{"as_of":"2026-08-13T20:47:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f4c5576bf0a7e50a43d2ab72061f83336c92f64f97a14155dd543a59bf6696a8","coverage":[{"denominator":32,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":32,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-19T19:35:51.992891Z","state":"measured"},{"denominator":32,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":32,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-13T06:32:02.005865+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/2605.15695/citation-record","integrity":"/paper/2605.15695/integrity","json":"/paper/2605.15695/citation-record.json","paper":"/paper/2605.15695"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"In: (IPDPS)","venue":null,"work_id":"a8461479-56bf-4291-890a-ad2880deca74","year":2016},"citing_paper":{"arxiv_id":"2605.15695","last_updated":"2026-05-15T07:38:04Z","snapshot_observed_at":"2026-07-06T23:26:56.013191Z","submitted_at":"2026-05-15T07:38:04Z","title":"ParamSpMM: Adaptive and Efficient Sparse Matrix-Matrix Multiplication on GPUs for GNNs","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-19T19:35:51.992891Z"},"links":{"citing_paper":"/paper/2605.15695"},"observation_digest":"sha256:23d2daedeb8704c33703ff284b0f3b18fa13fb7cc7007c34364c7ee469e8852f","observation_id":"18629f3b-2356-4024-98c3-87a5a6dacd8e","resolution":{"observed_at":"2026-05-19T19:37:44.202599Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"8d88f590-5041-4ca3-a655-03354b5de463","year":2011},"citing_paper":{"arxiv_id":"2605.15695","last_updated":"2026-05-15T07:38:04Z","snapshot_observed_at":"2026-07-06T23:26:56.013191Z","submitted_at":"2026-05-15T07:38:04Z","title":"ParamSpMM: Adaptive and Efficient Sparse Matrix-Matrix Multiplication on GPUs for GNNs","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-19T19:35:51.992891Z"},"links":{"citing_paper":"/paper/2605.15695"},"observation_digest":"sha256:5efeb5592070f4fd372d57914222295f92a7fa2da327b286e4400cb0002371fd","observation_id":"a6365a8c-6b1f-49a5-a7e0-ffeee1ba289d","resolution":{"observed_at":"2026-05-19T19:37:44.200749Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-06-05T21:23:00.469572Z","title":"Waschington University in St","venue":null,"work_id":"a8c415f1-dac3-4b00-96b1-bbfed3ba3b6b","year":2009},"citing_paper":{"arxiv_id":"2605.15695","last_updated":"2026-05-15T07:38:04Z","snapshot_observed_at":"2026-07-06T23:26:56.013191Z","submitted_at":"2026-05-15T07:38:04Z","title":"ParamSpMM: Adaptive and Efficient Sparse Matrix-Matrix Multiplication on GPUs for GNNs","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-19T19:35:51.992891Z"},"links":{"citing_paper":"/paper/2605.15695"},"observation_digest":"sha256:b78b439c3722ac89471a1fe7169e3f2fe09f68246720792819b802a0af98f90b","observation_id":"0922b852-42d4-4c70-ae29-896262b8c98b","resolution":{"observed_at":"2026-05-19T19:37:44.197121Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"fe2bd51e-5ac6-4c29-9fdc-79800ea0f10e","year":2022},"citing_paper":{"arxiv_id":"2605.15695","last_updated":"2026-05-15T07:38:04Z","snapshot_observed_at":"2026-07-06T23:26:56.013191Z","submitted_at":"2026-05-15T07:38:04Z","title":"ParamSpMM: Adaptive and Efficient Sparse Matrix-Matrix Multiplication on GPUs for GNNs","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-19T19:35:51.992891Z"},"links":{"citing_paper":"/paper/2605.15695"},"observation_digest":"sha256:71e74b7223ce6824d54ee69e99a8d59958119ac492d325180bbad6c559e2346f","observation_id":"e1c15043-c695-4a44-824d-46aea478a0d3","resolution":{"observed_at":"2026-05-19T19:37:44.195247Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-06-05T21:23:00.469572Z","title":"In: (IPDPS)","venue":null,"work_id":"5b6017c0-6221-409d-984a-750aa5c96c8c","year":2023},"citing_paper":{"arxiv_id":"2605.15695","last_updated":"2026-05-15T07:38:04Z","snapshot_observed_at":"2026-07-06T23:26:56.013191Z","submitted_at":"2026-05-15T07:38:04Z","title":"ParamSpMM: Adaptive and Efficient Sparse Matrix-Matrix Multiplication on GPUs for GNNs","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-19T19:35:51.992891Z"},"links":{"citing_paper":"/paper/2605.15695"},"observation_digest":"sha256:f996acdb38eb5fe31d6543ff54da1346d772a807785dbc46ca6209372ad4b500","observation_id":"7ea7348e-e338-4eca-8df6-92747b1c4f28","resolution":{"observed_at":"2026-05-19T19:37:44.193479Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"51c7d063-fdaf-49af-a70b-bf75c22f1a6d","year":2019},"citing_paper":{"arxiv_id":"2605.15695","last_updated":"2026-05-15T07:38:04Z","snapshot_observed_at":"2026-07-06T23:26:56.013191Z","submitted_at":"2026-05-15T07:38:04Z","title":"ParamSpMM: Adaptive and Efficient Sparse Matrix-Matrix Multiplication on GPUs for GNNs","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-19T19:35:51.992891Z"},"links":{"citing_paper":"/paper/2605.15695"},"observation_digest":"sha256:e87c37e0ce7e6c45595bcc90e25cae7d45984ed5109f803ab315084c73aa6671","observation_id":"a4e4194f-6b71-47d5-a353-9a1de39369df","resolution":{"observed_at":"2026-05-19T19:37:44.182856Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-06-05T21:23:00.469572Z","title":"Physics Reports486(3–5), 75–174 (Feb 2010)","venue":null,"work_id":"60ea10bf-bd12-48c7-867d-24b867ad2b66","year":2010},"citing_paper":{"arxiv_id":"2605.15695","last_updated":"2026-05-15T07:38:04Z","snapshot_observed_at":"2026-07-06T23:26:56.013191Z","submitted_at":"2026-05-15T07:38:04Z","title":"ParamSpMM: Adaptive and Efficient Sparse Matrix-Matrix Multiplication on GPUs for GNNs","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-19T19:35:51.992891Z"},"links":{"citing_paper":"/paper/2605.15695"},"observation_digest":"sha256:0e46e98b65122c915df403310877c132a2adbf98975ac151e898a2d21a3ef95e","observation_id":"36a880fc-a988-4979-8efe-b372e950a81e","resolution":{"observed_at":"2026-05-19T19:37:44.146108Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"24706778-c67a-426a-9371-5b61c37f49d3","year":2017},"citing_paper":{"arxiv_id":"2605.15695","last_updated":"2026-05-15T07:38:04Z","snapshot_observed_at":"2026-07-06T23:26:56.013191Z","submitted_at":"2026-05-15T07:38:04Z","title":"ParamSpMM: Adaptive and Efficient Sparse Matrix-Matrix Multiplication on GPUs for GNNs","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-19T19:35:51.992891Z"},"links":{"citing_paper":"/paper/2605.15695"},"observation_digest":"sha256:137660f2171658041956c2fc2ed545590c082ba967fd1e9d605d5afd790de719","observation_id":"0e91705f-1a29-4a02-aec3-3c163116c89f","resolution":{"observed_at":"2026-05-19T19:37:44.144264Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-06-05T21:23:00.469572Z","title":"AAAI’19/IAAI’19/EAAI’19 (2019)","venue":null,"work_id":"4194a677-642f-40b5-afd8-09c414d50e30","year":2019},"citing_paper":{"arxiv_id":"2605.15695","last_updated":"2026-05-15T07:38:04Z","snapshot_observed_at":"2026-07-06T23:26:56.013191Z","submitted_at":"2026-05-15T07:38:04Z","title":"ParamSpMM: Adaptive and Efficient Sparse Matrix-Matrix Multiplication on GPUs for