{"as_of":"2026-08-10T19:30:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:aff1a769bf34aa21219ea125d03699ddf03089ff8ae2d3d65a2f914c62191cf2","coverage":[{"denominator":25,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":25,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-09T19:11:31.218050Z","state":"measured"},{"denominator":26,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":26,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+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":"2026-05-10T15:59:46.142115Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-11T09:31:02.940632Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2502.00412","last_updated":"2025-03-11T07:44:46Z","snapshot_observed_at":"2026-08-09T19:05:11.623173Z","submitted_at":"2025-02-01T12:20:17Z","title":"TROI: Cross-Subject Pretraining with Sparse Voxel Selection for Enhanced fMRI Visual Decoding","version":2},"cited_work":{"arxiv_id":"2502.00412","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2502.00412","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Troi: Cross-subject pretraining with sparse voxel selection for enhanced fmri visual de- coding","venue":null,"work_id":"d31a8f27-6eca-4f06-a58f-a464a08449f4","year":2025},"citing_paper":{"arxiv_id":"2604.10617","last_updated":"2026-04-12T12:50:49Z","snapshot_observed_at":"2026-07-06T22:59:13.936436Z","submitted_at":"2026-04-12T12:50:49Z","title":"Brain-Grasp: Graph-based Saliency Priors for Improved fMRI-based Visual Brain Decoding","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-10T15:59:46.142115Z"},"links":{"cited_paper":"/paper/2502.00412","citing_paper":"/paper/2604.10617"},"observation_digest":"sha256:f660295f1e8cde63518bfc26cd08658593701ebffb72ad89280a74ca215649d0","observation_id":"001ed930-9ae1-4fd2-9633-80d93ed31009","resolution":{"observed_at":"2026-05-11T09:31:02.948075Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2502.00412/citation-record","integrity":"/paper/2502.00412/integrity","json":"/paper/2502.00412/citation-record.json","paper":"/paper/2502.00412"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T19:11:31.516527Z","title":"fmri-based decoding of visual information from human brain activity: A brief review","venue":null,"work_id":"a1d8099b-5697-4002-9e13-29e27465adfd","year":2021},"citing_paper":{"arxiv_id":"2502.00412","last_updated":"2025-03-11T07:44:46Z","snapshot_observed_at":"2026-08-09T19:05:11.623173Z","submitted_at":"2025-02-01T12:20:17Z","title":"TROI: Cross-Subject Pretraining with Sparse Voxel Selection for Enhanced fMRI Visual Decoding","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-09T19:11:31.113285Z"},"links":{"citing_paper":"/paper/2502.00412"},"observation_digest":"sha256:590a6e027a501cc6111cbb26588cd7cbd09abc868c4ebf1df3e61fb7c9faa7d5","observation_id":"54fbdc03-5f78-4dc0-a168-acc806304c1b","resolution":{"observed_at":"2026-08-09T19:11:31.520630Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-09T19:11:31.502554Z","title":"Reconstructing the mind’s eye: fmri-to-image with contrastive learning and diffusion priors","venue":null,"work_id":"aea7989f-a2b7-408d-9a6b-521384c5c830","year":2024},"citing_paper":{"arxiv_id":"2502.00412","last_updated":"2025-03-11T07:44:46Z","snapshot_observed_at":"2026-08-09T19:05:11.623173Z","submitted_at":"2025-02-01T12:20:17Z","title":"TROI: Cross-Subject Pretraining with Sparse Voxel Selection for Enhanced fMRI Visual Decoding","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-09T19:11:31.118299Z"},"links":{"citing_paper":"/paper/2502.00412"},"observation_digest":"sha256:a571e6f509c5d1b1da7529b95fbd5f649f339a48a0c14b4c9357a6d29392cbfe","observation_id":"4561b7b6-b314-41a4-913b-3fe2571d3a73","resolution":{"observed_at":"2026-08-09T19:11:31.507707Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.11207","last_updated":"2024-06-15T23:07:17Z","snapshot_observed_at":"2026-08-06T10:55:20.713624Z","submitted_at":"2024-03-17T13:15:22Z","title":"MindEye2: Shared-Subject Models Enable fMRI-To-Image With 1 Hour of