{"as_of":"2026-08-08T07:00:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:72501c5c09f4dd386eb0ee28b7faabaf933ea955c7ad0ace96de3b41fb190503","coverage":[{"denominator":38,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":38,"source":"paper_references, paper_reference_links","source_observed_at":"2026-06-27T01:50:30.097327Z","state":"measured"},{"denominator":38,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":38,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2606.18123/citation-record","integrity":"/paper/2606.18123/integrity","json":"/paper/2606.18123/citation-record.json","paper":"/paper/2606.18123"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T01:50:30.097327Z","title":"Chemokines in the cancer microenviron- ment and their relevance in cancer immunotherapy.Nature Reviews Immunology, 17(9):559– 572, 2017","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2606.18123","last_updated":"2026-06-20T16:00:00Z","snapshot_observed_at":"2026-08-07T17:11:23.888737Z","submitted_at":"2026-06-16T16:22:42Z","title":"Predicting Immune Biomarkers with MultiModal Mixture-of-Expert Pathology Foundation Models Empowers Precision Oncology","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-06-27T01:50:30.097327Z"},"links":{"citing_paper":"/paper/2606.18123"},"observation_digest":"sha256:1f4f064ac1f9154410db04003824bfbbdc5d47563c9fc9555ad6b89bf2c0b525","observation_id":"414c3985-9cef-4166-8ef1-c9de7a29533d","resolution":{"observed_at":"2026-06-27T01:50:30.097327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T01:50:30.097327Z","title":"Immunotherapy and the ovarian cancer microenvironment: exploring potential strate- gies for enhanced treatment efficacy.Immunology, 173(1):14–32, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.18123","last_updated":"2026-06-20T16:00:00Z","snapshot_observed_at":"2026-08-07T17:11:23.888737Z","submitted_at":"2026-06-16T16:22:42Z","title":"Predicting Immune Biomarkers with MultiModal Mixture-of-Expert Pathology Foundation Models Empowers Precision Oncology","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-06-27T01:50:30.097327Z"},"links":{"citing_paper":"/paper/2606.18123"},"observation_digest":"sha256:351a11d1913ddbd8dc9858f2174256edc0ef16a0b165f4cf37916957d69c0872","observation_id":"9a221113-169d-4327-9803-457b836190a1","resolution":{"observed_at":"2026-06-27T01:50:30.097327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T01:50:30.097327Z","title":"Conserved pan-cancer mi- croenvironment subtypes predict response to immunotherapy.Cancer cell, 39(6):845–865, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2606.18123","last_updated":"2026-06-20T16:00:00Z","snapshot_observed_at":"2026-08-07T17:11:23.888737Z","submitted_at":"2026-06-16T16:22:42Z","title":"Predicting Immune Biomarkers with MultiModal Mixture-of-Expert Pathology Foundation Models Empowers Precision Oncology","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-06-27T01:50:30.097327Z"},"links":{"citing_paper":"/paper/2606.18123"},"observation_digest":"sha256:777a65128244521e075070c7e609e9c6df36493cf1f3e1cf78ffe631ae67ab0d","observation_id":"a5cfbb1a-f83b-401f-9fc9-fc6d4b0827a0","resolution":{"observed_at":"2026-06-27T01:50:30.097327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T01:50:30.097327Z","title":"Computer- aided prognosis on breast cancer with hematoxylin and eosin histopathology images: A review","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2606.18123","last_updated":"2026-06-20T16:00:00Z","snapshot_observed_at":"2026-08-07T17:11:23.888737Z","submitted_at":"2026-06-16T16:22:42Z","title":"Predicting Immune Biomarkers with MultiModal Mixture-of-Expert Pathology Foundation Models Empowers Precision Oncology","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-06-27T01:50:30.097327Z"},"links":{"citing_paper":"/paper/2606.18123"},"observation_digest":"sha256:de64eab345ca345703f72defa622f9e4bfdb16e3f60369e456044d9ce7fb2f24","observation_id":"efdcf8e1-7216-456f-9926-4fc54350704e","resolution":{"observed_at":"2026-06-27T01:50:30.097327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T01:50:30.097327Z","title":"Understanding the tumor immune microenvironment (time) for effective ther- apy.Nature medicine, 24(5):541–550, 2018","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2606.18123","last_updated":"2026-06-20T16:00:00Z","snapshot_observed_at":"2026-08-07T17:11:23.888737Z","submitted_at":"2026-06-16T16:22:42Z","title":"Predicting