{"as_of":"2026-08-19T15:02:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2063aac6af3fc7223db81998f03daa7da3109abf3c46f8ae8dda953b10b90377","coverage":[{"denominator":63,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":63,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T17:55:03.674366Z","state":"measured"},{"denominator":64,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":64,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-19T06:32:44.657259+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T15:06:08.713044Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-15T15:06:09.976942Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"cited_work":{"arxiv_id":"2507.20089","doi":null,"metadata_source":"pith","pith_arxiv_id":"2507.20089","snapshot_observed_at":"2026-08-15T15:06:09.976942Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","venue":"cs.LG","work_id":"3e0a7221-5d0c-44d5-b3f1-afa8822eb7b2","year":2025},"citing_paper":{"arxiv_id":"2608.02769","last_updated":"2026-08-03T18:10:58Z","snapshot_observed_at":"2026-08-18T15:47:44.807589Z","submitted_at":"2026-08-03T18:10:58Z","title":"DAIF: A Data-Driven Intermediate Fusion Framework for Multimodal Supervised Learning via Approximate Message Passing","version":1},"reference_index":53,"source":"arxiv_source","source_observed_at":"2026-08-15T15:06:08.713044Z"},"links":{"cited_paper":"/paper/2507.20089","citing_paper":"/paper/2608.02769"},"observation_digest":"sha256:7d60e3b03797a9a3b503c707115920374e1628a109f15027096920ba57da9697","observation_id":"99ff2dc2-9599-4c59-84f8-79fcb270cb12","resolution":{"observed_at":"2026-08-15T15:06:09.985105Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2507.20089/citation-record","integrity":"/paper/2507.20089/integrity","json":"/paper/2507.20089/citation-record.json","paper":"/paper/2507.20089"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:04.422410Z","title":"Fuse- MODNet: Real-Time Camera and LiDAR Based Moving Object Detection for Ro- bust Low-Light Autonomous Driving","venue":null,"work_id":"c3093e03-1341-41c5-8a96-98aa5dbd45dd","year":2019},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.383771Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:538bb598ecabfaa356241e8cce4dde2aa375f764a13eda14a01a9f817e04d2ff","observation_id":"d481d9a5-7427-4ec0-9db5-79d41023f2c3","resolution":{"observed_at":"2026-08-15T17:55:04.426497Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:04.409598Z","title":"Sensors and Sensor Fusion in Autonomous Vehicles","venue":null,"work_id":"afb15ba7-53b1-4db7-9da6-6bced17fb862","year":2018},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.388856Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:16c39eda11495647312aa919bd997086731a35444029b69b7d60b08d7af4644b","observation_id":"d929f021-ddfd-421e-89a0-5acf8a48941c","resolution":{"observed_at":"2026-08-15T17:55:04.414642Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:04.395945Z","title":"Multimodal Language Analysis in the Wild: CMU-MOSEI Dataset and Interpretable Dynamic Fusion Graph","venue":null,"work_id":"7504f470-f7fa-4202-88de-8f537a0b24ad","year":2018},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.393606Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:c4810d49ee90c0dd984001286ed1b92176a65dbc08a628dbc2180f8ec7b1a74e","observation_id":"d3fdf6c7-9d8d-4693-970c-bbc3beb890ec","resolution":{"observed_at":"2026-08-15T17:55:04.399612Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:04.383572Z","title":"Multimodal Sentiment Analysis: A Survey of Methods, Trends, and Challenges","venue":null,"work_id":"b9e84c0e-71d3-4133-b703-bb200e2ea37f","year":2023},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.398645Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:5fea05a8319670d1b9fb46f51dff4bf19d8444a3f35a547db95b96a2bb97210d","observation_id":"bd37d112-4c3e-4126-ab8e-032726ae0473","resolution":{"observed_at":"2026-08-15T17:55:04.387577Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:04.371076Z","title":"Multimodal sentiment analysis: A systematic review of history, datasets, multimodal fusion methods, appli- cations, challenges and future