Data","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.11207","snapshot_observed_at":"2026-08-09T19:11:31.122746Z","title":"Mindeye2: Shared-subject models enable fmri-to-image with 1 hour of data","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.00412","last_updated":"2025-03-11T07:44:46Z","snapshot_observed_at":"2026-08-09T19:05:11.623173Z","submitted_at":"2025-02-01T12:20:17Z","title":"TROI: Cross-Subject Pretraining with Sparse Voxel Selection for Enhanced fMRI Visual Decoding","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-09T19:11:31.122746Z"},"links":{"cited_paper":"/paper/2403.11207","citing_paper":"/paper/2502.00412"},"observation_digest":"sha256:96f9e0a0327d6e1ae78b819cc7cb19f6782a32a53216ca5c662914268621a16e","observation_id":"076386d5-fdce-4daf-b678-e9327a72c315","resolution":{"observed_at":"2026-08-09T19:11:31.122746Z","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":"2026-08-09T19:11:31.488416Z","title":"Reconstruction of perceived images from fmri patterns and semantic brain exploration using instance-conditioned gans","venue":null,"work_id":"3888f5df-dc1a-491b-9ead-79f23cd18e5f","year":2022},"citing_paper":{"arxiv_id":"2502.00412","last_updated":"2025-03-11T07:44:46Z","snapshot_observed_at":"2026-08-09T19:05:11.623173Z","submitted_at":"2025-02-01T12:20:17Z","title":"TROI: Cross-Subject Pretraining with Sparse Voxel Selection for Enhanced fMRI Visual Decoding","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-09T19:11:31.128575Z"},"links":{"citing_paper":"/paper/2502.00412"},"observation_digest":"sha256:fe2f3bde207aab0b2f85025f0a2d25b59f7211100cc57bd4c3f9f536a377e174","observation_id":"4983d861-c9d8-433b-b156-4aa38ea98a75","resolution":{"observed_at":"2026-08-09T19:11:31.493041Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-09T19:11:31.473639Z","title":"Natural scene reconstruction from fmri signals using generative latent diffusion","venue":null,"work_id":"6ac6fe68-e700-4d2d-a4a2-9015d7cb8309","year":2023},"citing_paper":{"arxiv_id":"2502.00412","last_updated":"2025-03-11T07:44:46Z","snapshot_observed_at":"2026-08-09T19:05:11.623173Z","submitted_at":"2025-02-01T12:20:17Z","title":"TROI: Cross-Subject Pretraining with Sparse Voxel Selection for Enhanced fMRI Visual Decoding","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-09T19:11:31.133082Z"},"links":{"citing_paper":"/paper/2502.00412"},"observation_digest":"sha256:a6621ec82ad4179033d27613692631d886173ffd447a59921e2fe75adef80e43","observation_id":"8d4bcd46-126e-447c-a48a-96067cd68b97","resolution":{"observed_at":"2026-08-09T19:11:31.478815Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-09T19:11:31.460741Z","title":"Reconstructing seen images from human brain activity via guided stochastic search","venue":null,"work_id":"6693e75c-fcb5-4294-98d2-de0e90310b51","year":2023},"citing_paper":{"arxiv_id":"2502.00412","last_updated":"2025-03-11T07:44:46Z","snapshot_observed_at":"2026-08-09T19:05:11.623173Z","submitted_at":"2025-02-01T12:20:17Z","title":"TROI: Cross-Subject Pretraining with Sparse Voxel Selection for Enhanced fMRI Visual Decoding","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-09T19:11:31.137577Z"},"links":{"citing_paper":"/paper/2502.00412"},"observation_digest":"sha256:803d63154148ce9767e382a245999ffe103dde8e8399954f50496f025c54b52c","observation_id":"08d5137f-49bc-4e1f-814e-a7f4affd23c3","resolution":{"observed_at":"2026-08-09T19:11:31.465258Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-09T19:11:31.445265Z","title":"Talairach and P","venue":null,"work_id":"f6699613-27ef-4366-ba4c-1a4cdcf0dd7c","year":1988},"citing_paper":{"arxiv_id":"2502.00412","last_updated":"2025-03-11T07:44:46Z","snapshot_observed_at":"2026-08-09T19:05:11.623173Z","submitted_at":"2025-02-01T12:20:17Z","title":"TROI: Cross-Subject Pretraining with Sparse Voxel Selection for Enhanced fMRI Visual