{"as_of":"2026-08-11T20:42:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:60656df70b6f719cf4a62334833f09c32f9206ae187e0a0d1357be9caef6bae4","coverage":[{"denominator":47,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":47,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T11:00:18.192857Z","state":"measured"},{"denominator":47,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":47,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-11T06:34:44.6726+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2501.16760/citation-record","integrity":"/paper/2501.16760/integrity","json":"/paper/2501.16760/citation-record.json","paper":"/paper/2501.16760"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T11:00:18.494587Z","title":"Seismic layer segmentation models with channel attention block in carbon storage study,","venue":null,"work_id":"3f501b67-9825-4f5f-92b7-134d1d8c22b0","year":2024},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.004718Z"},"links":{"citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:4eafec9bff768197423d52c5bfc285906b57923077c2db3be501738ffe9ad477","observation_id":"4f1a6689-3818-4310-a8fe-dfba347e1aea","resolution":{"observed_at":"2026-08-10T11:00:18.498550Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T11:00:18.980479Z","title":"A seismic- based co2-sequestration regional assessment of the miocene section, northern gulf of mexico, texas and louisiana,","venue":null,"work_id":"5a5da93e-af78-4b1b-9c69-f53284b86e11","year":2019},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.009311Z"},"links":{"citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:e54cca0892b8842dbbdf1ecc8e02a13495905ad7d39898691f2f56fc51fed4da","observation_id":"65d32c28-9c94-4dd9-ae0d-b05272b5aa58","resolution":{"observed_at":"2026-08-10T11:00:18.984688Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T11:00:18.969286Z","title":"A machine learning benchmark for facies classification,","venue":null,"work_id":"bc3e2641-c2ed-4a6b-a284-3fc8bf6588c0","year":2019},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.013642Z"},"links":{"citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:4e96d4fe495120857d043d00072586fd9573082454c27bb92eacc9433e07bffc","observation_id":"d88e2a74-7abc-4c6a-ac20-fb5eddc1529d","resolution":{"observed_at":"2026-08-10T11:00:18.973009Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T11:00:18.958343Z","title":"Deep learning for automated seismic facies classification,","venue":null,"work_id":"ce7a2226-f19c-460c-8236-d830d6121732","year":2022},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.017637Z"},"links":{"citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:b859ffe2512706dbe1c693ab40c8aefdfcc550e8993ac7d21367a7be6cff9455","observation_id":"27c88198-e483-495b-b221-2dff9007d3d4","resolution":{"observed_at":"2026-08-10T11:00:18.962132Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T11:00:18.947164Z","title":"Few-shot learning for semantic segmentation of seismic data,","venue":null,"work_id":"d76f6f90-b38b-45dc-8ae8-a4a669ddecd3","year":2021},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.022085Z"},"links":{"citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:9fb947cac575612061ccdc91c45dd13a26ecfb62ff52b922e90b2fbcdba8925f","observation_id":"c4dca481-ce33-44bd-8f60-f3a0d7372274","resolution":{"observed_at":"2026-08-10T11:00:18.951028Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T11:00:18.936024Z","title":"Riding the wave: One-touch automatic salt segmentation by coupling sam and seggpt,","venue":null,"work_id":"7132a643-3222-4c6f-bc9c-473f7085e971","year":2023},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.026324Z"},"links":{"citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:4f4e0945361059c113c957719c22d9677546f0c80d213128044eeb66dbee01b4","observation_id":"13dffb9d-6df7-4bd1-894c-e393c946d297","resolution":{"observed_at":"2026-08-10T11:00:18.939938Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T11:00:18.924085Z","title":"Improving seismic interpretation accuracy and efficiency with human- machine collaboration,","venue":null,"work_id":"795e6e5d-1aaf-449f-9bcc-46d847f7c08a","year":2024},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.030477Z"},"links":{"citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:2032d090e0a9e96c2c24bb777255a1a01583703ad64ceda79b8b0984493dab12","observation_id":"ab8f79b0-33c2-47f9-b74d-1ff67c841cb4","resolution":{"observed_at":"2026-08-10T11:00:18.928643Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T11:00:18.911705Z","title":"Self-supervised