directions","venue":null,"work_id":"e7c2b562-4188-48b9-a95a-ff4deff046c7","year":2023},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.403833Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:38b93c2201557de9e1725e91b689890b907112d63342ec86e64f6b609cf3daba","observation_id":"63384619-b85c-47b4-9dd5-2d2b2052aa2e","resolution":{"observed_at":"2026-08-15T17:55:04.375729Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:04.357875Z","title":"Multimodal classification of Alzheimer’s disease and mild cognitive impairment","venue":null,"work_id":"80e2be67-8a9f-43c3-9f7f-d6ef2b4b3702","year":2011},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.408012Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:095a6a3d62559d67b55c0920bb6432eb6e8c0b2fc2e1d348b19a318d1953a776","observation_id":"1e134ed4-0c20-45d4-8368-f769a49ef0e1","resolution":{"observed_at":"2026-08-15T17:55:04.363103Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:04.346698Z","title":"Multimodal deep learning for Alzheimer’s disease dementia assessment","venue":null,"work_id":"2012db6e-a330-4803-a813-3a66913288bf","year":2022},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.413851Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:d1ec5c74c0500d6afa4ebeac790ccaf5093982cce20bf729ec9e171a79128d4d","observation_id":"b538b234-9adb-4a61-a784-e937bd72f98e","resolution":{"observed_at":"2026-08-15T17:55:04.350719Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:04.336468Z","title":"Fusion of medical imaging and electronic health records using deep learning: a systematic review and implementation guidelines","venue":null,"work_id":"9b2f41ce-84a5-40f3-bacb-251f15e49cca","year":2020},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.418871Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:9786f18aedc613240beb7e8fb983a48c4953631ef79c23d4ea83510d94a99337","observation_id":"adfa8835-dfda-4e2a-aa03-2b621fceadd2","resolution":{"observed_at":"2026-08-15T17:55:04.340414Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:04.324416Z","title":"Deep multimodal fusion for se- mantic image segmentation: A survey","venue":null,"work_id":"c5e85f8d-60e8-4e97-a324-37b74289fec3","year":2021},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.423558Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:d5b24a4ffe72e4dad5ee3db2a72844cad7edb11629c23787d7b753cd9d786d20","observation_id":"c61f5905-2c20-4e6b-a86d-bc8c914e660a","resolution":{"observed_at":"2026-08-15T17:55:04.328160Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:04.313291Z","title":"Indoor Semantic Segmentation using depth information","venue":null,"work_id":"3f42be27-6494-4453-af25-b995b2f91cc4","year":2013},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.429560Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:d366de328943b5547da515cc07874b7399bb47c5468fb7f424580340a8a36dfd","observation_id":"096065fc-33a3-4120-b7fd-f3b7977d46a0","resolution":{"observed_at":"2026-08-15T17:55:04.317521Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:04.300090Z","title":"Multimodal End-to-End Autonomous Driving","venue":null,"work_id":"13ec23f2-56fb-4280-87dd-cc91ea7e40fe","year":2022},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.434227Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:77b00486eae4ae27ce72edcd3621efdffa91587327e5f6c94e5c0a91e31a241d","observation_id":"b05d2545-e55b-4f21-89d1-c66431111e29","resolution":{"observed_at":"2026-08-15T17:55:04.305470Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:04.284248Z","title":"Fusion of deep learning models of MRI scans, Mini–Mental State Examination, and logical memory test enhances diagnosis of mild cognitive impairment","venue":null,"work_id":"ba4970d7-9bc6-49eb-aa09-5e149da4d785","year":null},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.438639Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:e1c96d071bedce1b45984d7b9dc20bacdc7e3d5d548a83b40c583844cd814e4f","observation_id":"b44c4964-b502-46cf-95d0-a92c8794a22d","resolution":{"observed_at":"2026-08-15T17:55:04.289017Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:04.267886Z","title":"Deep Learning Role in Early Diagnosis of Prostate Cancer","venue":null,"work_id":"c8a35ac6-c216-4d08-ab8c-15eb6d7f8dfd","year":2018},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.444076Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:1c5375e2fdc06a56a7f10832f364ec7a09c9051e14b424bc5e992571887f5bf8","observation_id":"884a6567-a0e4-4b76-be6d-1bd1ffff777a","resolution":{"observed_at":"2026-08-15T17:55:04.274589Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:04.250948Z","title":"Deep