Immune Biomarkers with MultiModal Mixture-of-Expert Pathology Foundation Models Empowers Precision Oncology","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-06-27T01:50:30.097327Z"},"links":{"citing_paper":"/paper/2606.18123"},"observation_digest":"sha256:f4f310d346404ff019e4206b7f8e50323510c75e8e40f68dcaaa0bb10114a124","observation_id":"dcd80cd2-62fb-4fc7-aa25-aefa0f3b861b","resolution":{"observed_at":"2026-06-27T01:50:30.097327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T01:50:30.097327Z","title":"Multimodal ai generates virtual population for tumor microenvironment modeling.Cell, 189(2):386–400, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2606.18123","last_updated":"2026-06-20T16:00:00Z","snapshot_observed_at":"2026-08-07T17:11:23.888737Z","submitted_at":"2026-06-16T16:22:42Z","title":"Predicting Immune Biomarkers with MultiModal Mixture-of-Expert Pathology Foundation Models Empowers Precision Oncology","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-06-27T01:50:30.097327Z"},"links":{"citing_paper":"/paper/2606.18123"},"observation_digest":"sha256:24cdbd07d13cd2346cbe6cf7708d29b505576055a8e718286edaef7abcaf17e1","observation_id":"935cea40-b399-4fa4-8250-c00bbc3b5073","resolution":{"observed_at":"2026-06-27T01:50:30.097327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T01:50:30.097327Z","title":"Stpath: a generative foundation model for integrating spatial transcriptomics and whole-slide images.NPJ Digital Medicine, 8(1):659, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.18123","last_updated":"2026-06-20T16:00:00Z","snapshot_observed_at":"2026-08-07T17:11:23.888737Z","submitted_at":"2026-06-16T16:22:42Z","title":"Predicting Immune Biomarkers with MultiModal Mixture-of-Expert Pathology Foundation Models Empowers Precision Oncology","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-06-27T01:50:30.097327Z"},"links":{"citing_paper":"/paper/2606.18123"},"observation_digest":"sha256:38ffc66fb5bfa5e36a2a88b9f4ab24b77449effbdfa4b92ad018c526838851f4","observation_id":"de6e69e4-9bd8-4af7-a218-9937b236f412","resolution":{"observed_at":"2026-06-27T01:50:30.097327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T01:50:30.097327Z","title":"Leveraging multi-modal foundation models for analysing spatial multi-omic and histopathology data.Nature Biomedical Engineering, pages 1–18, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2606.18123","last_updated":"2026-06-20T16:00:00Z","snapshot_observed_at":"2026-08-07T17:11:23.888737Z","submitted_at":"2026-06-16T16:22:42Z","title":"Predicting Immune Biomarkers with MultiModal Mixture-of-Expert Pathology Foundation Models Empowers Precision Oncology","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-06-27T01:50:30.097327Z"},"links":{"citing_paper":"/paper/2606.18123"},"observation_digest":"sha256:522d9387b8ed906dfec54274ded779f7c624ccb1377de6208cdc27e1ce6b2c39","observation_id":"cebafc0a-a7f3-4fea-8741-296b3eb9bab7","resolution":{"observed_at":"2026-06-27T01:50:30.097327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T01:50:30.097327Z","title":"A visual–omics foundation model to bridge histopathology with spatial transcriptomics.Nature Methods, 22(7):1568–1582, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.18123","last_updated":"2026-06-20T16:00:00Z","snapshot_observed_at":"2026-08-07T17:11:23.888737Z","submitted_at":"2026-06-16T16:22:42Z","title":"Predicting Immune Biomarkers with MultiModal Mixture-of-Expert Pathology Foundation Models Empowers Precision Oncology","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-06-27T01:50:30.097327Z"},"links":{"citing_paper":"/paper/2606.18123"},"observation_digest":"sha256:4af462b4a48395f194087d2f410314ad82f0b55361a453648c48536b6ca1c7cc","observation_id":"c2e4ad85-2758-4db2-a088-e8b8dd04dd10","resolution":{"observed_at":"2026-06-27T01:50:30.097327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T01:50:30.097327Z","title":"A visual-language foundation model for computational pathology.Nature medicine, 30(3):863–874, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.18123","last_updated":"2026-06-20T16:00:00Z","snapshot_observed_at":"2026-08-07T17:11:23.888737Z","submitted_at":"2026-06-16T16:22:42Z","title":"Predicting Immune Biomarkers with MultiModal Mixture-of-Expert Pathology Foundation Models Empowers Precision