learning for efficient seismic facies classification,","venue":null,"work_id":"b4b06286-43eb-469b-a372-16ba26807a41","year":2024},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.034066Z"},"links":{"citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:8656809528612323cef76c8440b2bad1769f067a314f065e23f5038b98fea43a","observation_id":"defea69f-f7e6-49b3-9ecd-bf2c22d41ce2","resolution":{"observed_at":"2026-08-10T11:00:18.916075Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T11:00:18.899741Z","title":"Visualizing and understanding convolu- tional networks,","venue":null,"work_id":"58adf9d9-f5f7-4fa7-96f3-9956d0bfd40b","year":2014},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.037853Z"},"links":{"citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:cc049b4058478733c4167800088c865d8784820388a501163ae8058a2292fa13","observation_id":"1885237f-de3c-4371-be8c-361e5636855f","resolution":{"observed_at":"2026-08-10T11:00:18.903742Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T11:00:18.887691Z","title":"Cnn features off-the-shelf: an astounding baseline for recognition,","venue":null,"work_id":"12eb8f9b-e6d8-48fa-acc2-0aa52b5f2eda","year":2014},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.041500Z"},"links":{"citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:a3b6006033e1c94978f980c4343b7e6687c3580683449a16c4864277cc0461af","observation_id":"baf0555b-6c5a-44ae-a63a-5a3eafec55aa","resolution":{"observed_at":"2026-08-10T11:00:18.891770Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T11:00:18.875412Z","title":"Seg advanced modeling corporation ai project,","venue":null,"work_id":"bd7ee84b-85a8-42e0-879b-be017882cf25","year":2024},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.045269Z"},"links":{"citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:0405fc497be4aaa12c1d043d02c96323f6d253bfaee0a966d3f00aa4fabc23c6","observation_id":"2d11089a-3778-4813-a045-c2131193536b","resolution":{"observed_at":"2026-08-10T11:00:18.879475Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T11:00:18.863067Z","title":"Penobscot dataset: Fostering machine learning devel- opment for seismic interpretation,","venue":null,"work_id":"11dd0b68-60c6-4f53-8501-9bee89dc7536","year":2021},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.049210Z"},"links":{"citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:a74c448de6256315958ab775de099c32c64e35ba8215de21af7d9c177ccc6c30","observation_id":"8f078443-ebaf-4718-b793-fe33b5085fe5","resolution":{"observed_at":"2026-08-10T11:00:18.867343Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T11:00:18.851337Z","title":"Optimization as a model for few-shot learning,","venue":null,"work_id":"a8eca364-7007-4371-9e69-8eb4ac7b1504","year":2017},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.063884Z"},"links":{"citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:642231288bc6d34880a858cc5add8d388d45bc4337011bc876ae3670a835b7f8","observation_id":"717f18e9-1289-46ae-8765-dbb63340a55c","resolution":{"observed_at":"2026-08-10T11:00:18.855241Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T11:00:18.067401Z","title":"Prototypical networks for few- shot learning,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.067401Z"},"links":{"citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:dc3aecdd3b613efd9749545f1a240742055d62cb35801d55b566d74bf512b878","observation_id":"f8671f69-82dd-488f-8f2c-9853dc1aae9d","resolution":{"observed_at":"2026-08-10T11:00:18.067401Z","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":"2026-08-10T11:00:18.833378Z","title":"Model-agnostic meta-learning for fast adaptation of deep networks,","venue":null,"work_id":"1e18bf7e-8569-419a-981e-3edf735e6ae5","year":2017},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.070937Z"},"links":{"citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:910589f05e3ffe901a1f285d7af35ed1f42aa9ff18e1e6a11017f25352c5b604","observation_id":"3e18c2a9-d740-43e8-baa8-80c2cc5afec4","resolution":{"observed_at":"2026-08-10T11:00:18.837379Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T11:00:18.822685Z","title":"Prototype queue learning for multi- class few-shot semantic segmentation,","venue":null,"work_id":"ef88daef-b2d4-4ac5-9276-10ec3388fdaf","year":2022},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.074459Z"},"links":{"citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:924b8cf1c2087696c0d8fbefd4d2ef7c3fcb223458af9ecad9ae579ec3cd4829","observation_id":"66a4e4b5-313d-4832-b77c-6d826a106a30","resolution":{"observed_at":"2026-08-10T11:00:18.826591Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T11:00:18.811489Z","title":"Incrementer: Transformer for class-incremental semantic segmentation with knowl- edge distillation focusing on old class,","venue":null,"work_id":"7d05a0d4-ece9-43dd-a9a6-56864bbc4023","year":2023},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.078317Z"},"links":{"citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:7d56b60fc3e71acb8f028927740c3829331d39feb9736253cd5cc830b0ed650a","observation_id":"590d5cae-0fe9-4eca-8600-e0332a068bf7","resolution":{"observed_at":"2026-08-10T11:00:18.815459Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T11:00:18.800537Z","title":"One-shot learning for semantic segmentation,","venue":null,"work_id":"2f96aa4b-31c2-45b5-bfca-8f78a0f381a7","year":2017},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.082104Z"},"links":{"citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:0e9e3280c3d7c9fcb10088fb67bd2cbfe350c5676c205f96bd0db5b7b92c8ce2","observation_id":"746c842c-3012-4db4-acf2-4a757f046310","resolution":{"observed_at":"2026-08-10T11:00:18.804413Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T11:00:18.789271Z","title":"Dense gaussian processes for few-shot segmentation,","venue":null,"work_id":"4ccfa3ea-c607-42e5-ba31-0cf26db524f5","year":2022},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.085825Z"},"links":{"citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:702c1fefeb25937bf1dd7ba8c1afa90d9233409dec07ae11df2d87c246b787c8","observation_id":"1033603f-4e4f-48c9-b5dd-4446bc68dc03","resolution":{"observed_at":"2026-08-10T11:00:18.793054Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T11:00:18.778380Z","title":"Mseg: A composite dataset for multi-domain semantic segmentation,","venue":null,"work_id":"00579108-42ec-49b1-9f9c-d72a0f3d1de2","year":2020},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.089433Z"},"links":{"citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:a99d17b2728754566567ee0856c454ed18862e73ba4a0a01c0ffa70af07a6b88","observation_id":"35a6215f-16f9-47ef-b518-e17c5e4174f4","resolution":{"observed_at":"2026-08-10T11:00:18.782086Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T11:00:18.767201Z","title":"Lmseg: Language- guided multi-dataset segmentation,","venue":null,"work_id":"a3a51b25-7ea8-4633-85d1-e68f1def2808","year":2023},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.092971Z"},"links":{"citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:2dae02374ee98f52559c3246900ac27e936fb1835b440a0f71ff4d520c5602a0","observation_id":"dd1000ac-5646-4dc6-8d51-6a33d325e028","resolution":{"observed_at":"2026-08-10T11:00:18.770977Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T11:00:18.756097Z","title":"Dataseg: Taming a universal multi-dataset multi-task segmentation model,","venue":null,"work_id":"65b4842e-9883-45e9-a62b-741c8fb39c91","year":2023},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.096503Z"},"links":{"citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:4b352ebc356de64796cb797335bd56dc8cce4cd3613ed55561c953ed938388f7","observation_id":"05a7f972-5022-46f8-97d3-82c8cedb7999","resolution":{"observed_at":"2026-08-10T11:00:18.760059Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T11:00:18.744499Z","title":"Few- shot learning for seismic facies segmentation via prototype learning,","venue":null,"work_id":"768d2bb7-4d4e-4cc6-9d66-1ec125b6045e","year":2023},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.099923Z"},"links":{"citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:eb0e1fbbb5d260c57a52e1ca34ca45b5653d10a212f48bde5b6677d12e299aec","observation_id":"f751acf8-dae7-47f1-abb7-38e699bc2865","resolution":{"observed_at":"2026-08-10T11:00:18.748560Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T11:00:18.732347Z","title":"Seismic fault detection in real data using transfer learning from a convolutional neural network pre-trained with synthetic seismic data,","venue":null,"work_id":"bc381646-e0c7-4ebb-858b-431d78ae6241","year":2020},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.103329Z"},"links":{"citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:31bea1b050b3f578a9f4727aa98ef981b30936b257716318b6f327a832ea6410","observation_id":"b3c3a8c8-3ddd-404c-bc74-f84d970e39b9","resolution":{"observed_at":"2026-08-10T11:00:18.736761Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T11:00:18.719213Z","title":"Multitask training as regularization strategy for seismic image