Paper Citation Record · LEDGER

Identifying actionable driver mutations in lung cancer using an efficient Asymmetric Transformer Decoder

As of 20 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 0 inbound Pith citation observations for arXiv:2508.02431.

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

pith.paper-citation-record.v1
2508.02431 v3

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T04:59:49.390734Z

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

27 of 27 outbound references displayed

verified exact3
verified fuzzy20
unresolved4
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7927569e-db74-49ce-abd7-58fb5c89d99b · outbound

This paper cites Albertina, M.

Identifying actionable driver mutations in lung cancer using an efficient Asymmetric Transformer Decoder Albertina, M

Reference 1

Resolution: verified exact; doi, observed 2026-08-06T04:59:49.797152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0cf827b4-b325-471c-a86f-d7f8be6a6905 · outbound

This paper cites H&E-based Computational Biomarker Enables Universal EGFR Screening for Lung Adenocarcinoma.

Identifying actionable driver mutations in lung cancer using an efficient Asymmetric Transformer Decoder H&E-based Computational Biomarker Enables Universal EGFR Screening for Lung Adenocarcinoma

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-08-06T04:59:49.973934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2a6be34b-eb0b-4cea-a8d9-d0ff53fdb91f · outbound

This paper cites Polydorides, Adam J.

Identifying actionable driver mutations in lung cancer using an efficient Asymmetric Transformer Decoder Polydorides, Adam J

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:59:54.212634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation bcaeb8a1-140f-4abd-83d3-ef73725c565e · outbound

This paper cites Circulating tumor cell detection technologies and clinical utility: Challenges and opportunities.

Identifying actionable driver mutations in lung cancer using an efficient Asymmetric Transformer Decoder Circulating tumor cell detection technologies and clinical utility: Challenges and opportunities

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:59:53.920110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d894cf1c-d420-4517-aba1-9738d71cc1c0 · outbound

This paper cites The biology and management of non-small cell lung cancer.

Identifying actionable driver mutations in lung cancer using an efficient Asymmetric Transformer Decoder The biology and management of non-small cell lung cancer

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:59:53.677361Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation efc779d9-5ce2-4f8c-af79-4e17096f8421 · outbound

This paper cites Attention-based deep multiple instance learning.

Identifying actionable driver mutations in lung cancer using an efficient Asymmetric Transformer Decoder Attention-based deep multiple instance learning

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:59:53.471695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d51da743-40f0-45b1-b957-f0344ebb377c · outbound

This paper cites Benchmarking self-supervised learning on diverse pathology datasets.

Identifying actionable driver mutations in lung cancer using an efficient Asymmetric Transformer Decoder Benchmarking self-supervised learning on diverse pathology datasets

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:59:53.283820Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f755eaa4-5808-4a7a-b9a5-64edd02bd59a · outbound

This paper cites an unresolved cited work.

Identifying actionable driver mutations in lung cancer using an efficient Asymmetric Transformer Decoder Unresolved cited work

Reference 8

Resolution: verified exact; doi, observed 2026-08-06T04:59:49.555490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation bacdc744-2c47-4613-b4e7-e656fc6a146d · outbound

This paper cites Dynamic graph representation with knowledge-aware attention for histopathology whole slide image analysis.

Identifying actionable driver mutations in lung cancer using an efficient Asymmetric Transformer Decoder Dynamic graph representation with knowledge-aware attention for histopathology whole slide image analysis

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:59:53.150592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3d87f2ef-7d74-44cc-9ef5-adc71bc024b6 · outbound

This paper cites Semantics-aware attention guidance for diagnosing whole slide images.

Identifying actionable driver mutations in lung cancer using an efficient Asymmetric Transformer Decoder Semantics-aware attention guidance for diagnosing whole slide images

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:59:52.967579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6a9fa26f-8637-4b58-acbe-738802d05e3f · outbound

This paper cites Cury, Taiga Abe, Venkatesh N.

Identifying actionable driver mutations in lung cancer using an efficient Asymmetric Transformer Decoder Cury, Taiga Abe, Venkatesh N

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:59:52.742175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0904d616-f7c1-4076-8a54-96105e33f889 · outbound

This paper cites Lung cancer ldct screening and mortality reduction—evidence, pitfalls and future perspectives.

Identifying actionable driver mutations in lung cancer using an efficient Asymmetric Transformer Decoder Lung cancer ldct screening and mortality reduction—evidence, pitfalls and future perspectives

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:59:52.599717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3f23e0b2-5414-4b6d-9267-0e45978bebf3 · outbound

This paper cites Predicting egfr mutational status from pathology images using a real-world dataset.