Oncology","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-06-27T01:50:30.097327Z"},"links":{"citing_paper":"/paper/2606.18123"},"observation_digest":"sha256:147adb17104cb17d806ae2b2a58df0b2edccfd5d839387fc3a0ad4b680bce99a","observation_id":"b391be21-d84c-43ed-b418-c2b5ce853f43","resolution":{"observed_at":"2026-06-27T01:50:30.097327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T01:50:30.097327Z","title":"Immunofluorescence techniques.Journal of Investigative Der- matology, 133(1):1–4, 2013","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2606.18123","last_updated":"2026-06-20T16:00:00Z","snapshot_observed_at":"2026-08-07T17:11:23.888737Z","submitted_at":"2026-06-16T16:22:42Z","title":"Predicting Immune Biomarkers with MultiModal Mixture-of-Expert Pathology Foundation Models Empowers Precision Oncology","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-06-27T01:50:30.097327Z"},"links":{"citing_paper":"/paper/2606.18123"},"observation_digest":"sha256:536babf601105d76db909d5ede7800d072f0fc6d9b9d1bcb408ca3fed694708a","observation_id":"9c2d91f2-bd3a-447e-9cac-988d56300474","resolution":{"observed_at":"2026-06-27T01:50:30.097327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T01:50:30.097327Z","title":"Miphei-vit: Multiplex immunofluorescence prediction from h&e images using vit foundation models.Computers in Biology and Medicine, 206:111564, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2606.18123","last_updated":"2026-06-20T16:00:00Z","snapshot_observed_at":"2026-08-07T17:11:23.888737Z","submitted_at":"2026-06-16T16:22:42Z","title":"Predicting Immune Biomarkers with MultiModal Mixture-of-Expert Pathology Foundation Models Empowers Precision Oncology","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-06-27T01:50:30.097327Z"},"links":{"citing_paper":"/paper/2606.18123"},"observation_digest":"sha256:ca83a7f09f3cbc467576f06e05e0735928276946b9039bed15acc88763445665","observation_id":"e3a92416-8dc7-460b-8a95-ea0fc8135d84","resolution":{"observed_at":"2026-06-27T01:50:30.097327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T01:50:30.097327Z","title":"Rosie: Ai gener- ation of multiplex immunofluorescence staining from histopathology images.Nature Commu- nications, 16(1):7633, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.18123","last_updated":"2026-06-20T16:00:00Z","snapshot_observed_at":"2026-08-07T17:11:23.888737Z","submitted_at":"2026-06-16T16:22:42Z","title":"Predicting Immune Biomarkers with MultiModal Mixture-of-Expert Pathology Foundation Models Empowers Precision Oncology","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-06-27T01:50:30.097327Z"},"links":{"citing_paper":"/paper/2606.18123"},"observation_digest":"sha256:2387f3752b3089df41118f1b553ef714ffcbc0c254bd0083a94809c0f11a4adb","observation_id":"3d309442-8dc9-456b-a7d2-7dd0bc385a65","resolution":{"observed_at":"2026-06-27T01:50:30.097327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T01:50:30.097327Z","title":"Ai-enabled virtual spatial proteomics from histopathol- ogy for interpretable biomarker discovery in lung cancer.Nature Medicine, pages 1–14, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2606.18123","last_updated":"2026-06-20T16:00:00Z","snapshot_observed_at":"2026-08-07T17:11:23.888737Z","submitted_at":"2026-06-16T16:22:42Z","title":"Predicting Immune Biomarkers with MultiModal Mixture-of-Expert Pathology Foundation Models Empowers Precision Oncology","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-06-27T01:50:30.097327Z"},"links":{"citing_paper":"/paper/2606.18123"},"observation_digest":"sha256:ede2e280e2674b34a7d1e3da3023fc3883694b34fc3b86c0b1a78d8edd289400","observation_id":"826ca200-e005-47d3-a5f4-6cdce5942bf9","resolution":{"observed_at":"2026-06-27T01:50:30.097327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1701.06538","last_updated":"2017-01-23T18:10:00Z","snapshot_observed_at":"2026-07-06T05:27:13.416519Z","submitted_at":"2017-01-23T18:10:00Z","title":"Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer","version":1},"cited_work":{"arxiv_id":"1701.06538","doi":"10.48550/arxiv.1701.06538","metadata_source":"pith","pith_arxiv_id":"1701.06538","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer","venue":"cs.LG","work_id":"2c6b3f6d-54e4-4df7-baa7-475a490799af","year":2017},"citing_paper":{"arxiv_id":"2606.18123","last_updated":"2026-06-20T16:00:00Z","snapshot_observed_at":"2026-08-07T17:11:23.888737Z","submitted_at":"2026-06-16T16:22:42Z","title":"Predicting Immune Biomarkers with