segmentation,","venue":null,"work_id":"2ef2889c-bd55-4095-84e6-a687e3bfa13c","year":2023},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.107401Z"},"links":{"citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:21ed5a10621f5c75828a824d6f5399695f38c4e73b7c72f6e5ac793f58399ccf","observation_id":"49c855f2-0783-489c-942e-d5f9961e940a","resolution":{"observed_at":"2026-08-10T11:00:18.724164Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T11:00:18.706852Z","title":"An open-source package for deep-learning-based seismic facies classifica- tion: Benchmarking experiments on the seg 2020 open data,","venue":null,"work_id":"59d7474a-c0b6-40e0-9bef-880b921ff2af","year":2020},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.111406Z"},"links":{"citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:246c4b08e5809a243f7c2ba134028963b3045aafcbca4c8ca15c0736094d3c5c","observation_id":"33ed6eed-120a-4914-a0a7-6f428d180dc7","resolution":{"observed_at":"2026-08-10T11:00:18.711166Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T11:00:18.695074Z","title":"A deep learning framework for seismic facies classification,","venue":null,"work_id":"6a735d18-fedb-40c7-9e86-5383e83afe9d","year":2023},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.115326Z"},"links":{"citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:fd6d638b6b5e6b1d0c0d89c12380a4b02589cdf97ee5cb4ffd0d28ee883d5a71","observation_id":"d6a1ca06-9dda-400e-adfd-82290fb58d46","resolution":{"observed_at":"2026-08-10T11:00:18.699265Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T11:00:18.683955Z","title":"Semantic segmentation of seismic images,","venue":null,"work_id":"76bbc6c0-c171-4d3a-9844-2f9f09fab4de","year":2018},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.119275Z"},"links":{"citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:f5e31636a87082a2a0b119d6d9879bcf536a6e04f00021879caa3a130cf4726e","observation_id":"9abaad37-801c-4f20-bfc1-a81fc0c6c624","resolution":{"observed_at":"2026-08-10T11:00:18.687736Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T11:00:18.672186Z","title":"Self-supervised learning for seismic image segmentation from few-labeled samples,","venue":null,"work_id":"b484e8dd-2a85-49b8-b007-df957d7562e3","year":2022},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.123282Z"},"links":{"citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:3f07be68a56b9b980d09a76b9d877f3454d74f3fd5597e349bc6b5c93a92207b","observation_id":"065492ab-cd8e-41d8-9031-d6599a9f6985","resolution":{"observed_at":"2026-08-10T11:00:18.676085Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T11:00:18.127279Z","title":"Segment anything,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.127279Z"},"links":{"citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:7891cf544b1725e90369c417bbcc611c113d8e3fe4b40556e4ac7fbe3803f80f","observation_id":"d431fd7c-eced-471c-9101-5f53ba05553e","resolution":{"observed_at":"2026-08-10T11:00:18.127279Z","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":"2026-08-10T11:00:18.653986Z","title":"On the texture bias for few-shot cnn segmentation,","venue":null,"work_id":"c82669a5-4e1b-48e5-93d6-8d14306fdc63","year":2021},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.131238Z"},"links":{"citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:bc6283a2696d30acf035ba73ec6ca9e2ca5ea7a656512fb4bfb73f0321dc8d61","observation_id":"f7c0204d-1e5c-44fb-b5b5-9baaf39b3474","resolution":{"observed_at":"2026-08-10T11:00:18.658162Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T11:00:18.641001Z","title":"ImageNet: A Large-Scale Hierarchical Image Database,","venue":null,"work_id":"b74b9218-1175-4471-b9e7-6517ea9b15d0","year":2009},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.135326Z"},"links":{"citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:21b1daff62918aeb5142638806e16041688cbbcdad57af7888ca7dcf46b775b2","observation_id":"0cefeb56-60a0-4a56-a91d-ec85f1b90f4b","resolution":{"observed_at":"2026-08-10T11:00:18.645411Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1608.08614","last_updated":"2016-12-10T13:37:06Z","snapshot_observed_at":"2026-08-10T10:23:24.034021Z","submitted_at":"2016-08-30T19:45:09Z","title":"What makes ImageNet good for transfer learning?