3e83b3dc4bc1 · inbound

The $a_1(1420)$ in a Unitary Coupled-Channel Three-Body Approach cites this paper.

The $a_1(1420)$ in a Unitary Coupled-Channel Three-Body Approach A Deep Learning Framework for Disentangling Triangle Singularity and Pole-Based Enhancements

Reference 72

Resolution
unresolved
no resolver link, observed 2026-07-14T17:25:05.536989Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T17:25:05.536989Z digest=sha256:51123386f28fa32b257ddb4f6224ddab826291e694c680925ee42362d7bdaed0