MultiModal Mixture-of-Expert Pathology Foundation Models Empowers Precision Oncology","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-06-27T01:50:30.097327Z"},"links":{"cited_paper":"/paper/1701.06538","citing_paper":"/paper/2606.18123"},"observation_digest":"sha256:05a4c27826d510d7051334ed33de448b1a434f00d827e5a20816a6493bd8b790","observation_id":"ebfc74a6-b842-40bc-9589-519e06d008a5","resolution":{"observed_at":"2026-07-03T19:28:52.312968Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-01T08:08:24.174744+00:00","source":"crossref_status_cache"},{"observed_at":"2026-08-01T08:08:24.174744+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T01:50:30.097327Z","title":"Towardsageneral- purpose foundation model for computational pathology.Nature medicine, 30(3):850–862, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.18123","last_updated":"2026-06-20T16:00:00Z","snapshot_observed_at":"2026-08-07T17:11:23.888737Z","submitted_at":"2026-06-16T16:22:42Z","title":"Predicting Immune Biomarkers with MultiModal Mixture-of-Expert Pathology Foundation Models Empowers Precision Oncology","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-06-27T01:50:30.097327Z"},"links":{"citing_paper":"/paper/2606.18123"},"observation_digest":"sha256:af554ae489ad0d738142668d5ada891fdf6287e44c863fac720ca69bb1380f7a","observation_id":"0505ccd0-659b-44d4-897f-5582cb78c8e4","resolution":{"observed_at":"2026-06-27T01:50:30.097327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T01:50:30.097327Z","title":"Hemit: H&e to multiplex- immunohistochemistry image translation with dual-branch pix2pix generator","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.18123","last_updated":"2026-06-20T16:00:00Z","snapshot_observed_at":"2026-08-07T17:11:23.888737Z","submitted_at":"2026-06-16T16:22:42Z","title":"Predicting Immune Biomarkers with MultiModal Mixture-of-Expert Pathology Foundation Models Empowers Precision Oncology","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-06-27T01:50:30.097327Z"},"links":{"citing_paper":"/paper/2606.18123"},"observation_digest":"sha256:6ff9d19678673985bb74bf08032bab30b6a8b8e851987ac69d6f604f87cb7846","observation_id":"03e7210a-3477-4763-8f98-796db57fa0a3","resolution":{"observed_at":"2026-06-27T01:50:30.097327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T01:50:30.097327Z","title":"High-plex immunofluores- cence imaging and traditional histology of the same tissue section for discovering image-based biomarkers.Nature cancer, 4(7):1036–1052, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.18123","last_updated":"2026-06-20T16:00:00Z","snapshot_observed_at":"2026-08-07T17:11:23.888737Z","submitted_at":"2026-06-16T16:22:42Z","title":"Predicting Immune Biomarkers with MultiModal Mixture-of-Expert Pathology Foundation Models Empowers Precision Oncology","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-06-27T01:50:30.097327Z"},"links":{"citing_paper":"/paper/2606.18123"},"observation_digest":"sha256:1c19bc61ea38653c73f77630448506f73a30d4f3c1faa1696b080d29c0ea372b","observation_id":"cfc6aa44-97b5-41a9-b02b-c5c3794031bf","resolution":{"observed_at":"2026-06-27T01:50:30.097327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T01:50:30.097327Z","title":"Curran Associates Inc., Red Hook, NY, USA, 2019","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2606.18123","last_updated":"2026-06-20T16:00:00Z","snapshot_observed_at":"2026-08-07T17:11:23.888737Z","submitted_at":"2026-06-16T16:22:42Z","title":"Predicting Immune Biomarkers with MultiModal Mixture-of-Expert Pathology Foundation Models Empowers Precision Oncology","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-06-27T01:50:30.097327Z"},"links":{"citing_paper":"/paper/2606.18123"},"observation_digest":"sha256:32f5daf51654bc43011d66cb5457c85b55e3e6571679d77e76bf27878112b541","observation_id":"cf8f2b00-a8cb-456a-b774-8eb63b9a1918","resolution":{"observed_at":"2026-06-27T01:50:30.097327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T01:50:30.097327Z","title":"Unicorn: Towards universal cellular expression prediction with a multi-task learning framework.Nature Communications, 16(1):9455, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.18123","last_updated":"2026-06-20T16:00:00Z","snapshot_observed_at":"2026-08-07T17:11:23.888737Z","submitted_at":"2026-06-16T16:22:42Z","title":"Predicting Immune Biomarkers with MultiModal Mixture-of-Expert Pathology Foundation Models