Decoding","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-09T19:11:31.142305Z"},"links":{"citing_paper":"/paper/2502.00412"},"observation_digest":"sha256:ba2a845840e95ff98d0b4f312d64b4cec9d4427a9d79f6f3590172768ab63ae6","observation_id":"ead16ba4-d9e6-42d8-b29a-dc4827765892","resolution":{"observed_at":"2026-08-09T19:11:31.449432Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-09T19:11:31.432619Z","title":"A probabilistic atlas and reference system for the human brain: International consortium for brain mapping (icbm)","venue":null,"work_id":"0b6091b4-a0e7-476a-b30c-55fd7788dace","year":2001},"citing_paper":{"arxiv_id":"2502.00412","last_updated":"2025-03-11T07:44:46Z","snapshot_observed_at":"2026-08-09T19:05:11.623173Z","submitted_at":"2025-02-01T12:20:17Z","title":"TROI: Cross-Subject Pretraining with Sparse Voxel Selection for Enhanced fMRI Visual Decoding","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-09T19:11:31.146631Z"},"links":{"citing_paper":"/paper/2502.00412"},"observation_digest":"sha256:2aefa47bb2681803c29641a1778dac07ea8648409b7267ec3fbeaf135b6b9792","observation_id":"89dfc0e3-089d-4baa-9a2b-f03211e7e1a3","resolution":{"observed_at":"2026-08-09T19:11:31.436763Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-09T19:11:31.151204Z","title":"The wu-minn human connectome project: an overview","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2502.00412","last_updated":"2025-03-11T07:44:46Z","snapshot_observed_at":"2026-08-09T19:05:11.623173Z","submitted_at":"2025-02-01T12:20:17Z","title":"TROI: Cross-Subject Pretraining with Sparse Voxel Selection for Enhanced fMRI Visual Decoding","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-09T19:11:31.151204Z"},"links":{"citing_paper":"/paper/2502.00412"},"observation_digest":"sha256:b97f62d713ecbbf8ff57562e5104e36e4fb6734757aec0cbd7f0129e573642c8","observation_id":"bc7e704b-9f1a-4748-b9d8-a2b028fa1936","resolution":{"observed_at":"2026-08-09T19:11:31.151204Z","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":"2026-08-09T19:11:31.412804Z","title":"The anatomical and functional organization of the human visual pulvinar","venue":null,"work_id":"962393d1-caaf-4d2a-b424-7e594d6c3642","year":2015},"citing_paper":{"arxiv_id":"2502.00412","last_updated":"2025-03-11T07:44:46Z","snapshot_observed_at":"2026-08-09T19:05:11.623173Z","submitted_at":"2025-02-01T12:20:17Z","title":"TROI: Cross-Subject Pretraining with Sparse Voxel Selection for Enhanced fMRI Visual Decoding","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-09T19:11:31.155367Z"},"links":{"citing_paper":"/paper/2502.00412"},"observation_digest":"sha256:5fafabf25a76000bee5de352e40c008a06723b823a57f5fe47c51d1147626b99","observation_id":"7ba6c02f-315c-4776-bdf3-28e3dcb64baf","resolution":{"observed_at":"2026-08-09T19:11:31.417184Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-09T19:11:31.159869Z","title":"A massive 7t fmri dataset to bridge cognitive neuroscience and artificial intelligence","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2502.00412","last_updated":"2025-03-11T07:44:46Z","snapshot_observed_at":"2026-08-09T19:05:11.623173Z","submitted_at":"2025-02-01T12:20:17Z","title":"TROI: Cross-Subject Pretraining with Sparse Voxel Selection for Enhanced fMRI Visual Decoding","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-09T19:11:31.159869Z"},"links":{"citing_paper":"/paper/2502.00412"},"observation_digest":"sha256:dae8254439f494cdaac3329a266b2caac23a74e66586197a6f6211e1457d2eb6","observation_id":"7620b2bc-5a5b-4e5d-a2d0-8dc3cfc8db24","resolution":{"observed_at":"2026-08-09T19:11:31.159869Z","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":"2026-08-09T19:11:31.393036Z","title":"Investigations into resting-state connectivity using independent component analysis","venue":null,"work_id":"ff8dddff-cafe-4bb1-aad2-e05b2fbfaf84","year":2005},"citing_paper":{"arxiv_id":"2502.00412","last_updated":"2025-03-11T07:44:46Z","snapshot_observed_at":"2026-08-09T19:05:11.623173Z","submitted_at":"2025-02-01T12:20:17Z","title":"TROI: Cross-Subject Pretraining with Sparse Voxel Selection for Enhanced fMRI Visual