learning of brain lesion patterns and user-defined clinical and MRI fea- tures for predicting conversion to multiple sclerosis from clinically isolated syndrome","venue":null,"work_id":"3bc6f775-71ab-4d4a-b6f7-f30e04ff105b","year":2019},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.449489Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:0a970a2e2b2771c8809e44b9d915ad14f9b3a599ef2cfca6cdcdf8bcfe9beca9","observation_id":"dea2aeee-83c8-47be-ade9-8599f0078d88","resolution":{"observed_at":"2026-08-15T17:55:04.255609Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:04.240132Z","title":"Cooperative learning for mul- tiview analysis","venue":null,"work_id":"f099776f-3b56-437a-902f-0420b71b2140","year":2022},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.453767Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:de1aeb377ec5a1294fc44d856adae02b459d7e88c49eb8968c9555353b5a6721","observation_id":"32fa293d-460d-469e-91ce-e325b41def9a","resolution":{"observed_at":"2026-08-15T17:55:04.243949Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:04.226169Z","title":"A Deep Learning Mammography-based Model for Improved Breast Cancer Risk Prediction","venue":null,"work_id":"4c68a315-c8e1-4606-859f-cf220fc8f040","year":2019},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.458036Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:357e5f1ec47b761334c88630bf6f13fb200dbcf545a47cf5ef238dbb0180d2a3","observation_id":"dbdb3726-93b8-4824-8515-e2baf795b1b1","resolution":{"observed_at":"2026-08-15T17:55:04.231399Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:04.214794Z","title":"Multi-Channel 3D Deep Feature Learning for Survival Time Prediction of Brain Tumor Patients Using Multi-Modal Neuroimages","venue":null,"work_id":"424112e8-e08f-4433-b817-11aef2537964","year":2019},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.462220Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:f207d693e9f53e1d854fcd38939480bb4723c685970b7464c27618fc8d1bf99c","observation_id":"f3943682-c633-4a91-9b58-ebc152511d6c","resolution":{"observed_at":"2026-08-15T17:55:04.218865Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:04.200755Z","title":"An Efficient Multi-View Multimodal Data Processing Framework for Social Media Popularity Prediction","venue":null,"work_id":"379960cd-cd64-4ad6-926f-2e9406394212","year":2022},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.467767Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:dc9f73e3a1498ad898c869ad62cbb245a30f4a874c6356a1c029da2148d059c7","observation_id":"b0e6cfc8-65b6-4e95-82c6-fc006469b4b6","resolution":{"observed_at":"2026-08-15T17:55:04.206150Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:04.189275Z","title":"Multimodal Learning with Deep Boltzmann Machines","venue":null,"work_id":"04a5eb15-c9d0-4052-a529-12a89ef2b7d4","year":2012},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.472247Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:1523e709df33eb6741cae17bf3d61694889eb0c31ffb76570ef49397cd4fb832","observation_id":"e8e64cb2-4bd8-4a42-94a1-c9bb47b7f3d0","resolution":{"observed_at":"2026-08-15T17:55:04.193132Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:04.174156Z","title":"Multimodal generative models for scalable weakly-supervised learning","venue":null,"work_id":"f4420de7-f3fe-41b0-9893-073eda7797f2","year":2018},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.478059Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:30dff2fa92ecc247b77fdce6a73097072c4370a5d37b4b19a5d841d78b97bce6","observation_id":"b9e40ae6-f5db-4ef3-93f0-b501fd1511c7","resolution":{"observed_at":"2026-08-15T17:55:04.178973Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:04.163390Z","title":"Unity by Diversity: Improved Representation Learning in Multimodal VAEs","venue":null,"work_id":"784b6060-eec6-4f22-a20f-7e4e99fb83a8","year":2024},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.483826Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:c31aacfdca9826a0686cb6b60e79887071fb7c2ec85a4b0aaf9b1d2e806eca66","observation_id":"aa76d843-efac-4e90-bcbc-80219c6f2f63","resolution":{"observed_at":"2026-08-15T17:55:04.167308Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:04.152383Z","title":"Deep Mutual