Empowers Precision Oncology","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-06-27T01:50:30.097327Z"},"links":{"citing_paper":"/paper/2606.18123"},"observation_digest":"sha256:8f530e39743f9260c48b8cb2fed96afa27de7f454c7b50d72e76ac15fbc88b5a","observation_id":"d9f3dae2-162b-4e54-ac0e-0444582d8070","resolution":{"observed_at":"2026-06-27T01:50:30.097327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T01:50:30.097327Z","title":"Stimage- 1k4m: A histopathology image-gene expression dataset for spatial transcriptomics.Advances in neural information processing systems, 37:35796–35823, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.18123","last_updated":"2026-06-20T16:00:00Z","snapshot_observed_at":"2026-08-07T17:11:23.888737Z","submitted_at":"2026-06-16T16:22:42Z","title":"Predicting Immune Biomarkers with MultiModal Mixture-of-Expert Pathology Foundation Models Empowers Precision Oncology","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-06-27T01:50:30.097327Z"},"links":{"citing_paper":"/paper/2606.18123"},"observation_digest":"sha256:a88b34fbf31f77807cdeccfcd195fee7cd8e2042d6e965561fcbf5efe20b4b33","observation_id":"f58b1dd6-b9a6-45d3-981d-b86daf799a04","resolution":{"observed_at":"2026-06-27T01:50:30.097327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T01:50:30.097327Z","title":"Scikit- learn: Machine learning in python.the Journal of machine Learning research, 12:2825–2830, 2011","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2606.18123","last_updated":"2026-06-20T16:00:00Z","snapshot_observed_at":"2026-08-07T17:11:23.888737Z","submitted_at":"2026-06-16T16:22:42Z","title":"Predicting Immune Biomarkers with MultiModal Mixture-of-Expert Pathology Foundation Models Empowers Precision Oncology","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-06-27T01:50:30.097327Z"},"links":{"citing_paper":"/paper/2606.18123"},"observation_digest":"sha256:4aa5dc3454b6ed377359cb855e37dd985fe9e0db11817e2e81493845ac645226","observation_id":"f3e99415-a823-4cd8-9624-a09997f09020","resolution":{"observed_at":"2026-06-27T01:50:30.097327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T01:50:30.097327Z","title":"Accurate spatial gene expression prediction by integrating multi-resolution features","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.18123","last_updated":"2026-06-20T16:00:00Z","snapshot_observed_at":"2026-08-07T17:11:23.888737Z","submitted_at":"2026-06-16T16:22:42Z","title":"Predicting Immune Biomarkers with MultiModal Mixture-of-Expert Pathology Foundation Models Empowers Precision Oncology","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-06-27T01:50:30.097327Z"},"links":{"citing_paper":"/paper/2606.18123"},"observation_digest":"sha256:25a7238ea5a99d44e527f222cbd00ff378735f9d444a284532a5e6edb95a14a0","observation_id":"abffd1c1-59e7-4af9-a7d3-ffd0c01a514a","resolution":{"observed_at":"2026-06-27T01:50:30.097327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T01:50:30.097327Z","title":"Spatially resolved gene expression prediction from histology images via bi-modal con- trastive learning.Advances in Neural Information Processing Systems, 36:70626–70637, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.18123","last_updated":"2026-06-20T16:00:00Z","snapshot_observed_at":"2026-08-07T17:11:23.888737Z","submitted_at":"2026-06-16T16:22:42Z","title":"Predicting Immune Biomarkers with MultiModal Mixture-of-Expert Pathology Foundation Models Empowers Precision Oncology","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-06-27T01:50:30.097327Z"},"links":{"citing_paper":"/paper/2606.18123"},"observation_digest":"sha256:20969c5aee274726b7f89c20f41f48bb72d08a2e1ff971ecc3e4bd4b191fb896","observation_id":"3c286c17-786b-4e8a-bbc9-4bfa5b9bd551","resolution":{"observed_at":"2026-06-27T01:50:30.097327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T01:50:30.097327Z","title":"A whole-slide foundation model for digital pathology from real-world data.Nature, 630(8015):181–188, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.18123","last_updated":"2026-06-20T16:00:00Z","snapshot_observed_at":"2026-08-07T17:11:23.888737Z","submitted_at":"2026-06-16T16:22:42Z","title":"Predicting Immune Biomarkers with MultiModal Mixture-of-Expert Pathology Foundation Models Empowers Precision