{"as_of":"2026-08-09T23:45:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:c5df7e6998545a92c1b2181091e9d54dba01633a0e42b43897374a9d4e8b8363","coverage":[{"denominator":28,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":28,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T23:39:38.578568Z","state":"measured"},{"denominator":29,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":29,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+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":"2026-08-06T20:08:11.644258Z","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":"2026-08-06T20:08:12.262871Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2502.09669","last_updated":"2025-02-12T21:54:22Z","snapshot_observed_at":"2026-08-09T11:17:32.506759Z","submitted_at":"2025-02-12T21:54:22Z","title":"Meta-INR: Efficient Encoding of Volumetric Data via Meta-Learning Implicit Neural Representation","version":1},"cited_work":{"arxiv_id":"2502.09669","doi":null,"metadata_source":"pith","pith_arxiv_id":"2502.09669","snapshot_observed_at":"2026-08-06T20:08:12.262871Z","title":"Meta-INR: Efficient Encoding of Volumetric Data via Meta-Learning Implicit Neural Representation","venue":"cs.CV","work_id":"ff5c9ca8-c0ac-4325-9f6c-27bfe88149dd","year":2025},"citing_paper":{"arxiv_id":"2507.03836","last_updated":"2025-07-04T23:23:26Z","snapshot_observed_at":"2026-08-09T11:17:50.326969Z","submitted_at":"2025-07-04T23:23:26Z","title":"F-Hash: Feature-Based Hash Design for Time-Varying Volume Visualization via Multi-Resolution Tesseract Encoding","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-06T20:08:11.644258Z"},"links":{"cited_paper":"/paper/2502.09669","citing_paper":"/paper/2507.03836"},"observation_digest":"sha256:fd3b8f188532de508b070ee97689043723d4b243e29f8e24f1fa9dc027b4bb94","observation_id":"e2944d25-9f29-470b-8e8d-1da8df18f639","resolution":{"observed_at":"2026-08-06T20:08:12.270036Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2502.09669/citation-record","integrity":"/paper/2502.09669/integrity","json":"/paper/2502.09669/citation-record.json","paper":"/paper/2502.09669"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:39:38.428497Z","title":null,"venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2502.09669","last_updated":"2025-02-12T21:54:22Z","snapshot_observed_at":"2026-08-09T11:17:32.506759Z","submitted_at":"2025-02-12T21:54:22Z","title":"Meta-INR: Efficient Encoding of Volumetric Data via Meta-Learning Implicit Neural Representation","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T23:39:38.428497Z"},"links":{"citing_paper":"/paper/2502.09669"},"observation_digest":"sha256:d4272360c5132bd9ea5855ac04c21a9dd7469e33f1ffa46e2834f10b2e6bdce9","observation_id":"2e89b91e-41b4-4aa6-8e8d-9fdee831b3cf","resolution":{"observed_at":"2026-08-07T23:39:38.428497Z","resolver_source":null,"status":"malformed_identifier"},"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":"2026-08-07T23:39:41.180230Z","title":"Dupont, H","venue":null,"work_id":"b6428b2a-dd75-4a2b-a280-97bb13032b8d","year":2022},"citing_paper":{"arxiv_id":"2502.09669","last_updated":"2025-02-12T21:54:22Z","snapshot_observed_at":"2026-08-09T11:17:32.506759Z","submitted_at":"2025-02-12T21:54:22Z","title":"Meta-INR: Efficient Encoding of Volumetric Data via Meta-Learning Implicit Neural