Learning","venue":null,"work_id":"91755729-8420-4ce6-9884-10f3d6e89ac2","year":2017},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.488618Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:c93a69dbe8d7ff9c5430e8216ebdee990ac41c9364df0188347ffe2c67b6124f","observation_id":"724e25b2-0d4c-4708-946f-d7b3880e6fd4","resolution":{"observed_at":"2026-08-15T17:55:04.156003Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:04.142491Z","title":"Bagging predictors","venue":null,"work_id":"0833b912-3542-44b7-a69f-5e9f70db5797","year":1996},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.493113Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:6b1b29e231a0d21853f23636f3cd05a59a8f954c4bfb8e39e87c6d4d7162ceb1","observation_id":"caeef9ad-7f1a-4bcf-9c84-4c5c2a04bef6","resolution":{"observed_at":"2026-08-15T17:55:04.146189Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:04.131897Z","title":"Ensemble selection from libraries of models","venue":null,"work_id":"f6c78ac9-ca3f-4d63-877a-8dea71946f1f","year":2004},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.497419Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:9f1d50f33b2e2d9afc5c8e4258a4836e4043ffa5286904f37c1d0f889b626f15","observation_id":"43949141-210f-4ca4-9d9b-f0bff1e8bbfa","resolution":{"observed_at":"2026-08-15T17:55:04.135646Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:04.120917Z","title":"Regression Shrinkage and Selection via the Lasso","venue":null,"work_id":"6171cd61-f6a6-47ac-8553-d792ff52410d","year":1996},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.501606Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:6593117a5f4870baf3eef7862a5c8ff4ae4ec496f032545dc4b529b2933ec882","observation_id":"91719157-7120-4cb8-a560-27433f86314c","resolution":{"observed_at":"2026-08-15T17:55:04.124549Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:04.110126Z","title":"Model compression","venue":null,"work_id":"0589bc58-2d28-4a80-8e92-8a4c56af7763","year":2006},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.507482Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:c953143a730a8bd9729d2328480cc6478c30fccef17c4cd8f16e74660a21d415","observation_id":"61bebb18-7f6f-46ac-b361-60d4c83109ee","resolution":{"observed_at":"2026-08-15T17:55:04.114009Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1503.02531","last_updated":"2015-03-09T15:44:49Z","snapshot_observed_at":"2026-08-16T18:00:58.008096Z","submitted_at":"2015-03-09T15:44:49Z","title":"Distilling the Knowledge in a Neural Network","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1503.02531","snapshot_observed_at":"2026-08-15T17:55:03.512069Z","title":"Distilling the Knowledge in a Neural Network","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.512069Z"},"links":{"cited_paper":"/paper/1503.02531","citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:5415733d230c53a8221ba113b7b745d8ce84e095a09e6e0aa59bc8aefe3ad2a1","observation_id":"456bc156-feca-417d-bddb-ea245f5c38c5","resolution":{"observed_at":"2026-08-15T17:55:03.512069Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:04.099713Z","title":"Modality-Aware Mutual Learning for Multi-modal Medical Image Segmentation","venue":null,"work_id":"7578236e-0281-4bd7-88cf-58ec48d1fc38","year":2021},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.517990Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:0df858ae9d8d702d19630d127f22fac91eb54534ebe7ac9aed479ab42959b061","observation_id":"32bb849c-57d9-4ca3-ace1-2a4a5b2bb7d3","resolution":{"observed_at":"2026-08-15T17:55:04.103374Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:04.088666Z","title":"AM ³Net: Adaptive Mutual-Learning-Based Multimodal Data Fusion Network","venue":null,"work_id":"dc237370-7498-4331-aa4a-d00425496766","year":2022},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.523271Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:89dc66be6c8a5675d0ce47592e4246488e8106f348b053db739a445fed9acdce","observation_id":"bf31f492-c982-4e5d-8af5-7789cea7a7d7","resolution":{"observed_at":"2026-08-15T17:55:04.092884Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:04.078484Z","title":"Multi-modal contrastive mutual learning and pseudo-label re-learning for semi-supervised medical image