Oncology","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-06-27T01:50:30.097327Z"},"links":{"citing_paper":"/paper/2606.18123"},"observation_digest":"sha256:ce39bc6edae8111f792152ab467d45f016460bd01edf4b8d81b27bf7f4003d95","observation_id":"83504b96-5467-494f-b513-bf8d2d04396e","resolution":{"observed_at":"2026-06-27T01:50:30.097327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T01:50:30.097327Z","title":"The cancer imaging archive (tcia): maintaining and operating a public information repository.Journal of digital imaging, 26(6):1045–1057, 2013","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2606.18123","last_updated":"2026-06-20T16:00:00Z","snapshot_observed_at":"2026-08-07T17:11:23.888737Z","submitted_at":"2026-06-16T16:22:42Z","title":"Predicting Immune Biomarkers with MultiModal Mixture-of-Expert Pathology Foundation Models Empowers Precision Oncology","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-06-27T01:50:30.097327Z"},"links":{"citing_paper":"/paper/2606.18123"},"observation_digest":"sha256:22a0130b95faefabd490f69244d3638889e6e5cff01f7fb7fb9c2619d45db776","observation_id":"c2ab9cd9-c498-458c-a416-88a18f5307b8","resolution":{"observed_at":"2026-06-27T01:50:30.097327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T01:50:30.097327Z","title":"Cancer-induced nerve injury promotes resistance to anti-pd-1 therapy.Nature, 646(8084):462–473, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.18123","last_updated":"2026-06-20T16:00:00Z","snapshot_observed_at":"2026-08-07T17:11:23.888737Z","submitted_at":"2026-06-16T16:22:42Z","title":"Predicting Immune Biomarkers with MultiModal Mixture-of-Expert Pathology Foundation Models Empowers Precision Oncology","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-06-27T01:50:30.097327Z"},"links":{"citing_paper":"/paper/2606.18123"},"observation_digest":"sha256:35a1862abece912199b5ffe844914af40b373d0434154cfcde5af935650f750a","observation_id":"3a775a62-6581-4019-a271-e902f978196d","resolution":{"observed_at":"2026-06-27T01:50:30.097327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T01:50:30.097327Z","title":"Regulatory t cells and foxp3.Immunological reviews, 241(1):260–268, 2011","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2606.18123","last_updated":"2026-06-20T16:00:00Z","snapshot_observed_at":"2026-08-07T17:11:23.888737Z","submitted_at":"2026-06-16T16:22:42Z","title":"Predicting Immune Biomarkers with MultiModal Mixture-of-Expert Pathology Foundation Models Empowers Precision Oncology","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-06-27T01:50:30.097327Z"},"links":{"citing_paper":"/paper/2606.18123"},"observation_digest":"sha256:669ca2c820e37cfce17448b2811ed147fa56ba71d1e8566c6a31518e1bfcf47c","observation_id":"11865c97-e39a-4aa8-ac10-9daccf75b887","resolution":{"observed_at":"2026-06-27T01:50:30.097327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T01:50:30.097327Z","title":"Pecam-1: regulatorof endothelialjunctional integrity","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2606.18123","last_updated":"2026-06-20T16:00:00Z","snapshot_observed_at":"2026-08-07T17:11:23.888737Z","submitted_at":"2026-06-16T16:22:42Z","title":"Predicting Immune Biomarkers with MultiModal Mixture-of-Expert Pathology Foundation Models Empowers Precision Oncology","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-06-27T01:50:30.097327Z"},"links":{"citing_paper":"/paper/2606.18123"},"observation_digest":"sha256:5a0ad33d6e672c3af8bff51ac02f51a784e6728ff8d2bb71123304cd31d639ab","observation_id":"fc6f5f28-a3d0-4c17-bb2c-f6974bb59ccc","resolution":{"observed_at":"2026-06-27T01:50:30.097327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T01:50:30.097327Z","title":null,"venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2606.18123","last_updated":"2026-06-20T16:00:00Z","snapshot_observed_at":"2026-08-07T17:11:23.888737Z","submitted_at":"2026-06-16T16:22:42Z","title":"Predicting Immune Biomarkers with MultiModal Mixture-of-Expert Pathology Foundation Models Empowers Precision Oncology","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-06-27T01:50:30.097327Z"},"links":{"citing_paper":"/paper/2606.18123"},"observation_digest":"sha256:245c3a22bf81e9c6ac5c6476e70fdcb55327d98a730fb21bf7c638239fa7635c","observation_id":"f2075e3e-3d63-4951-ba61-5eb19f0c6f46","resolution":{"observed_at":"2026-06-27T01:50:30.097327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T01:50:30.097327Z","title":"Cd163 and ccr7 as markers for macrophage polari- sation in lung cancer microenvironment.Central European Journal of Immunology, 