Representation","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T23:39:38.434850Z"},"links":{"citing_paper":"/paper/2502.09669"},"observation_digest":"sha256:18eec46630c79a84d41b5f4dc458715c148de8479e06d7a5b0fc7cc60e836e60","observation_id":"a422b0d9-cd76-49e8-a00e-33d1495c8c1e","resolution":{"observed_at":"2026-08-07T23:39:41.185062Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:39:41.099856Z","title":null,"venue":null,"work_id":"6d68eb6e-9b9c-408b-9dad-82e30b159b2d","year":2017},"citing_paper":{"arxiv_id":"2502.09669","last_updated":"2025-02-12T21:54:22Z","snapshot_observed_at":"2026-08-09T11:17:32.506759Z","submitted_at":"2025-02-12T21:54:22Z","title":"Meta-INR: Efficient Encoding of Volumetric Data via Meta-Learning Implicit Neural Representation","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T23:39:38.439903Z"},"links":{"citing_paper":"/paper/2502.09669"},"observation_digest":"sha256:98cfec328ff39c8a19529f024d96da89c8db343cde08e0b42e314059c52b0dbf","observation_id":"d678adc9-f30b-45dd-8f70-6b2825b495da","resolution":{"observed_at":"2026-08-07T23:39:41.104608Z","resolver_source":"arxiv_id_nonexistent","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T23:39:41.164910Z","title":null,"venue":null,"work_id":"9c636446-0aa9-4d2a-88ad-2b68a3fd1397","year":2023},"citing_paper":{"arxiv_id":"2502.09669","last_updated":"2025-02-12T21:54:22Z","snapshot_observed_at":"2026-08-09T11:17:32.506759Z","submitted_at":"2025-02-12T21:54:22Z","title":"Meta-INR: Efficient Encoding of Volumetric Data via Meta-Learning Implicit Neural Representation","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T23:39:38.445135Z"},"links":{"citing_paper":"/paper/2502.09669"},"observation_digest":"sha256:e8e90b4e8f3f8b46eac1f65fe308a14d66d41aa53a5c3b603ecacb794e3921a1","observation_id":"b5296fba-328b-432a-ade3-67a5efb63c53","resolution":{"observed_at":"2026-08-07T23:39:41.169657Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:39:40.928309Z","title":"Han and C","venue":null,"work_id":"90597420-620c-420a-9462-7a7df05d91af","year":2023},"citing_paper":{"arxiv_id":"2502.09669","last_updated":"2025-02-12T21:54:22Z","snapshot_observed_at":"2026-08-09T11:17:32.506759Z","submitted_at":"2025-02-12T21:54:22Z","title":"Meta-INR: Efficient Encoding of Volumetric Data via Meta-Learning Implicit Neural Representation","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T23:39:38.450672Z"},"links":{"citing_paper":"/paper/2502.09669"},"observation_digest":"sha256:3fd45e758bfafb9c743198a44bed7c39844069c0c23e277f2409956526e67431","observation_id":"00a87719-bae9-4b5f-ba4d-fb50317f7e76","resolution":{"observed_at":"2026-08-07T23:39:40.935582Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:39:40.769782Z","title":null,"venue":null,"work_id":"541a1959-2e88-46d9-8176-416bd482e4c7","year":2024},"citing_paper":{"arxiv_id":"2502.09669","last_updated":"2025-02-12T21:54:22Z","snapshot_observed_at":"2026-08-09T11:17:32.506759Z","submitted_at":"2025-02-12T21:54:22Z","title":"Meta-INR: Efficient Encoding of Volumetric Data via Meta-Learning Implicit Neural Representation","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T23:39:38.455876Z"},"links":{"citing_paper":"/paper/2502.09669"},"observation_digest":"sha256:80a492cae2cdbe02cbd000f5e6e3d694be8ae92f48b984b7ce7e9ae3ebe7cd72","observation_id":"f176857c-27b6-4e0f-bef7-554972a67448","resolution":{"observed_at":"2026-08-07T23:39:40.774962Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:39:40.570560Z","title":null,"venue":null,"work_id":"5a97a5b6-fba2-465c-8602-9a56ab8b7316","year":2022},"citing_paper":{"arxiv_id":"2502.09669","last_updated":"2025-02-12T21:54:22Z","snapshot_observed_at":"2026-08-09T11:17:32.506759Z","submitted_at":"2025-02-12T21:54:22Z","title":"Meta-INR: Efficient Encoding of Volumetric Data via Meta-Learning Implicit Neural Representation","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T23:39:38.462021Z"},"links":{"citing_paper":"/paper/2502.09669"},"observation_digest":"sha256:3731c4fbb0cfd37bbb582d3c7e4ac094bcbd8a663992dd0ef75a554ce315c990","observation_id":"f23f3ad7-4c9d-4344-961c-6e6df5007a87","resolution":{"observed_at":"2026-08-07T23:39:40.577840Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:39:40.402722Z","title":"Li and H.