seg- mentation","venue":null,"work_id":"e60422a9-addc-46c9-bc92-d5bc125394e9","year":2023},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.528373Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:e48d20df96c016c3bb35e4c1440535522041de7463f809e4c8b9b84c5040fb53","observation_id":"9c09af9d-f84f-4c8e-b1f9-30ff60ff08de","resolution":{"observed_at":"2026-08-15T17:55:04.082276Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:04.061625Z","title":"Graph neural networks with deep mutual learning for designing multi-modal recommendation systems","venue":null,"work_id":"abb368c1-f1d9-4c97-9b92-d99f6e488b14","year":2024},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.532579Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:4c11766e03904d57d3ef46ce27393eb5886f01c0a669c4fbf2840f0147ca9936","observation_id":"a146cf33-ddda-42f4-a6b3-141a7eefcab0","resolution":{"observed_at":"2026-08-15T17:55:04.066279Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:04.050410Z","title":"Deep Residual Learning for Image Recognition","venue":null,"work_id":"63c44f97-2980-4847-aeb0-fb9f54d2f0c1","year":2015},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.536729Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:5ca26475c63a0d1d68313f3b8dc26b208120c2045b3ef1ad3297bb5f3d113b82","observation_id":"bb9d5101-4b60-4ead-9ef1-b9a1a211692f","resolution":{"observed_at":"2026-08-15T17:55:04.054210Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:04.039130Z","title":"BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding","venue":null,"work_id":"02d132e3-1800-4264-9050-b58a28ba4716","year":2019},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.545749Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:1d4b76ea5603505ad1dd84880befdaed5aab982ac4ba8d3768e8b8bad6e45977","observation_id":"bf5364a2-e00d-48f4-9e4e-5031f365cc08","resolution":{"observed_at":"2026-08-15T17:55:04.042611Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:04.029604Z","title":"A unified theory of diversity in ensemble learning","venue":null,"work_id":"fc43c4fc-b94b-4436-a7c9-d53f41a6c9f4","year":2024},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.550766Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:369ebc1c4a9c727668fcbed2f512144d3b71fc83d3d67d3a974f197f68e92b5e","observation_id":"7fb991f9-2fec-4760-a013-284455dacded","resolution":{"observed_at":"2026-08-15T17:55:04.032927Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:04.019500Z","title":"A review of feature set partitioning methods for multi-view ensemble learning","venue":null,"work_id":"2d3bc5e1-2eb4-4d9b-aab5-c7240bfc892f","year":2023},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.555825Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:444b273fdb56020489a538d3da813d30290e969a28dde352ada3a165b8966ad9","observation_id":"9fec09b8-1c90-4d4b-8ff3-62bfda65d672","resolution":{"observed_at":"2026-08-15T17:55:04.023007Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:04.009361Z","title":"Silhouettes: A graphical aid to the interpretation and validation of cluster analysis","venue":null,"work_id":"c1bf7c45-cbbd-4950-8510-6f72a9089f3a","year":1987},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.560391Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:5d8471449eb1b3d162b9c0b3b30d1307b96ab45a2c8de2170cc8400bd609d2b1","observation_id":"1928ac58-cc03-47ad-bbe2-8979b1ce3742","resolution":{"observed_at":"2026-08-15T17:55:04.013000Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:03.998134Z","title":"The Determination of Cluster Number at k-Mean Using Elbow Method and Purity Evaluation on Headline News","venue":null,"work_id":"b942f45b-8189-48a1-9611-05f5e3705b96","year":2018},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.564135Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:4d5bd7987e6b95f8431681524a682a842ecb75bb8bdf1c55bcc706e47ba651f6","observation_id":"43e66b58-ffc6-4cc0-8574-09fa1a47519e","resolution":{"observed_at":"2026-08-15T17:55:04.001920Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:03.986964Z","title":"Getting the Most Out of Ensem- ble Selection","venue":null,"work_id":"7eb6d5c0-dbc9-4c59-b6e4-ed9eb4bb9ae4","year":2006},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.569498Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:28597ce24eb921683b3fd3bd162c00a5363e221988190aa1845470731bf19d4a","observation_id":"f1ca76ad-ff6e-43a1-8716-58cf0371e1f3","resolution":{"observed_at":"2026-08-15T17:55:03.990767Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:03.974919Z","title":null,"venue":null,"work_id":"f8a2eac2-e51d-428a-a17c-20297b7727ed","year":2012},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.574752Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:e72eecf3ad78f8ec7b449ad97b2fb6b4b98fd54554a4238e33363c86a98494b6","observation_id":"b37064a9-5d24-48ef-88bb-6b06e933bad8","resolution":{"observed_at":"2026-08-15T17:55:03.979711Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:03.964874Z","title":"Exact