Identifying actionable driver mutations in lung cancer using an efficient Asymmetric Transformer Decoder Predicting egfr mutational status from pathology images using a real-world dataset

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:59:52.374941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 8de01c86-28a5-45b1-ae8f-a9adc1338c9d · outbound

This paper cites Metastatic non-small cell lung cancer: Esmo clinical practice guidelines for diagnosis, treatment and follow-up.

Identifying actionable driver mutations in lung cancer using an efficient Asymmetric Transformer Decoder Metastatic non-small cell lung cancer: Esmo clinical practice guidelines for diagnosis, treatment and follow-up

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:59:52.242111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4ae8b054-07a8-4528-a24a-dca571eb54b1 · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation.

Identifying actionable driver mutations in lung cancer using an efficient Asymmetric Transformer Decoder U-net: Convolutional networks for biomedical image segmentation

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:59:52.040805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ff30dada-1696-472f-9b6e-07ce1a8ec22b · outbound

This paper cites H-optimus-0, 2024.

Identifying actionable driver mutations in lung cancer using an efficient Asymmetric Transformer Decoder H-optimus-0, 2024

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:59:51.830166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2f30860d-857f-44ce-98a2-9fe08937655e · outbound

This paper cites Transmil: Transformer based correlated multiple instance learning for whole slide image classification.

Identifying actionable driver mutations in lung cancer using an efficient Asymmetric Transformer Decoder Transmil: Transformer based correlated multiple instance learning for whole slide image classification

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:59:51.664774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9eb3073f-7ff4-4807-9c3d-6af49618638e · outbound

This paper cites Vila-mil: Dual-scale vision-language multiple instance learning for whole slide image classification.

Identifying actionable driver mutations in lung cancer using an efficient Asymmetric Transformer Decoder Vila-mil: Dual-scale vision-language multiple instance learning for whole slide image classification

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:59:51.445130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 44b48c75-4308-45a8-bdb7-c3139ad66628 · outbound

This paper cites Integrative graph-transformer framework for histopathology whole slide image representation and classification.

Identifying actionable driver mutations in lung cancer using an efficient Asymmetric Transformer Decoder Integrative graph-transformer framework for histopathology whole slide image representation and classification

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:59:51.238545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ea5800e7-e764-4f22-9146-ebf00f254577 · outbound

This paper cites Artificial intelligence in histopathology: enhancing cancer research and clinical oncology.

Identifying actionable driver mutations in lung cancer using an efficient Asymmetric Transformer Decoder Artificial intelligence in histopathology: enhancing cancer research and clinical oncology

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:59:50.991036Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 78bfc9dc-807d-4b48-9588-53ef82584f41 · outbound

This paper cites Attention is all you need.

Identifying actionable driver mutations in lung cancer using an efficient Asymmetric Transformer Decoder Attention is all you need

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T04:59:48.802675Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8c8f3ecd-6cc0-43e8-aabd-a11cbad3e96f · outbound

This paper cites an unresolved cited work.

Identifying actionable driver mutations in lung cancer using an efficient Asymmetric Transformer Decoder Unresolved cited work

Reference 22

Resolution: unresolved; raw_fallback, observed 2026-08-06T04:59:50.814118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation be77c6cf-5c17-4b13-aaa2-a55647a1aab9 · outbound

This paper cites Transformer-based biomarker prediction from colorectal cancer histology: A large-scale multicentric study.

Identifying actionable driver mutations in lung cancer using an efficient Asymmetric Transformer Decoder Transformer-based biomarker prediction from colorectal cancer histology: A large-scale multicentric study

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:59:50.629716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2fee968c-2df4-48d5-86cf-a16347c1b1a9 · outbound

This paper cites Mambamil: Enhancing long sequence modeling with sequence reordering in computational pathology.

Identifying actionable driver mutations in lung cancer using an efficient Asymmetric Transformer Decoder Mambamil: Enhancing long sequence modeling with sequence reordering in computational pathology

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:59:50.432108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c10537d9-c7ca-48dc-80a5-9d70f3191575 · outbound

This paper cites EXAONEPath 1.0 Patch-level Foundation Model for Pathology.

Identifying actionable driver mutations in lung cancer using an efficient Asymmetric Transformer Decoder EXAONEPath 1.0 Patch-level Foundation Model for Pathology

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T04:59:49.164637Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c942fdd1-0f2f-45ec-bb82-c6df34cf1a1d · outbound

This paper cites Dynamic policy-driven adaptive multi-instance learning for whole slide image classification.

Identifying actionable driver mutations in lung cancer using an efficient Asymmetric Transformer Decoder Dynamic policy-driven adaptive multi-instance learning for whole slide image classification

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:59:50.238319Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1663ceed-b19d-432b-813f-7514993889ab · outbound

This paper cites A graph-transformer for whole slide image classification.

Identifying actionable driver mutations in lung cancer using an efficient Asymmetric Transformer Decoder A graph-transformer for whole slide image classification

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T04:59:49.390734Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.