-W","venue":null,"work_id":"43c65884-63ce-4299-8e43-1b6caaa664ff","year":2024},"citing_paper":{"arxiv_id":"2502.09669","last_updated":"2025-02-12T21:54:22Z","snapshot_observed_at":"2026-08-09T11:17:32.506759Z","submitted_at":"2025-02-12T21:54:22Z","title":"Meta-INR: Efficient Encoding of Volumetric Data via Meta-Learning Implicit Neural Representation","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T23:39:38.467216Z"},"links":{"citing_paper":"/paper/2502.09669"},"observation_digest":"sha256:212cdbf9361fa974cf2d97185463e47091a9eb21c029fc5ba5b61b5cc9e57b54","observation_id":"16a810c4-59ba-4401-8977-7d0ee31a1aeb","resolution":{"observed_at":"2026-08-07T23:39:40.408300Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:39:40.202723Z","title":null,"venue":null,"work_id":"66c95d80-c2c0-43e2-bc1b-817fabb23a76","year":2024},"citing_paper":{"arxiv_id":"2502.09669","last_updated":"2025-02-12T21:54:22Z","snapshot_observed_at":"2026-08-09T11:17:32.506759Z","submitted_at":"2025-02-12T21:54:22Z","title":"Meta-INR: Efficient Encoding of Volumetric Data via Meta-Learning Implicit Neural Representation","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T23:39:38.472038Z"},"links":{"citing_paper":"/paper/2502.09669"},"observation_digest":"sha256:acee17e92d4a44d8fa972d7f900ac91897e4e18ceb3b56ad2a6791dc42c14a9c","observation_id":"830c14cd-e262-4df1-a435-89b386a1f55f","resolution":{"observed_at":"2026-08-07T23:39:40.208374Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T23:39:38.476901Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2502.09669","last_updated":"2025-02-12T21:54:22Z","snapshot_observed_at":"2026-08-09T11:17:32.506759Z","submitted_at":"2025-02-12T21:54:22Z","title":"Meta-INR: Efficient Encoding of Volumetric Data via Meta-Learning Implicit Neural Representation","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T23:39:38.476901Z"},"links":{"citing_paper":"/paper/2502.09669"},"observation_digest":"sha256:7fda38719b7bf41afc99d7e41ac8e177b4cb21f9cd4b85ff3266b45e5772615c","observation_id":"6efc54fe-1284-4d69-893b-6d3b1c629d33","resolution":{"observed_at":"2026-08-07T23:39:38.476901Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1803.02999","last_updated":"2018-10-22T16:11:14Z","snapshot_observed_at":"2026-08-05T12:53:31.632675Z","submitted_at":"2018-03-08T08:29:38Z","title":"On First-Order Meta-Learning Algorithms","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1803.02999","snapshot_observed_at":"2026-08-07T23:39:38.482235Z","title":"Nichol, A","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2502.09669","last_updated":"2025-02-12T21:54:22Z","snapshot_observed_at":"2026-08-09T11:17:32.506759Z","submitted_at":"2025-02-12T21:54:22Z","title":"Meta-INR: Efficient Encoding of Volumetric Data via Meta-Learning Implicit Neural Representation","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T23:39:38.482235Z"},"links":{"cited_paper":"/paper/1803.02999","citing_paper":"/paper/2502.09669"},"observation_digest":"sha256:2d24f72dc87ff41d89bdb8f503f7ba2a0164c5f6f9a1028736573fc0f3e84575","observation_id":"3b3b852f-b348-4b70-b354-3f45cd056ee7","resolution":{"observed_at":"2026-08-07T23:39:38.482235Z","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":"10.1175/1520-0426(2004)021","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:39:38.702381Z","title":"Popinet, M","venue":null,"work_id":"18e51ad5-63f9-4ec6-bc32-123b7b8f9fce","year":2004},"citing_paper":{"arxiv_id":"2502.09669","last_updated":"2025-02-12T21:54:22Z","snapshot_observed_at":"2026-08-09T11:17:32.506759Z","submitted_at":"2025-02-12T21:54:22Z","title":"Meta-INR: Efficient Encoding of Volumetric Data via Meta-Learning Implicit Neural Representation","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T23:39:38.488607Z"},"links":{"citing_paper":"/paper/2502.09669"},"observation_digest":"sha256:0f7f1b8128838a91fd7183b5759ac99a9de653f9fcab66e1b95860e386eb25be","observation_id":"ce7af795-b163-4301-8204-b08bdfa50ddc","resolution":{"observed_at":"2026-08-07T23:39:38.708186Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T23:39:38.494695Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2502.09669","last_updated":"2025-02-12T21:54:22Z","snapshot_observed_at":"2026-08-09T11:17:32.506759Z","submitted_at":"2025-02-12T21:54:22Z","title":"Meta-INR: Efficient Encoding of Volumetric Data via Meta-Learning Implicit Neural Representation","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T23:39:38.494695Z"},"links":{"citing_paper":"/paper/2502.09669"},"observation_digest":"sha256:3c5f8d4765c42e76934d90357bd09d5c261d78565e5dbcd387a1e6735f769a8d","observation_id":"68fad8d0-043c-4459-8a9c-2000696bbfe9","resolution":{"observed_at":"2026-08-07T23:39:38.494695Z","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":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:39:40.000999Z","title":null,"venue":null,"work_id":"86ac12c1-8860-4fbd-a09f-3a119666d9bf","year":2019},"citing_paper":{"arxiv_id":"2502.09669","last_updated":"2025-02-12T21:54:22Z","snapshot_observed_at":"2026-08-09T11:17:32.506759Z","submitted_at":"2025-02-12T21:54:22Z","title":"Meta-INR: Efficient Encoding of Volumetric Data via Meta-Learning Implicit Neural Representation","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T23:39:38.500847Z"},"links":{"citing_paper":"/paper/2502.09669"},"observation_digest":"sha256:a0813b2cfdf4763b8cef06cc058ef7f74dc0c2681ecc4a7fda9b347546846abd","observation_id":"53941383-40c4-46bb-965b-909b0dae0659","resolution":{"observed_at":"2026-08-07T23:39:40.005986Z","resolver_source":"arxiv_id_nonexistent","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:39:39.840873Z","title":"Silver and X","venue":null,"work_id":"b78d3cc9-48b8-4031-a51e-62212a0d5b4e","year":1997},"citing_paper":{"arxiv_id":"2502.09669","last_updated":"2025-02-12T21:54:22Z","snapshot_observed_at":"2026-08-09T11:17:32.506759Z","submitted_at":"2025-02-12T21:54:22Z","title":"Meta-INR: Efficient Encoding of Volumetric Data via Meta-Learning Implicit Neural Representation","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T23:39:38.505608Z"},"links":{"citing_paper":"/paper/2502.09669"},"observation_digest":"sha256:dc9cf7673eee5468d353ed8a8e63fb5858f3d0d1f166e8496bebbddcea130710","observation_id":"ff16162d-e13e-4bc4-99cb-6aa9f2b83695","resolution":{"observed_at":"2026-08-07T23:39:39.847100Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2006.09662","last_updated":"2020-06-17T05:14:53Z","snapshot_observed_at":"2026-08-03T18:45:36.327859Z","submitted_at":"2020-06-17T05:14:53Z","title":"MetaSDF: Meta-learning Signed Distance Functions","version":1},"cited_work":{"arxiv_id":"2006.09662","doi":"10.48550/arxiv.2006.09662","metadata_source":"pith","pith_arxiv_id":"2006.09662","snapshot_observed_at":"2026-08-08T00:16:16.039225Z","title":"MetaSDF: Meta-learning Signed Distance