solutions to the nonlinear dy- namics of learning in deep linear neural networks","venue":null,"work_id":"de2a6818-a86f-4206-9c71-4cfe8e6c636e","year":2014},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.579012Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:283444bfeeb30d551092417801a2882367a3a5d1707363a4f39a0bd6bfd37170","observation_id":"b86f2b52-4b25-452b-950f-7a5e92c0287e","resolution":{"observed_at":"2026-08-15T17:55:03.968374Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:03.953846Z","title":"Deep Learning without Poor Local Minima","venue":null,"work_id":"814d9d16-4834-4c5d-85f2-a5cb2c01b313","year":2016},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.582650Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:51dd56758085ca43b8088d8cab795c1589b08d01754726ed304a0deb85bcfa0c","observation_id":"f81c2e31-f942-4616-bfb4-c3c3635d878e","resolution":{"observed_at":"2026-08-15T17:55:03.958058Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:03.943818Z","title":"Identity Matters in Deep Learning","venue":null,"work_id":"cc9e7a83-5562-4550-bab2-6a4faf0027fa","year":2017},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.587010Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:3fe65e8081938c36d12bb394187e567b653c61d5b6433a6cef80a79e26888ef8","observation_id":"3d8378ad-5b0b-4712-922b-409c29628d44","resolution":{"observed_at":"2026-08-15T17:55:03.947191Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:03.934239Z","title":"Towards Understanding Knowledge Distillation","venue":null,"work_id":"6f7fc096-876c-4c4c-b94b-f1cbd1d55d54","year":2019},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.590968Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:92fca95612ee139dff3cd72657a43d681c7a565ff94ae91127b136b61440a4c0","observation_id":"4f695ffa-291a-4cf3-8bc0-df1c242c3496","resolution":{"observed_at":"2026-08-15T17:55:03.937650Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:03.924988Z","title":"The Revised National Alzheimer’s Coordinating Center’s Neuropathology Form—Available Data and New Analyses","venue":null,"work_id":"2004e540-e49f-42a6-97a4-d27b11442ae4","year":2018},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.595027Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:ac643e481faef78ceaced3122ba5cf7fb2fbabbb5775d8a182a4aa1c227766d4","observation_id":"79458425-cbe1-450c-9306-cb6560617dd9","resolution":{"observed_at":"2026-08-15T17:55:03.928226Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:03.915746Z","title":"Version 3 of the Alzheimer Disease Centers’ Neuropsychological Test Battery in the Uniform Data Set (UDS)","venue":null,"work_id":"9722fd1a-103e-429a-bb5a-dbd2644036bb","year":2018},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.599569Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:ef08b45221334f78c0fd94583449837c54e9e63f50aa455acebe5b010408f498","observation_id":"ec3dbbe5-7e2c-4f1e-85a3-b828711add48","resolution":{"observed_at":"2026-08-15T17:55:03.918931Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:03.906999Z","title":"“Mini-mental state","venue":null,"work_id":"f7621445-7f2d-4c59-9551-93febe42b7b5","year":1975},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.603878Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:d2655a97e63edd471b88f99e8ee6031858449d2286ecb877c2537ef671d450ae","observation_id":"e0143664-26d6-4bfc-88d2-22d7a386d8d0","resolution":{"observed_at":"2026-08-15T17:55:03.910124Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:03.896974Z","title":"The Neuropsychological Profile of Alzheimer Disease","venue":null,"work_id":"448f3c34-e3b0-408e-a345-cfaeb17043f4","year":2012},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.607502Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:287da8db0a363b6cc775b6bcc08e72422d1f6a21ba9294abdb057b749361a6dc","observation_id":"8cb2ea26-379b-40fe-ae01-ad6ac13afa82","resolution":{"observed_at":"2026-08-15T17:55:03.900479Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:03.887675Z","title":"Cognitive