Decoding","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-09T19:11:31.164445Z"},"links":{"citing_paper":"/paper/2502.00412"},"observation_digest":"sha256:92e03b8a0f175daa89cc6c0d9523a629106c95e5af41792d5e6573750316ddd1","observation_id":"b005371a-e174-45fd-a58f-d5ae34af626b","resolution":{"observed_at":"2026-08-09T19:11:31.397551Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-09T19:11:31.379353Z","title":"The organization of the human cerebral cortex estimated by intrinsic functional connectivity","venue":null,"work_id":"77b34d50-f9c8-4dc1-b60f-e254cabaa98c","year":2011},"citing_paper":{"arxiv_id":"2502.00412","last_updated":"2025-03-11T07:44:46Z","snapshot_observed_at":"2026-08-09T19:05:11.623173Z","submitted_at":"2025-02-01T12:20:17Z","title":"TROI: Cross-Subject Pretraining with Sparse Voxel Selection for Enhanced fMRI Visual Decoding","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-09T19:11:31.170128Z"},"links":{"citing_paper":"/paper/2502.00412"},"observation_digest":"sha256:cd9ca0a9f7a5ba142d8ea5598d2862f890442bc44228b7766159102474b6e6ee","observation_id":"470b7f7c-4214-4f90-869d-7a44707762d7","resolution":{"observed_at":"2026-08-09T19:11:31.384627Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-09T19:11:31.174294Z","title":"Regression shrinkage and selection via the lasso","venue":null,"work_id":null,"year":1996},"citing_paper":{"arxiv_id":"2502.00412","last_updated":"2025-03-11T07:44:46Z","snapshot_observed_at":"2026-08-09T19:05:11.623173Z","submitted_at":"2025-02-01T12:20:17Z","title":"TROI: Cross-Subject Pretraining with Sparse Voxel Selection for Enhanced fMRI Visual Decoding","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-09T19:11:31.174294Z"},"links":{"citing_paper":"/paper/2502.00412"},"observation_digest":"sha256:21c4f2264db2cfee09a97af6de92531f7680c5627e6d5168cd2b5d746398f278","observation_id":"74c0ea22-4a47-4dc0-825a-9c9cb035d69e","resolution":{"observed_at":"2026-08-09T19:11:31.174294Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2010.06300","last_updated":"2020-11-15T08:29:07Z","snapshot_observed_at":"2026-08-05T00:43:21.750337Z","submitted_at":"2020-10-13T11:34:25Z","title":"MixCo: Mix-up Contrastive Learning for Visual Representation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.06300","snapshot_observed_at":"2026-08-09T19:11:31.177547Z","title":"Mixco: Mix-up contrastive learning for visual representation","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2502.00412","last_updated":"2025-03-11T07:44:46Z","snapshot_observed_at":"2026-08-09T19:05:11.623173Z","submitted_at":"2025-02-01T12:20:17Z","title":"TROI: Cross-Subject Pretraining with Sparse Voxel Selection for Enhanced fMRI Visual Decoding","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-09T19:11:31.177547Z"},"links":{"cited_paper":"/paper/2010.06300","citing_paper":"/paper/2502.00412"},"observation_digest":"sha256:55a23b735084432f3a9889d1a58526adc8d99169881a465d3277d0be7fbb3bc9","observation_id":"62b8d1c6-f0ef-4175-baf8-d82cb6ce7b38","resolution":{"observed_at":"2026-08-09T19:11:31.177547Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.01475","last_updated":"2023-03-02T18:37:34Z","snapshot_observed_at":"2026-08-01T04:27:56.718815Z","submitted_at":"2023-03-02T18:37:34Z","title":"Over-training with Mixup May Hurt Generalization","version":1},"cited_work":{"arxiv_id":"2303.01475","doi":null,"metadata_source":"pith","pith_arxiv_id":"2303.01475","snapshot_observed_at":"2026-08-09T19:11:31.262498Z","title":"Over-training with Mixup May Hurt Generalization","venue":"cs.LG","work_id":"d3106fd6-06cc-49f5-9af7-49a306dd090c","year":2023},"citing_paper":{"arxiv_id":"2502.00412","last_updated":"2025-03-11T07:44:46Z","snapshot_observed_at":"2026-08-09T19:05:11.623173Z","submitted_at":"2025-02-01T12:20:17Z","title":"TROI: Cross-Subject Pretraining with Sparse Voxel Selection for Enhanced fMRI Visual Decoding","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-09T19:11:31.181162Z"},"links":{"cited_paper":"/paper/2303.01475","citing_paper":"/paper/2502.00412"},"observation_digest":"sha256:d662939cfbd37b7c7362bada3cb250164d7d1a2570bc26131107be9a80a4aaea","observation_id":"3d4740f6-49f2-4eeb-892d-97ce01686622","resolution":{"observed_at":"2026-08-09T19:11:31.268971Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-09T19:11:31.184749Z","title":"Hierarchical