GNNs","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-19T19:35:51.992891Z"},"links":{"citing_paper":"/paper/2605.15695"},"observation_digest":"sha256:35a81400e380008978005e1ab784f94258bae038edc27ca409d98586fb0d5bc8","observation_id":"e0605598-d3e6-4ff5-ba0a-312b3a47f15b","resolution":{"observed_at":"2026-05-19T19:37:44.142549Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"e03c288e-8783-4ae5-96ce-8d750b3b7561","year":2021},"citing_paper":{"arxiv_id":"2605.15695","last_updated":"2026-05-15T07:38:04Z","snapshot_observed_at":"2026-07-06T23:26:56.013191Z","submitted_at":"2026-05-15T07:38:04Z","title":"ParamSpMM: Adaptive and Efficient Sparse Matrix-Matrix Multiplication on GPUs for GNNs","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-19T19:35:51.992891Z"},"links":{"citing_paper":"/paper/2605.15695"},"observation_digest":"sha256:fe6678a1b2f8975a405f7dc7cb7fc9f1c0896f3f34a88f0da602b8b22f4cf5a4","observation_id":"0c896a2e-e96c-461f-a63a-c5360e940722","resolution":{"observed_at":"2026-05-19T19:37:44.140881Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"fdf77114-ba16-40ab-b042-4d4410040458","year":2019},"citing_paper":{"arxiv_id":"2605.15695","last_updated":"2026-05-15T07:38:04Z","snapshot_observed_at":"2026-07-06T23:26:56.013191Z","submitted_at":"2026-05-15T07:38:04Z","title":"ParamSpMM: Adaptive and Efficient Sparse Matrix-Matrix Multiplication on GPUs for GNNs","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-19T19:35:51.992891Z"},"links":{"citing_paper":"/paper/2605.15695"},"observation_digest":"sha256:368a6591a98352463454afb3bb4d31446b2b4bc94740e76a363ffc968b65f3e7","observation_id":"65bf3b79-e278-482e-8242-8972afd4bb26","resolution":{"observed_at":"2026-05-19T19:37:44.135139Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-06-05T21:23:00.469572Z","title":"Advances in neural information processing systems33, 22118–22133 (2020)","venue":null,"work_id":"b54efd26-904d-40b9-bda6-9023d5f76dc5","year":2020},"citing_paper":{"arxiv_id":"2605.15695","last_updated":"2026-05-15T07:38:04Z","snapshot_observed_at":"2026-07-06T23:26:56.013191Z","submitted_at":"2026-05-15T07:38:04Z","title":"ParamSpMM: Adaptive and Efficient Sparse Matrix-Matrix Multiplication on GPUs for GNNs","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-19T19:35:51.992891Z"},"links":{"citing_paper":"/paper/2605.15695"},"observation_digest":"sha256:b4ac582fd7d166c4c950cf0dc1c1836c7918a3a92590951bdfba9c94941ac015","observation_id":"87064c4f-ec99-4565-bf2d-5981a46b37a3","resolution":{"observed_at":"2026-05-19T19:37:44.139131Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-06-05T21:23:00.469572Z","title":"In: SC20","venue":null,"work_id":"ca7c3f7d-8ae5-4fc4-afc4-d6de3f4b6dfe","year":2020},"citing_paper":{"arxiv_id":"2605.15695","last_updated":"2026-05-15T07:38:04Z","snapshot_observed_at":"2026-07-06T23:26:56.013191Z","submitted_at":"2026-05-15T07:38:04Z","title":"ParamSpMM: Adaptive and Efficient Sparse Matrix-Matrix Multiplication on GPUs for GNNs","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-19T19:35:51.992891Z"},"links":{"citing_paper":"/paper/2605.15695"},"observation_digest":"sha256:3804ec57b3d9445b58a323d657246b9138a4068a79ca6026d8599efb56e47660","observation_id":"6cba68b4-ddca-4cc8-a576-470ff24de846","resolution":{"observed_at":"2026-05-19T19:37:44.136936Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"094b06bd-e885-4973-933b-3aac535633c9","year":2021},"citing_paper":{"arxiv_id":"2605.15695","last_updated":"2026-05-15T07:38:04Z","snapshot_observed_at":"2026-07-06T23:26:56.013191Z","submitted_at":"2026-05-15T07:38:04Z","title":"ParamSpMM: Adaptive and Efficient Sparse Matrix-Matrix Multiplication on GPUs for