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Paper Citation Record · LEDGER

PathAsst: A Generative Foundation AI Assistant Towards Artificial General Intelligence of Pathology

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2305.15072.

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

pith.paper-citation-record.v1
2305.15072 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 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 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T11:34:08.888459Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T23:06:21.175652Z

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 87dac7a1-cba4-4fbc-b115-d3160540c54f · inbound

Data-Centric Foundation Models in Computational Healthcare: A Survey cites this paper.

Data-Centric Foundation Models in Computational Healthcare: A Survey PathAsst: A Generative Foundation AI Assistant Towards Artificial General Intelligence of Pathology

Reference 281

Resolution
verified exact
arxiv_id, observed 2026-05-24T04:13:52.721059Z

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=2026-05-24T04:13:05.328492Z digest=sha256:94c3c2e9065741b063a7033daef5333ca8301aa8fa30c43cb643f25525d990e2

Observation b145ddc4-2660-4a62-a73f-c0b2791b5796 · inbound

Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription cites this paper.

Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription PathAsst: A Generative Foundation AI Assistant Towards Artificial General Intelligence of Pathology

Reference 70

Resolution
unresolved
no resolver link, observed 2026-08-09T11:34:08.888459Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T11:34:08.888459Z digest=sha256:224874e7e71e1ddc3603579e143bf5d425aa4a91daf601b87c3007429f7301af

Observation 079f2254-1d02-4f8e-a3f0-bbcddf8eca62 · inbound

Contrastive Regularization over LoRA for Multimodal Biomedical Image Incremental Learning cites this paper.

Contrastive Regularization over LoRA for Multimodal Biomedical Image Incremental Learning PathAsst: A Generative Foundation AI Assistant Towards Artificial General Intelligence of Pathology

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-05T23:08:16.582815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T23:08:16.582815Z digest=sha256:3f34546c4046aa7b8d71c837b4b447bc8220a130ed0795189dc3a5e6a2ca6380

Observation 4b232d4e-ed5c-43c4-bdb2-0c6aabe24215 · inbound

AutoMedBench: Towards Medical AutoResearch with Agentic AI Models cites this paper.

AutoMedBench: Towards Medical AutoResearch with Agentic AI Models PathAsst: A Generative Foundation AI Assistant Towards Artificial General Intelligence of Pathology

Reference 71

Resolution
verified exact
arxiv_id, observed 2026-07-01T23:06:21.179269Z

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=2026-06-28T14:38:40.017263Z digest=sha256:728448ede2458d2222db20fa89e12292e81db7e0e2c635aee6aaa964dfb664c7