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Paper Citation Record · LEDGER

MedViLaM: A multimodal large language model with advanced generalizability and explainability for medical data understanding and generation

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2409.19684.

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

pith.paper-citation-record.v1
2409.19684 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 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 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T17:18:16.391750Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T22:37:26.494552Z

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 b1413c7a-f36c-43d1-a5c8-ca336a0980b3 · inbound

Toward a Vision-Language Foundation Model for Medical Data: Multimodal Dataset and Benchmarks for Vietnamese PET/CT Report Generation cites this paper.

Toward a Vision-Language Foundation Model for Medical Data: Multimodal Dataset and Benchmarks for Vietnamese PET/CT Report Generation MedViLaM: A multimodal large language model with advanced generalizability and explainability for medical data understanding and generation

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-04T13:51:49.772453Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T13:51:49.772453Z digest=sha256:b6e1a321f1819debc8e352d66e0f1e6952f1ec6998467af0f877944848f82e9d

Observation 2cbe650e-0647-49b3-9228-3165824af08d · inbound

XrayClaw: Cooperative-Competitive Multi-Agent Alignment for Trustworthy Chest X-ray Diagnosis cites this paper.

XrayClaw: Cooperative-Competitive Multi-Agent Alignment for Trustworthy Chest X-ray Diagnosis MedViLaM: A multimodal large language model with advanced generalizability and explainability for medical data understanding and generation

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-05-13T21:03:19.890099Z

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=pdf_text observed=2026-05-13T21:00:18.392949Z digest=sha256:3a92e1f1fed3b2f0a900c8f9a3b960032c78399f06bfe126cdf68f2c0cbdf36e

Observation d29316fa-8be9-4c72-b014-903201a6619c · inbound

Beyond Surrogate Gradients: Fully Differentiable Token Pruning for Vision-Language Models cites this paper.

Beyond Surrogate Gradients: Fully Differentiable Token Pruning for Vision-Language Models MedViLaM: A multimodal large language model with advanced generalizability and explainability for medical data understanding and generation

Reference 72

Resolution
metadata mismatch
arxiv_id, observed 2026-06-29T13:13:27.437713Z

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=pdf_text observed=2026-06-29T13:07:21.789901Z digest=sha256:da90dba19b6364d72a50b0ba372a159fdde78bc0551f4f187c816f99c83ebcba

Observation aa4ff03c-160e-4ba0-8136-cdd4168ab181 · inbound

A unified multi-task framework enables interpretable chest radiograph analysis cites this paper.

A unified multi-task framework enables interpretable chest radiograph analysis MedViLaM: A multimodal large language model with advanced generalizability and explainability for medical data understanding and generation

Reference 2

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T02:26:26.612820Z

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=pdf_text observed=2026-06-28T10:56:54.620852Z digest=sha256:623e7fab79cc9cbb5140ce1e77df977becdb6879a0baf69486598aca2d7d3528

Observation e912aa31-b58d-48ce-9fbc-db27f3656292 · inbound

Learnable Token Sparsification for Efficient Gigapixel Whole Slide Image Reasoning cites this paper.

Learnable Token Sparsification for Efficient Gigapixel Whole Slide Image Reasoning MedViLaM: A multimodal large language model with advanced generalizability and explainability for medical data understanding and generation

Reference 29

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T22:37:26.496193Z

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=pdf_text observed=2026-06-27T18:43:45.530986Z digest=sha256:54b0a2af4763c93651b4ef85b00ba1207ef8787bd5d45affdeeeba682dfd2d4c

Observation 66c42414-cee6-4ad4-b5b2-795048e0f53e · inbound

PathSelect: Sequential Token Selection for Whole Slide Pathology cites this paper.

PathSelect: Sequential Token Selection for Whole Slide Pathology MedViLaM: A multimodal large language model with advanced generalizability and explainability for medical data understanding and generation

Reference 33

Resolution
unresolved
no resolver link, observed 2026-07-30T17:15:34.947525Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T17:15:34.947525Z digest=sha256:c0dd7317fe7fd3ba65a0261c9219bc0e93f329f60ad3e267df0ad3e1e0a7232f

Observation d41fddf2-6438-4ff3-b61f-5f0f148e643f · inbound

DiffPrune: differentiable information throttling for token pruning in vision-language models cites this paper.

DiffPrune: differentiable information throttling for token pruning in vision-language models MedViLaM: A multimodal large language model with advanced generalizability and explainability for medical data understanding and generation

Reference 69

Resolution
unresolved
no resolver link, observed 2026-08-04T17:18:16.391750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T17:18:16.391750Z digest=sha256:443fc4c6f3dd4c3061119359023b08e273244961ae64adca334e6aa1732a2e2c