Tests to Detect Dementia: A Systematic Review and Meta-analysis","venue":null,"work_id":"dca8fb5f-24b6-4421-a5a6-2a2a83f73b18","year":2015},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.611195Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:bf463b6f7a047358c3ab92b2b77abfae280f4aad346a55371eb5322eddf92059","observation_id":"710f8e9a-91af-4c77-a5cf-d2703dd7e062","resolution":{"observed_at":"2026-08-15T17:55:03.891141Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:03.878305Z","title":"Hypothetical model of dynamic biomarkers of the Alzheimer’s pathological cascade","venue":null,"work_id":"01480dfe-5fe3-46ba-a31c-a0824693673c","year":2010},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.615374Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:0e2137192b935ac7b11be53b75668a0b78806f933f630f401750f8b4e28ff560","observation_id":"5c3771db-77c8-4448-bc9b-3747b7e99b6c","resolution":{"observed_at":"2026-08-15T17:55:03.881623Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:03.868776Z","title":"Dementia prevention, intervention, and care: 2020 report of the Lancet Commission","venue":null,"work_id":"9e371397-e5e3-44ed-b166-c86b5ab83efb","year":2020},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.619616Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:43c1e164c922ee86dab6bb0bf23199f26de6464d1eb8e5f7afe3c6fe11f0aca7","observation_id":"920d2485-9a4e-447d-9455-a4bfea3ccdb4","resolution":{"observed_at":"2026-08-15T17:55:03.872303Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:03.857722Z","title":"Alzheimer’s disease detection using data fusion with a deep supervised encoder","venue":null,"work_id":"b8391ee3-e0a1-427d-9544-e75e9e9ede6d","year":2024},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.623318Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:409f3266ee2a421ccff224da5420080bd07f65658613915d34eebee50fcdfef4","observation_id":"8bdd24b1-6255-413c-b9a8-8d2ce95da2d3","resolution":{"observed_at":"2026-08-15T17:55:03.862089Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:03.847457Z","title":"Episodic and Semantic Memory","venue":null,"work_id":"4cf3395b-a58d-4bdd-ae10-767c4ea75905","year":1972},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.628438Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:fe41f9b54f404328ae57cb97a62486535f46f48f7077d15084a9eb4eb683467b","observation_id":"546be39f-03e0-408d-84a5-cfa34d17f477","resolution":{"observed_at":"2026-08-15T17:55:03.850996Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:03.835365Z","title":"Neural basis of the perception and estimation of time","venue":null,"work_id":"613f0700-5e0f-4e0f-a29f-2a381cc3e4e8","year":2013},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.634547Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:c0ea5874c157a5cb222da5ebc2f8afe9346245633e59492a699dd20a98f8c192","observation_id":"82681cf7-019f-4b72-981f-953cfd5d0d82","resolution":{"observed_at":"2026-08-15T17:55:03.840114Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:03.824512Z","title":"Time cells in the hippocampus: a new dimension for mapping mem- ories","venue":null,"work_id":"64b6c22d-7d5d-46de-9991-9332ae82344e","year":2014},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.639269Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:c4d5208e910b8aaa980c1e125e3846c08af653e2a42a528a9329c42779605ee5","observation_id":"5fb05ef5-daca-4b83-b09a-b61f5fa4b114","resolution":{"observed_at":"2026-08-15T17:55:03.828465Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:03.813407Z","title":"Mitzdorf et al","venue":null,"work_id":"60e89286-aeef-48c4-b703-39a1b2855805","year":1985},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.642974Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:2b3a2e6c786ad6f50b040a2e7dfeeeeb14f42dd7ca23e48efef7ce52cc7919e6","observation_id":"9465fdae-8c65-477d-8cc5-a1a3b2ba9f8e","resolution":{"observed_at":"2026-08-15T17:55:03.817565Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:03.803073Z","title":"Nonspatial sequence coding in CA1 neurons","venue":null,"work_id":"8131c502-568c-4bcc-8ce6-4be9f1202c17","year":2016},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.646591Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:e032edb8b92bd0b4e8ffa1b452fc3179f1ad75c255097b33b108082d61586800","observation_id":"c76617a7-1552-4617-8d30-d6e004db1fe6","resolution":{"observed_at":"2026-08-15T17:55:03.806440Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:03.792297Z","title":"Hippocampal