GNNs","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-19T19:35:51.992891Z"},"links":{"citing_paper":"/paper/2605.15695"},"observation_digest":"sha256:82c97601b45c68348012088249282ff2dec74ddc56dbd2f1ea9c29146ed9c228","observation_id":"35d9ab1a-da55-4198-831b-d061134e559b","resolution":{"observed_at":"2026-05-19T19:37:44.115616Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"b3207e33-bd06-4510-b76e-676e079d1239","year":2017},"citing_paper":{"arxiv_id":"2605.15695","last_updated":"2026-05-15T07:38:04Z","snapshot_observed_at":"2026-07-06T23:26:56.013191Z","submitted_at":"2026-05-15T07:38:04Z","title":"ParamSpMM: Adaptive and Efficient Sparse Matrix-Matrix Multiplication on GPUs for GNNs","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-19T19:35:51.992891Z"},"links":{"citing_paper":"/paper/2605.15695"},"observation_digest":"sha256:cf436a9895c71ac0c469645488cedfe21539ae926df75d3372d2e1f8da40bf61","observation_id":"2c9e21bd-bfa1-470c-8f87-317a27588637","resolution":{"observed_at":"2026-05-19T19:37:44.117352Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"51287dd9-7e2c-443e-a1f8-aeb0c7b1afb9","year":2014},"citing_paper":{"arxiv_id":"2605.15695","last_updated":"2026-05-15T07:38:04Z","snapshot_observed_at":"2026-07-06T23:26:56.013191Z","submitted_at":"2026-05-15T07:38:04Z","title":"ParamSpMM: Adaptive and Efficient Sparse Matrix-Matrix Multiplication on GPUs for GNNs","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-19T19:35:51.992891Z"},"links":{"citing_paper":"/paper/2605.15695"},"observation_digest":"sha256:5f562fc39216621102bb3ea7d8ac9588c034e0af878cb86ce1b9bd2427fe417a","observation_id":"11e82f3f-18ee-4581-9f2c-fe746fe60c00","resolution":{"observed_at":"2026-05-19T19:37:44.133384Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-06-05T21:23:00.469572Z","title":"Nature Biomedical Engineering6(12), 1353–1369 (2022)","venue":null,"work_id":"5672a88c-b3d1-45b0-82a9-bf2001cd8bd3","year":2022},"citing_paper":{"arxiv_id":"2605.15695","last_updated":"2026-05-15T07:38:04Z","snapshot_observed_at":"2026-07-06T23:26:56.013191Z","submitted_at":"2026-05-15T07:38:04Z","title":"ParamSpMM: Adaptive and Efficient Sparse Matrix-Matrix Multiplication on GPUs for GNNs","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-19T19:35:51.992891Z"},"links":{"citing_paper":"/paper/2605.15695"},"observation_digest":"sha256:a369ea80ebd8a7eb766089947ff1bd44b90fe277301f96a6d8cf493b0b69a711","observation_id":"7f4a8bc1-06a7-4a36-b2f9-15e84e22d686","resolution":{"observed_at":"2026-05-19T19:37:44.129946Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-06-05T21:23:00.469572Z","title":"SC ’22 (2022)","venue":null,"work_id":"ce6813d0-a3c1-4408-a85c-f30c87074cc1","year":2022},"citing_paper":{"arxiv_id":"2605.15695","last_updated":"2026-05-15T07:38:04Z","snapshot_observed_at":"2026-07-06T23:26:56.013191Z","submitted_at":"2026-05-15T07:38:04Z","title":"ParamSpMM: Adaptive and Efficient Sparse Matrix-Matrix Multiplication on GPUs for GNNs","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-19T19:35:51.992891Z"},"links":{"citing_paper":"/paper/2605.15695"},"observation_digest":"sha256:48e133a5877b8ace0aaccbdeb52336fab6f16d663cbdcaf903bddf16704d7ed4","observation_id":"b87b04a7-8730-4e7f-bb3e-725e843ded2c","resolution":{"observed_at":"2026-05-19T19:37:44.198961Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-06-05T21:23:00.469572Z","title":"PPoPP ’16 (2016)","venue":null,"work_id":"65e43b10-afac-4db3-9cde-389a4fbed858","year":2016},"citing_paper":{"arxiv_id":"2605.15695","last_updated":"2026-05-15T07:38:04Z","snapshot_observed_at":"2026-07-06T23:26:56.013191Z","submitted_at":"2026-05-15T07:38:04Z","title":"ParamSpMM: Adaptive and Efficient