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1608.08614","snapshot_observed_at":"2026-08-10T11:00:18.139590Z","title":"What makes imagenet good for transfer learning?","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.139590Z"},"links":{"cited_paper":"/paper/1608.08614","citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:0e7a450c859edcd856802489e7aa32511d9a7c3b20908c3fb5ca72ab7fe919dc","observation_id":"b76a7db3-599a-4e44-9539-3fd227b660b6","resolution":{"observed_at":"2026-08-10T11:00:18.139590Z","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":"2026-08-10T11:00:18.629424Z","title":"A simple framework for contrastive learning of visual representations,","venue":null,"work_id":"2c9318f1-f953-4013-837e-0cb8f010a299","year":2020},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.143925Z"},"links":{"citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:6c688b4402c43ef006176662a822cb98128f2bb953b834c77a085d7e7834b6bb","observation_id":"535e3877-d47c-42c0-ba9b-d11c7a689ecd","resolution":{"observed_at":"2026-08-10T11:00:18.633317Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T11:00:18.147790Z","title":null,"venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.147790Z"},"links":{"citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:7aafd366028876eec2c159120a19afe07f27aa342382c2b7bed42ce2fe754b48","observation_id":"00d03dbc-3394-4a73-894b-dcccadc7ff7d","resolution":{"observed_at":"2026-08-10T11:00:18.147790Z","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":"2026-08-10T11:00:18.151723Z","title":"Deep residual learning for image recognition,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.151723Z"},"links":{"citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:976ac17e9316c121fa837af68819edddcbcb827605fecc12ca1f325b31fc693c","observation_id":"a6f508f7-4def-4747-8073-5f66f4e3aaa0","resolution":{"observed_at":"2026-08-10T11:00:18.151723Z","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":"2026-08-10T11:00:18.603619Z","title":"Learning a discriminative feature network for semantic segmentation,","venue":null,"work_id":"150ffc13-ca28-4b42-93b4-8ee4bcc4f232","year":2018},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.155589Z"},"links":{"citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:1ee226b933229078e8148eecab964fa766633ff884b65a58ddf27d65680760f7","observation_id":"82c758a9-c2b2-4203-b246-0a9a8870f6af","resolution":{"observed_at":"2026-08-10T11:00:18.607408Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T11:00:18.591619Z","title":"Improving seismic fault recognition with self-supervised pre-training: A study of 3d transformer-based with multi-scale decoding and fusion,","venue":null,"work_id":"f5a35404-4b41-4db3-9d3c-b471625702ea","year":2024},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.159199Z"},"links":{"citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:df478c7e1915b8037d67218906395b03a482a7a503b51cc70350ee2c8cf15b86","observation_id":"31f589c8-541f-4fe9-908a-4bf3fa56e4bc","resolution":{"observed_at":"2026-08-10T11:00:18.595996Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T11:00:18.580036Z","title":"Salt3dnet: A self-supervised learning framework for 3-d salt segmen- tation,","venue":null,"work_id":"2991f980-e4f3-40a4-b814-48ca3c548ee8","year":2024},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.162875Z"},"links":{"citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:467adb254f09a97f4956b69ca0fbcd8acd6ff38356cec1f840223e6f679c177a","observation_id":"8eafd700-ecd3-420f-b679-b85bb59c4cd1","resolution":{"observed_at":"2026-08-10T11:00:18.584000Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T11:00:18.567333Z","title":"Barlow twins: Self- supervised learning via redundancy reduction,","venue":null,"work_id":"7dddfc60-02a8-405c-a2ab-8f9296887f4d","year":2021},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.166555Z"},"links":{"citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:7906b1c9ffa52633cb6025f297bd27e63fe20af7a3336ec4991f80add9f226d4","observation_id":"9853fca6-a341-4159-a18e-a6ffac69047b","resolution":{"observed_at":"2026-08-10T11:00:18.572380Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T11:00:18.555853Z","title":"Auto-encoding variational bayes,","venue":null,"work_id":"3ad1bd7a-2e47-433f-a0db-09e57daefc47","year":2014},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.170878Z"},"links":{"citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:5c3a11530e775be6433e47bbc2cb8223151db86caec593dfdfc32cb60574be0c","observation_id":"c8d9a465-cb0d-4fbe-9c6f-b534d2e1a175","resolution":{"observed_at":"2026-08-10T11:00:18.559688Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T11:00:18.544205Z","title":"Gens: generative encoding