Functions","venue":"cs.CV","work_id":"ca62809c-61da-45be-b8d9-88c4569e7e3c","year":2020},"citing_paper":{"arxiv_id":"2502.09669","last_updated":"2025-02-12T21:54:22Z","snapshot_observed_at":"2026-08-09T11:17:32.506759Z","submitted_at":"2025-02-12T21:54:22Z","title":"Meta-INR: Efficient Encoding of Volumetric Data via Meta-Learning Implicit Neural Representation","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T23:39:38.510704Z"},"links":{"cited_paper":"/paper/2006.09662","citing_paper":"/paper/2502.09669"},"observation_digest":"sha256:94c770499ee334d606c0ecaaaeca760ea3d75702c91a1d49081db19e52c39a90","observation_id":"9255258f-8a8b-43fd-b5ba-8a9c3e50d086","resolution":{"observed_at":"2026-08-07T23:39:38.675086Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2006.09661","last_updated":"2020-06-17T05:13:33Z","snapshot_observed_at":"2026-08-09T11:16:50.938045Z","submitted_at":"2020-06-17T05:13:33Z","title":"Implicit Neural Representations with Periodic Activation Functions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2006.09661","snapshot_observed_at":"2026-08-07T23:39:38.516175Z","title":"Sitzmann, J","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2502.09669","last_updated":"2025-02-12T21:54:22Z","snapshot_observed_at":"2026-08-09T11:17:32.506759Z","submitted_at":"2025-02-12T21:54:22Z","title":"Meta-INR: Efficient Encoding of Volumetric Data via Meta-Learning Implicit Neural Representation","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T23:39:38.516175Z"},"links":{"cited_paper":"/paper/2006.09661","citing_paper":"/paper/2502.09669"},"observation_digest":"sha256:f046c824a3fcfb7a93a6914a1a018fffa92b96e6fbaebe3a6eb7d14b3ce2feb7","observation_id":"d6ab7378-c982-47ca-a23a-3518d1025e33","resolution":{"observed_at":"2026-08-07T23:39:38.516175Z","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":"2026-08-07T23:39:38.521231Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.09669","last_updated":"2025-02-12T21:54:22Z","snapshot_observed_at":"2026-08-09T11:17:32.506759Z","submitted_at":"2025-02-12T21:54:22Z","title":"Meta-INR: Efficient Encoding of Volumetric Data via Meta-Learning Implicit Neural Representation","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T23:39:38.521231Z"},"links":{"citing_paper":"/paper/2502.09669"},"observation_digest":"sha256:5deb7ae3326269b1b76732a495d27cefd48f3b4050a650de54616f1ee89544cc","observation_id":"6c8fa7a9-56b4-4fa7-8dd7-2b0bd978978e","resolution":{"observed_at":"2026-08-07T23:39:38.521231Z","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":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:39:39.656491Z","title":"Tancik, B","venue":null,"work_id":"023a4f8a-c7c5-46c7-b692-420b21c7b4e7","year":2021},"citing_paper":{"arxiv_id":"2502.09669","last_updated":"2025-02-12T21:54:22Z","snapshot_observed_at":"2026-08-09T11:17:32.506759Z","submitted_at":"2025-02-12T21:54:22Z","title":"Meta-INR: Efficient Encoding of Volumetric Data via Meta-Learning Implicit Neural Representation","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T23:39:38.526940Z"},"links":{"citing_paper":"/paper/2502.09669"},"observation_digest":"sha256:3bb13e856ca490218d27156fdd1aee14fe976db4cf2bddd60ed24309df517932","observation_id":"f8a97920-00fc-4cf1-b810-cf81bc01de07","resolution":{"observed_at":"2026-08-07T23:39:39.661396Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:39:39.610588Z","title":"Tang and C","venue":null,"work_id":"0a82b1ab-9c4d-43e8-bef1-9e80d9be6236","year":2024},"citing_paper":{"arxiv_id":"2502.09669","last_updated":"2025-02-12T21:54:22Z","snapshot_observed_at":"2026-08-09T11:17:32.506759Z","submitted_at":"2025-02-12T21:54:22Z","title":"Meta-INR: Efficient Encoding of Volumetric Data via Meta-Learning Implicit Neural Representation","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T23:39:38.531366Z"},"links":{"citing_paper":"/paper/2502.09669"},"observation_digest":"sha256:7fedf03110b6d736bae9cf5b3d7d9c983f3fbc420bffdc675b56b28fbcd29516","observation_id":"a4fc28ec-19c8-473e-83ff-39ed64919dce","resolution":{"observed_at":"2026-08-07T23:39:39.615510Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T23:39:41.149259Z","title":"Tang and C","venue":null,"work_id":"77cbe333-7534-49bc-9c40-0e1d1a618469","year":2024},"citing_paper":{"arxiv_id":"2502.09669","last_updated":"2025-02-12T21:54:22Z","snapshot_observed_at":"2026-08-09T11:17:32.506759Z","submitted_at":"2025-02-12T21:54:22Z","title":"Meta-INR: Efficient Encoding of Volumetric Data via Meta-Learning Implicit Neural Representation","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T23:39:38.536685Z"},"links":{"citing_paper":"/paper/2502.09669"},"observation_digest":"sha256:0d69ad5b66d631a3c19334f6a756da14789a803c5083665d3ad801f95d5eff6c","observation_id":"0cc5ee1e-b3ad-4b42-9f51-647d05842bd2","resolution":{"observed_at":"2026-08-07T23:39:41.154210Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T23:39:41.133739Z","title":"van der Maaten and G","venue":null,"work_id":"4ac5a5b0-c7e4-4bd8-8eb7-9601b0292f27","year":2008},"citing_paper":{"arxiv_id":"2502.09669","last_updated":"2025-02-12T21:54:22Z","snapshot_observed_at":"2026-08-09T11:17:32.506759Z","submitted_at":"2025-02-12T21:54:22Z","title":"Meta-INR: Efficient Encoding of Volumetric Data via Meta-Learning Implicit Neural Representation","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T23:39:38.546683Z"},"links":{"citing_paper":"/paper/2502.09669"},"observation_digest":"sha256:12fc808870d42a585d578499d3e1d85d704a3577f3fc2b7d038e34f3e80186e6","observation_id":"8ad124b6-dabc-4007-87ff-e09fc0730d86","resolution":{"observed_at":"2026-08-07T23:39:41.138791Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:39:39.257661Z","title":"Wang and J","venue":null,"work_id":"1cd48055-8e9f-464b-9e6b-ed038087722b","year":2023},"citing_paper":{"arxiv_id":"2502.09669","last_updated":"2025-02-12T21:54:22Z","snapshot_observed_at":"2026-08-09T11:17:32.506759Z","submitted_at":"2025-02-12T21:54:22Z","title":"Meta-INR: Efficient Encoding of Volumetric Data via Meta-Learning Implicit Neural Representation","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T23:39:38.551449Z"},"links":{"citing_paper":"/paper/2502.09669"},"observation_digest":"sha256:743f01aeb0adf1f42aecc6ea6ba5af6a47c953158975c094be1f39c61804dcf2","observation_id":"b0903f5a-efba-4397-a426-a81b82a0196d","resolution":{"observed_at":"2026-08-07T23:39:39.262292Z","resolver_source":"arxiv_id_nonexistent","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T23:39:38.557183Z","title":"Weiss, P","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2502.09669","last_updated":"2025-02-12T21:54:22Z","snapshot_observed_at":"2026-08-09T11:17:32.506759Z","submitted_at":"2025-02-12T21:54:22Z","title":"Meta-INR: Efficient Encoding of Volumetric Data via Meta-Learning Implicit Neural Representation","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T23:39:38.557183Z"},"links":{"citing_paper":"/paper/2502.09669"},"observation_digest":"sha256:f08d6541cc1b0174a24ad35fb35f80a695a957b172fb5a7aa6ce77bf9d55c5bb","observation_id":"3d385d46-05e1-4a03-ab5e-d168db2bec09","resolution":{"observed_at":"2026-08-07T23:39:38.557183Z","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":"2026-08-07T23:39:38.562057Z","title":"Whalen