text-conditional image generation with clip latents, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2502.00412","last_updated":"2025-03-11T07:44:46Z","snapshot_observed_at":"2026-08-09T19:05:11.623173Z","submitted_at":"2025-02-01T12:20:17Z","title":"TROI: Cross-Subject Pretraining with Sparse Voxel Selection for Enhanced fMRI Visual Decoding","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-09T19:11:31.184749Z"},"links":{"citing_paper":"/paper/2502.00412"},"observation_digest":"sha256:74098e66a870a3c0ed0b1ad541af7c102ca2a59302c83a762c2c26b1fe53f3ca","observation_id":"a5d330b3-970a-4a6d-8606-3c92aac91baf","resolution":{"observed_at":"2026-08-09T19:11:31.184749Z","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":"2026-08-09T19:11:31.346040Z","title":"The human visual cortex","venue":null,"work_id":"00d2f9c3-286a-451b-aaec-01057da98e4b","year":2004},"citing_paper":{"arxiv_id":"2502.00412","last_updated":"2025-03-11T07:44:46Z","snapshot_observed_at":"2026-08-09T19:05:11.623173Z","submitted_at":"2025-02-01T12:20:17Z","title":"TROI: Cross-Subject Pretraining with Sparse Voxel Selection for Enhanced fMRI Visual Decoding","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-09T19:11:31.188627Z"},"links":{"citing_paper":"/paper/2502.00412"},"observation_digest":"sha256:bcaf452f7539389e6ec16ca8d5c1f9cb93f52495fb4cf631d9385665a58297b1","observation_id":"cb7e3574-da83-4730-b63b-f79e0fdf7256","resolution":{"observed_at":"2026-08-09T19:11:31.351243Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-09T19:11:31.192576Z","title":"Channel pruning for accelerating very deep neural networks","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2502.00412","last_updated":"2025-03-11T07:44:46Z","snapshot_observed_at":"2026-08-09T19:05:11.623173Z","submitted_at":"2025-02-01T12:20:17Z","title":"TROI: Cross-Subject Pretraining with Sparse Voxel Selection for Enhanced fMRI Visual Decoding","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-09T19:11:31.192576Z"},"links":{"citing_paper":"/paper/2502.00412"},"observation_digest":"sha256:69dad78736c22829d1a1c53301f8ffacd5def7cf7699d03616e04d69dbd0a1c2","observation_id":"0866a66f-1311-4e47-836d-e4bf2e1952e4","resolution":{"observed_at":"2026-08-09T19:11:31.192576Z","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":"2026-08-09T19:11:31.196483Z","title":"Learning structured sparsity in deep neural networks","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2502.00412","last_updated":"2025-03-11T07:44:46Z","snapshot_observed_at":"2026-08-09T19:05:11.623173Z","submitted_at":"2025-02-01T12:20:17Z","title":"TROI: Cross-Subject Pretraining with Sparse Voxel Selection for Enhanced fMRI Visual Decoding","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-09T19:11:31.196483Z"},"links":{"citing_paper":"/paper/2502.00412"},"observation_digest":"sha256:ad89ce7a91a9abfd2fff6b80aa4b8ebe19ccb920786c84deeb5cd45f436417bd","observation_id":"6f8f5f78-0d18-4fbd-a810-c168b07d4a12","resolution":{"observed_at":"2026-08-09T19:11:31.196483Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2003.02389","last_updated":"2020-03-05T00:53:18Z","snapshot_observed_at":"2026-08-03T12:12:31.487587Z","submitted_at":"2020-03-05T00:53:18Z","title":"Comparing Rewinding and Fine-tuning in Neural Network Pruning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2003.02389","snapshot_observed_at":"2026-08-09T19:11:31.201754Z","title":"Comparing rewinding and fine-tuning in neural network pruning","venue":null,"work_id":null,"year":2003},"citing_paper":{"arxiv_id":"2502.00412","last_updated":"2025-03-11T07:44:46Z","snapshot_observed_at":"2026-08-09T19:05:11.623173Z","submitted_at":"2025-02-01T12:20:17Z","title":"TROI: Cross-Subject Pretraining with Sparse Voxel Selection for Enhanced fMRI Visual