44(4):395– 402, 2019","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2606.18123","last_updated":"2026-06-20T16:00:00Z","snapshot_observed_at":"2026-08-07T17:11:23.888737Z","submitted_at":"2026-06-16T16:22:42Z","title":"Predicting Immune Biomarkers with MultiModal Mixture-of-Expert Pathology Foundation Models Empowers Precision Oncology","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-06-27T01:50:30.097327Z"},"links":{"citing_paper":"/paper/2606.18123"},"observation_digest":"sha256:52f893248f8f9c93b18c3710bcb9c2bc696670df31e0cb604dc9f011ebbcc7c2","observation_id":"119c6f96-99fa-4088-9175-0325d59ce8a7","resolution":{"observed_at":"2026-06-27T01:50:30.097327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T01:50:30.097327Z","title":"Expression of naive/memory(cd45ra/cd45ro)markersbyperipheralbloodcd4+andcd8+tcellsinchildren with asthma.Archivum immunologiae et therapiae experimentalis, 56(1):55–62, 2008","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2606.18123","last_updated":"2026-06-20T16:00:00Z","snapshot_observed_at":"2026-08-07T17:11:23.888737Z","submitted_at":"2026-06-16T16:22:42Z","title":"Predicting Immune Biomarkers with MultiModal Mixture-of-Expert Pathology Foundation Models Empowers Precision Oncology","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-06-27T01:50:30.097327Z"},"links":{"citing_paper":"/paper/2606.18123"},"observation_digest":"sha256:678a50a909104b7ebec0501e7d044b26c55816f93ebfd5a63c94f9dda28b5164","observation_id":"fcb33dac-ea2f-4075-b1d6-9fe3b7eea4d7","resolution":{"observed_at":"2026-06-27T01:50:30.097327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T01:50:30.097327Z","title":"Video-assisted thoracic surgery lobectomy (vats), open tho- racotomy, and the robot for lung cancer.The Annals of thoracic surgery, 85(2):S710–S715, 2008","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2606.18123","last_updated":"2026-06-20T16:00:00Z","snapshot_observed_at":"2026-08-07T17:11:23.888737Z","submitted_at":"2026-06-16T16:22:42Z","title":"Predicting Immune Biomarkers with MultiModal Mixture-of-Expert Pathology Foundation Models Empowers Precision Oncology","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-06-27T01:50:30.097327Z"},"links":{"citing_paper":"/paper/2606.18123"},"observation_digest":"sha256:42e460569b80d5913755a188d4e3f26b99657ad029a0b8e9416e38e9f6b82c97","observation_id":"39e26045-1e80-434b-8b98-61642f44c029","resolution":{"observed_at":"2026-06-27T01:50:30.097327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T01:50:30.097327Z","title":"Ccnet: Criss-cross attention for semantic segmentation","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2606.18123","last_updated":"2026-06-20T16:00:00Z","snapshot_observed_at":"2026-08-07T17:11:23.888737Z","submitted_at":"2026-06-16T16:22:42Z","title":"Predicting Immune Biomarkers with MultiModal Mixture-of-Expert Pathology Foundation Models Empowers Precision Oncology","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-06-27T01:50:30.097327Z"},"links":{"citing_paper":"/paper/2606.18123"},"observation_digest":"sha256:8e0ca031cf4c41ad3e2caee4d85d41181d97d2ef344ff5b793d4ebf9d1cd93ad","observation_id":"8d7b4038-33a6-4c7d-8d12-2cc72195bd07","resolution":{"observed_at":"2026-06-27T01:50:30.097327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1711.05101","last_updated":"2019-01-04T21:01:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2017-11-14T14:24:06Z","title":"Decoupled Weight Decay Regularization","version":3},"cited_work":{"arxiv_id":"1711.05101","doi":"10.1137/1.9781611972825.47","metadata_source":"pith","pith_arxiv_id":"1711.05101","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Decoupled Weight Decay Regularization","venue":"cs.LG","work_id":"07ef7360-d385-4033-83f7-8384a6325204","year":2017},"citing_paper":{"arxiv_id":"2606.18123","last_updated":"2026-06-20T16:00:00Z","snapshot_observed_at":"2026-08-07T17:11:23.888737Z","submitted_at":"2026-06-16T16:22:42Z","title":"Predicting Immune Biomarkers with MultiModal Mixture-of-Expert Pathology Foundation Models Empowers Precision Oncology","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-06-27T01:50:30.097327Z"},"links":{"cited_paper":"/paper/1711.05101","citing_paper":"/paper/2606.18123"},"observation_digest":"sha256:c39a76e42d085f7fa8aaf9019553e6239558c3f9f1abbffa4bca1fd67e1f2b27","observation_id":"43508204-b8dc-43db-879d-ac565736cdca","resolution":{"observed_at":"2026-07-03T19:28:52.308191Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.06750","last_updated":"2025-02-10T18:23:55Z","snapshot_observed_at":"2026-08-07T04:52:13.980282Z","submitted_at":"2025-02-10T18:23:55Z","title":"Accelerating