networks,","venue":null,"work_id":"1c955b4c-fcac-4079-9ab9-78722ad64c71","year":2022},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.174634Z"},"links":{"citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:eb654c505610d0025813d9ce6aa02c96875ad754127c89e4a82d279d9cac9155","observation_id":"692fbd5e-9931-40a2-8eb8-c5cbe2786fd3","resolution":{"observed_at":"2026-08-10T11:00:18.548096Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T11:00:18.532162Z","title":"Matching aggregate posteriors in the variational autoencoder,","venue":null,"work_id":"f591c79b-ffa6-49dc-8e5f-c73203231272","year":2024},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.178365Z"},"links":{"citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:f3d12cffe582fc16e24df6ee28f4abe6676ea497526c48156fd4bc1e0dd4fa38","observation_id":"3412f9c9-3757-4424-8bc0-18e55e302dc6","resolution":{"observed_at":"2026-08-10T11:00:18.536120Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2501.10901","last_updated":"2025-01-26T23:39:11Z","snapshot_observed_at":"2026-08-10T18:48:58.575982Z","submitted_at":"2025-01-18T23:27:05Z","title":"ARD-VAE: A Statistical Formulation to Find the Relevant Latent Dimensions of Variational Autoencoders","version":2},"cited_work":{"arxiv_id":"2501.10901","doi":null,"metadata_source":"pith","pith_arxiv_id":"2501.10901","snapshot_observed_at":"2026-08-10T11:00:18.242744Z","title":"ARD-VAE: A Statistical Formulation to Find the Relevant Latent Dimensions of Variational Autoencoders","venue":"cs.LG","work_id":"a9da85fd-e90e-482b-b76d-fe7ec699df81","year":2025},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.181745Z"},"links":{"cited_paper":"/paper/2501.10901","citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:decedfd2643008640566dcd176e13974e0b8242ca49004100c00a95248f8193b","observation_id":"175e0f3e-0bb7-4ffe-b572-632bcf49be20","resolution":{"observed_at":"2026-08-10T11:00:18.247278Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2501.15705","last_updated":"2025-01-26T23:38:39Z","snapshot_observed_at":"2026-08-10T14:00:00.018720Z","submitted_at":"2025-01-26T23:38:39Z","title":"Disentanglement Analysis in Deep Latent Variable Models Matching Aggregate Posterior Distributions","version":1},"cited_work":{"arxiv_id":"2501.15705","doi":null,"metadata_source":"pith","pith_arxiv_id":"2501.15705","snapshot_observed_at":"2026-08-10T11:00:18.224003Z","title":"Disentanglement Analysis in Deep Latent Variable Models Matching Aggregate Posterior Distributions","venue":"cs.LG","work_id":"34e0b798-7cec-4e79-897e-5c47934c6251","year":2025},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.185759Z"},"links":{"cited_paper":"/paper/2501.15705","citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:3124394a72b9cf88bb6307f97ee28297055372f9bff6177ee805f7a2bd237414","observation_id":"c8e24836-669d-4c10-b84b-a7c77ca75abf","resolution":{"observed_at":"2026-08-10T11:00:18.230747Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T11:00:18.520241Z","title":"U-net: Convolutional networks for biomedical image segmentation,","venue":null,"work_id":"5c5f3227-90d5-41f3-a329-0649acd8e244","year":2015},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.189504Z"},"links":{"citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:e50aba135011fe5edc36a64c2cc2e43834ac353fcc8656a4fd87a2180c154c86","observation_id":"4d32a335-4363-4cc4-918a-41509a34c2d5","resolution":{"observed_at":"2026-08-10T11:00:18.524199Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T11:00:18.506541Z","title":"Transfer learning applied to seismic images classification,","venue":null,"work_id":"7f256dd5-87f7-4af8-8f71-739f1a190c22","year":2018},"citing_paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-10T11:00:18.192857Z"},"links":{"citing_paper":"/paper/2501.16760"},"observation_digest":"sha256:3fa354bac2dbc8dfd1c102e0885edc654b6cd11cca8b4224aa9d282ca2a9b513","observation_id":"6a3df911-8657-41ee-99ab-4c8fd03d61c4","resolution":{"observed_at":"2026-08-10T11:00:18.512206Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2501.16760","last_updated":"2025-01-28T07:31:09Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-11T17:26:53.873265Z","submitted_at":"2025-01-28T07:31:09Z","title":"AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies"},"reference_resolution":{"displayed":47,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":5,"verified_exact":3,"verified_fuzzy":39},"total_outbound_references":47},"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":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"thesis":"As of 11 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2501.16760."}