and M","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2502.09669","last_updated":"2025-02-12T21:54:22Z","snapshot_observed_at":"2026-08-09T11:17:32.506759Z","submitted_at":"2025-02-12T21:54:22Z","title":"Meta-INR: Efficient Encoding of Volumetric Data via Meta-Learning Implicit Neural Representation","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T23:39:38.562057Z"},"links":{"citing_paper":"/paper/2502.09669"},"observation_digest":"sha256:2dc675a0352043580289a1aa8d9107a7eeafe23dfd655a98175f70dbc3a05adb","observation_id":"4bda73a3-a14d-48bc-9333-5dc23a915894","resolution":{"observed_at":"2026-08-07T23:39:38.562057Z","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":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:39:39.018433Z","title":null,"venue":null,"work_id":"e6757523-4981-4814-ae9c-63230e23ed97","year":2024},"citing_paper":{"arxiv_id":"2502.09669","last_updated":"2025-02-12T21:54:22Z","snapshot_observed_at":"2026-08-09T11:17:32.506759Z","submitted_at":"2025-02-12T21:54:22Z","title":"Meta-INR: Efficient Encoding of Volumetric Data via Meta-Learning Implicit Neural Representation","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T23:39:38.567838Z"},"links":{"citing_paper":"/paper/2502.09669"},"observation_digest":"sha256:2dfa09c8313f13ad29ec975d862e9975cdb3a0af132a1b31e6851077feff42f6","observation_id":"38b764d0-bf31-40e8-9ef2-582bfa989ec1","resolution":{"observed_at":"2026-08-07T23:39:39.023383Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:39:39.438234Z","title":"Xiong, S","venue":null,"work_id":"21c42142-57a9-4bf8-b1a2-f46cc567ca3c","year":2025},"citing_paper":{"arxiv_id":"2502.09669","last_updated":"2025-02-12T21:54:22Z","snapshot_observed_at":"2026-08-09T11:17:32.506759Z","submitted_at":"2025-02-12T21:54:22Z","title":"Meta-INR: Efficient Encoding of Volumetric Data via Meta-Learning Implicit Neural Representation","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T23:39:38.573661Z"},"links":{"citing_paper":"/paper/2502.09669"},"observation_digest":"sha256:47ce33c9bbd12f500b0b6d10714ea8af47e7f8912a82b6b0b9d5fac3b8fd7196","observation_id":"415812ab-704b-4e70-8f21-5fc3c9e756da","resolution":{"observed_at":"2026-08-07T23:39:39.443303Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T23:39:41.116146Z","title":null,"venue":null,"work_id":"b266bc81-8279-48b5-8bce-74fa9144a8cd","year":2025},"citing_paper":{"arxiv_id":"2502.09669","last_updated":"2025-02-12T21:54:22Z","snapshot_observed_at":"2026-08-09T11:17:32.506759Z","submitted_at":"2025-02-12T21:54:22Z","title":"Meta-INR: Efficient Encoding of Volumetric Data via Meta-Learning Implicit Neural Representation","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T23:39:38.578568Z"},"links":{"citing_paper":"/paper/2502.09669"},"observation_digest":"sha256:e3a9f721b92f331f8b08c18a75b8635c2ce8ed53a368f6b576056d603446f619","observation_id":"31686f6d-f287-40ea-a5d9-808e4882df7e","resolution":{"observed_at":"2026-08-07T23:39:41.122339Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2502.09669","last_updated":"2025-02-12T21:54:22Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-09T11:17:32.506759Z","submitted_at":"2025-02-12T21:54:22Z","title":"Meta-INR: Efficient Encoding of Volumetric Data via Meta-Learning Implicit Neural Representation"},"reference_resolution":{"displayed":28,"state_counts":{"malformed_identifier":5,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":9,"verified_exact":12,"verified_fuzzy":2},"total_outbound_references":28},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 1 inbound Pith citation observation for arXiv:2502.09669."}