Data Processing and Benchmarking of AI Models for Pathology","version":1},"cited_work":{"arxiv_id":"2502.06750","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2502.06750","snapshot_observed_at":"2026-07-03T19:28:52.302392Z","title":"Accelerating data processing and benchmarking of ai models for pathology","venue":null,"work_id":"aa58e0f9-b009-4c60-afd1-522baa54c7c5","year":2025},"citing_paper":{"arxiv_id":"2606.18123","last_updated":"2026-06-20T16:00:00Z","snapshot_observed_at":"2026-08-07T17:11:23.888737Z","submitted_at":"2026-06-16T16:22:42Z","title":"Predicting Immune Biomarkers with MultiModal Mixture-of-Expert Pathology Foundation Models Empowers Precision Oncology","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-06-27T01:50:30.097327Z"},"links":{"cited_paper":"/paper/2502.06750","citing_paper":"/paper/2606.18123"},"observation_digest":"sha256:9f4e14dbec4f888e98022e2a821ae8ccb3d8671692f8d6b3940ba50d5e255a72","observation_id":"20023223-2b91-445f-97ae-291d3cb2b315","resolution":{"observed_at":"2026-07-03T19:28:52.304120Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2501.16652","last_updated":"2025-01-28T02:35:02Z","snapshot_observed_at":"2026-07-06T20:27:09.296190Z","submitted_at":"2025-01-28T02:35:02Z","title":"Molecular-driven Foundation Model for Oncologic Pathology","version":1},"cited_work":{"arxiv_id":"2501.16652","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2501.16652","snapshot_observed_at":"2026-07-03T19:28:52.304119Z","title":"Molecular-driven foundation model for oncologic pathology","venue":null,"work_id":"35e2a6b6-4a1b-4d32-b3e8-1e437c782997","year":2025},"citing_paper":{"arxiv_id":"2606.18123","last_updated":"2026-06-20T16:00:00Z","snapshot_observed_at":"2026-08-07T17:11:23.888737Z","submitted_at":"2026-06-16T16:22:42Z","title":"Predicting Immune Biomarkers with MultiModal Mixture-of-Expert Pathology Foundation Models Empowers Precision Oncology","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-06-27T01:50:30.097327Z"},"links":{"cited_paper":"/paper/2501.16652","citing_paper":"/paper/2606.18123"},"observation_digest":"sha256:77d2b53e00bbabd4850abd090c5634f2883724237930bef2f9ab629131c9d836","observation_id":"6e44baf5-4ceb-4d84-b522-6b149d84ce7b","resolution":{"observed_at":"2026-07-03T19:28:52.305682Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2601.03267","last_updated":"2026-05-01T23:55:43Z","snapshot_observed_at":"2026-08-02T10:52:10.211700Z","submitted_at":"2025-12-19T07:05:38Z","title":"OpenAI GPT-5 System Card","version":2},"cited_work":{"arxiv_id":"2601.03267","doi":"10.48550/arxiv.2601.03267","metadata_source":"pith","pith_arxiv_id":"2601.03267","snapshot_observed_at":"2026-08-05T02:49:54.815029Z","title":"OpenAI GPT-5 System Card","venue":"cs.CL","work_id":"ca87689a-0d29-4476-b504-b65dbbb08af4","year":2025},"citing_paper":{"arxiv_id":"2606.18123","last_updated":"2026-06-20T16:00:00Z","snapshot_observed_at":"2026-08-07T17:11:23.888737Z","submitted_at":"2026-06-16T16:22:42Z","title":"Predicting Immune Biomarkers with MultiModal Mixture-of-Expert Pathology Foundation Models Empowers Precision Oncology","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-06-27T01:50:30.097327Z"},"links":{"cited_paper":"/paper/2601.03267","citing_paper":"/paper/2606.18123"},"observation_digest":"sha256:f52716249187f2d7c1e9b5fe03d6c3b70ab0977d4e21c04cdb2f9284b974c2f3","observation_id":"e4add402-58ad-4fd5-88e9-13c2244a61e5","resolution":{"observed_at":"2026-07-03T19:28:52.313176Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-03T00:38:11.458508+00:00","source":"crossref_status_cache"},{"observed_at":"2026-08-03T00:38:11.458508+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2606.18123","last_updated":"2026-06-20T16:00:00Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-07T17:11:23.888737Z","submitted_at":"2026-06-16T16:22:42Z","title":"Predicting Immune Biomarkers with MultiModal Mixture-of-Expert Pathology Foundation Models Empowers Precision Oncology"},"reference_resolution":{"displayed":38,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":33,"verified_exact":5,"verified_fuzzy":0},"total_outbound_references":38},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2606.18123."}