Decoding","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-09T19:11:31.201754Z"},"links":{"cited_paper":"/paper/2003.02389","citing_paper":"/paper/2502.00412"},"observation_digest":"sha256:50f726a8a980f084604717903c38d81bd8e5cdf505077ddaeb906aa7ad8c233b","observation_id":"5aedab51-328b-44e2-af8e-3890c51c0b4f","resolution":{"observed_at":"2026-08-09T19:11:31.201754Z","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":"2026-08-09T19:11:31.206216Z","title":"Microsoft coco: Common objects in context","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2502.00412","last_updated":"2025-03-11T07:44:46Z","snapshot_observed_at":"2026-08-09T19:05:11.623173Z","submitted_at":"2025-02-01T12:20:17Z","title":"TROI: Cross-Subject Pretraining with Sparse Voxel Selection for Enhanced fMRI Visual Decoding","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-09T19:11:31.206216Z"},"links":{"citing_paper":"/paper/2502.00412"},"observation_digest":"sha256:469eeae879401cfd34cdbda216004d7d81c1bdd0d0e246da01d8ae113d21c0d2","observation_id":"325351e6-658f-40c3-9556-5def21bd4cbc","resolution":{"observed_at":"2026-08-09T19:11:31.206216Z","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":"2026-08-09T19:11:31.210131Z","title":"Image quality assessment: from error visibility to structural similarity","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2502.00412","last_updated":"2025-03-11T07:44:46Z","snapshot_observed_at":"2026-08-09T19:05:11.623173Z","submitted_at":"2025-02-01T12:20:17Z","title":"TROI: Cross-Subject Pretraining with Sparse Voxel Selection for Enhanced fMRI Visual Decoding","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-09T19:11:31.210131Z"},"links":{"citing_paper":"/paper/2502.00412"},"observation_digest":"sha256:1bcc58949f997f48d9acd7c34dc6f8b6473d326be04301ca8d90b71ce4e3adfb","observation_id":"2471f95e-aff5-4787-b612-6ae48777f682","resolution":{"observed_at":"2026-08-09T19:11:31.210131Z","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":"2026-08-09T19:11:31.214131Z","title":"Unsupervised learning of visual features by contrasting cluster assignments","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2502.00412","last_updated":"2025-03-11T07:44:46Z","snapshot_observed_at":"2026-08-09T19:05:11.623173Z","submitted_at":"2025-02-01T12:20:17Z","title":"TROI: Cross-Subject Pretraining with Sparse Voxel Selection for Enhanced fMRI Visual Decoding","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-09T19:11:31.214131Z"},"links":{"citing_paper":"/paper/2502.00412"},"observation_digest":"sha256:0d2333b8423769b764d2af6a8db83b3c7394d15235ef6d91a89d83097b68403d","observation_id":"848c41d2-40d1-4698-87ad-da69fb49dd9c","resolution":{"observed_at":"2026-08-09T19:11:31.214131Z","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":"2026-08-09T19:11:31.300386Z","title":"Rethinking the inception architecture for computer vision","venue":null,"work_id":"b7636b24-0319-49e8-879f-f8089e59f33f","year":2016},"citing_paper":{"arxiv_id":"2502.00412","last_updated":"2025-03-11T07:44:46Z","snapshot_observed_at":"2026-08-09T19:05:11.623173Z","submitted_at":"2025-02-01T12:20:17Z","title":"TROI: Cross-Subject Pretraining with Sparse Voxel Selection for Enhanced fMRI Visual Decoding","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-09T19:11:31.218050Z"},"links":{"citing_paper":"/paper/2502.00412"},"observation_digest":"sha256:8ec21904fc52aea04123b41baeac80a261cb40787db2499a8dd98a72959cebfb","observation_id":"b8d0cef7-c70e-474d-ad79-0fdc71c7c9c7","resolution":{"observed_at":"2026-08-09T19:11:31.303769Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2502.00412","last_updated":"2025-03-11T07:44:46Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-09T19:05:11.623173Z","submitted_at":"2025-02-01T12:20:17Z","title":"TROI: Cross-Subject Pretraining with Sparse Voxel Selection for Enhanced fMRI Visual Decoding"},"reference_resolution":{"displayed":25,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":12,"verified_exact":1,"verified_fuzzy":12},"total_outbound_references":25},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 1 inbound Pith citation observation for arXiv:2502.00412."}