ensembles represent sequential relation- ships among an extended sequence of nonspatial events","venue":null,"work_id":"874f47d4-0bbc-44b7-b622-e8a9457637c0","year":2022},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.650285Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:0700619c0609a8cacd7babb094f33bacee9263a4ea3010477b4ef4f6bd0b0410","observation_id":"cebbbaa4-1a77-4d81-a4a0-07d90807c79e","resolution":{"observed_at":"2026-08-15T17:55:03.796091Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:03.780168Z","title":"Federated Learning: Challenges, Methods, and Future Directions","venue":null,"work_id":"95f84a76-3abe-4b39-ac86-78c6f8c0b49b","year":2020},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.654344Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:3d17c7be201e0f80461400535f0bf73265e1c58bfed6a886859c9fbab4591003","observation_id":"e3d45566-93f3-48b1-ae8a-447097a9e9c0","resolution":{"observed_at":"2026-08-15T17:55:03.784592Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:03.768638Z","title":"Inverses of 2 × 2 block matrices","venue":null,"work_id":"317a2ba4-5858-484d-aea3-b61106e89485","year":2002},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.658130Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:aa48cb8faa090c1c8584eb11e17ed4a28c9f0f1a9534714cfa501d3bc90b8dc8","observation_id":"3281a4f4-5ac3-4128-af6f-80985b333918","resolution":{"observed_at":"2026-08-15T17:55:03.772299Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:03.756299Z","title":"Generate latent variables: X∗∈ Rn×p∗ x, X∗ ij∼N(0, 1); Z∗∈ Rn×p∗ z, Z∗ ij∼N(0, 1); S∗∈ Rn×p∗ s, S∗ ij∼N(0, 1)","venue":null,"work_id":"834136d4-e11e-4ff7-8eec-a84cdb53acee","year":null},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.662535Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:b0f7d6304465da3ae634f262ad4d389ffae954c721a1f4d1f20fe3d18d48cfb5","observation_id":"7f7645a8-c62c-4896-9d36-b17829dcbc14","resolution":{"observed_at":"2026-08-15T17:55:03.760379Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:03.745468Z","title":null,"venue":null,"work_id":"8135258a-30a8-4efd-9da1-a6cbcd5a422e","year":null},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.666411Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:cc8b05787d8b9f0d5ed53ccac52d8f8a67d7d059dd3f7f0b79aaa50365d35a28","observation_id":"7982f12e-4d02-44d3-896d-436df2f40486","resolution":{"observed_at":"2026-08-15T17:55:03.749682Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:03.734129Z","title":"For instance, setting ct = 0 removes that component’s influence on Y","venue":null,"work_id":"24a060cb-b391-477f-b079-078dedaa65aa","year":null},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.670380Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:b9b247b9da5064d29424976a31c1acf61cd08befed7afaf698d94cb2d4989c3d","observation_id":"bc9a2cfd-0a3a-4c37-859c-b50a3233aed2","resolution":{"observed_at":"2026-08-15T17:55:03.738624Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:55:03.722034Z","title":"Best Single,","venue":null,"work_id":"675d687e-6213-4f6d-9ce8-b317bd8b305e","year":null},"citing_paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-15T17:55:03.674366Z"},"links":{"citing_paper":"/paper/2507.20089"},"observation_digest":"sha256:ebbc6a824ea068554be1d1d6a365c5918bd7bda64c23fd95f220a7cab4d7a925","observation_id":"7f492085-f87f-4c1a-83b1-9153d6063650","resolution":{"observed_at":"2026-08-15T17:55:03.726798Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2507.20089","last_updated":"2025-07-27T00:50:29Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-18T11:00:36.568481Z","submitted_at":"2025-07-27T00:50:29Z","title":"Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning"},"reference_resolution":{"displayed":63,"state_counts":{"malformed_identifier":2,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":3,"verified_exact":0,"verified_fuzzy":58},"total_outbound_references":63},"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":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"thesis":"As of 19 August 2026, this Paper Citation Record lists 63 of 63 outbound references and 1 inbound Pith citation observation for arXiv:2507.20089."}