Sparse Matrix-Matrix Multiplication on GPUs for GNNs","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-19T19:35:51.992891Z"},"links":{"citing_paper":"/paper/2605.15695"},"observation_digest":"sha256:7c410c8b5d2d1f3c7d8935c1f064756ec1e47f6e762c8e566a0c8e0e611fefe1","observation_id":"6044c024-e904-41f7-9170-7a1b060deef6","resolution":{"observed_at":"2026-05-19T19:37:44.131619Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-06-05T21:23:00.469572Z","title":"In: GPU Technology Conference (2010)","venue":null,"work_id":"9a224fa3-985f-4c7b-8c5f-9ff23a870587","year":2010},"citing_paper":{"arxiv_id":"2605.15695","last_updated":"2026-05-15T07:38:04Z","snapshot_observed_at":"2026-07-06T23:26:56.013191Z","submitted_at":"2026-05-15T07:38:04Z","title":"ParamSpMM: Adaptive and Efficient Sparse Matrix-Matrix Multiplication on GPUs for GNNs","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-19T19:35:51.992891Z"},"links":{"citing_paper":"/paper/2605.15695"},"observation_digest":"sha256:fc3f353d5a5b50385054e62aa18a821b54f8d0feb31d57b75a0a4eeaa4260f1d","observation_id":"a66e2ce2-c1a4-436c-ac5f-b754efd357a3","resolution":{"observed_at":"2026-05-19T19:37:44.128171Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"e5af73d5-b38f-484f-a2d5-3ad96a44997d","year":2010},"citing_paper":{"arxiv_id":"2605.15695","last_updated":"2026-05-15T07:38:04Z","snapshot_observed_at":"2026-07-06T23:26:56.013191Z","submitted_at":"2026-05-15T07:38:04Z","title":"ParamSpMM: Adaptive and Efficient Sparse Matrix-Matrix Multiplication on GPUs for GNNs","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-19T19:35:51.992891Z"},"links":{"citing_paper":"/paper/2605.15695"},"observation_digest":"sha256:e3e19828f91740a990c81cba360dc7f578d4a3ab437301b3a9c7053c40104b73","observation_id":"6a232030-a14c-4fda-be9a-daed53336143","resolution":{"observed_at":"2026-05-19T19:37:44.187429Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1145/3648358","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"ACM Comput","venue":"ACM Computing Surveys","work_id":"91df5956-7dc8-40de-b525-3fcf809a919e","year":2024},"citing_paper":{"arxiv_id":"2605.15695","last_updated":"2026-05-15T07:38:04Z","snapshot_observed_at":"2026-07-06T23:26:56.013191Z","submitted_at":"2026-05-15T07:38:04Z","title":"ParamSpMM: Adaptive and Efficient Sparse Matrix-Matrix Multiplication on GPUs for GNNs","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-19T19:35:51.992891Z"},"links":{"citing_paper":"/paper/2605.15695"},"observation_digest":"sha256:c1936a2079eca7f7ab3d3f63ec575465f44acc54fff81303a63bdadf9105d58a","observation_id":"1aedf4ea-4116-4895-b70f-1f25f5c646c8","resolution":{"observed_at":"2026-05-19T19:37:43.657127Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-05-24T09:53:19.865701+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-24T09:53:19.865701+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-06-05T21:23:00.469572Z","title":"In: SC ’08","venue":null,"work_id":"7a65bbc3-2074-48bf-b3f6-31ccb2d94cfd","year":2008},"citing_paper":{"arxiv_id":"2605.15695","last_updated":"2026-05-15T07:38:04Z","snapshot_observed_at":"2026-07-06T23:26:56.013191Z","submitted_at":"2026-05-15T07:38:04Z","title":"ParamSpMM: Adaptive and Efficient Sparse Matrix-Matrix Multiplication on GPUs for GNNs","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-19T19:35:51.992891Z"},"links":{"citing_paper":"/paper/2605.15695"},"observation_digest":"sha256:58739d77d1141e6ee19aa76eb4bfc45ba30c5a833e4882813413b581b2419316","observation_id":"113b8dce-01ff-47eb-b209-e1050a503998","resolution":{"observed_at":"2026-05-19T19:37:44.125942Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"f2fdf0ce-92ac-48ab-9b2f-f122f710cc53","year":2020},"citing_paper":{"arxiv_id":"2605.15695","last_updated":"2026-05-15T07:38:04Z","snapshot_observed_at":"2026-07-06T23:26:56.013191Z","submitted_at":"2026-05-15T07:38:04Z","title":"ParamSpMM: Adaptive and Efficient Sparse Matrix-Matrix Multiplication on GPUs for GNNs","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-05-19T19:35:51.992891Z"},"links":{"citing_paper":"/paper/2605.15695"},"observation_digest":"sha256:daa6dfd90a5396d21b9654473a811011393c88dc372ef9c7af37429e3c3357d5","observation_id":"033c03ac-1d7c-4773-9bf7-6f046b5beb3b","resolution":{"observed_at":"2026-05-19T19:37:44.124122Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-06-05T21:23:00.469572Z","title":"In: (OSDI 21)","venue":null,"work_id":"81a2d676-6659-4528-b450-533e6b38113a","year":2021},"citing_paper":{"arxiv_id":"2605.15695","last_updated":"2026-05-15T07:38:04Z","snapshot_observed_at":"2026-07-06T23:26:56.013191Z","submitted_at":"2026-05-15T07:38:04Z","title":"ParamSpMM: Adaptive and Efficient Sparse Matrix-Matrix Multiplication on GPUs for GNNs","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-19T19:35:51.992891Z"},"links":{"citing_paper":"/paper/2605.15695"},"observation_digest":"sha256:60486aeacca4bc83a82f3c73fb916c66634a9e59073951c7bbae17f568caa347","observation_id":"e075840f-53cd-4d70-a15c-8bf8a46e99a1","resolution":{"observed_at":"2026-05-19T19:37:44.152587Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"a0430ce5-3805-4928-b08d-4d2b9d37e162","year":2016},"citing_paper":{"arxiv_id":"2605.15695","last_updated":"2026-05-15T07:38:04Z","snapshot_observed_at":"2026-07-06T23:26:56.013191Z","submitted_at":"2026-05-15T07:38:04Z","title":"ParamSpMM: Adaptive and Efficient Sparse Matrix-Matrix Multiplication on GPUs for GNNs","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-05-19T19:35:51.992891Z"},"links":{"citing_paper":"/paper/2605.15695"},"observation_digest":"sha256:33d2a5df1a0941824240ddd5ab5ec519cd80b7521a9ae961e4c504771cd677d5","observation_id":"ed979a89-1a01-435c-bf01-e38ccb9735ee","resolution":{"observed_at":"2026-05-19T19:37:44.122386Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-06-05T21:23:00.469572Z","title":"ACM Comput","venue":null,"work_id":"2303029b-3385-4e42-b88d-913b475532a3","year":2022},"citing_paper":{"arxiv_id":"2605.15695","last_updated":"2026-05-15T07:38:04Z","snapshot_observed_at":"2026-07-06T23:26:56.013191Z","submitted_at":"2026-05-15T07:38:04Z","title":"ParamSpMM: Adaptive and Efficient Sparse Matrix-Matrix Multiplication on GPUs for GNNs","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-05-19T19:35:51.992891Z"},"links":{"citing_paper":"/paper/2605.15695"},"observation_digest":"sha256:e18bb5adfcc8d7a52c9b1a30174d5486aa5c949c0b56bbff112b4fd9dc519da1","observation_id":"803d1a19-18ac-4239-85dc-370d1bceaa62","resolution":{"observed_at":"2026-05-19T19:37:44.185554Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2309.10285","last_updated":"2023-09-19T03:20:02Z","snapshot_observed_at":"2026-08-13T10:10:20.721971Z","submitted_at":"2023-09-19T03:20:02Z","title":"Flash-LLM: Enabling Cost-Effective and Highly-Efficient Large Generative Model Inference with Unstructured Sparsity","version":1},"cited_work":{"arxiv_id":"2309.10285","doi":"10.48550/arxiv.2309.10285","metadata_source":"arxiv_reference","pith_arxiv_id":"2309.10285","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Flash-llm: Enabling cost-effective and highly-efficient large generative model inference with unstructured sparsity","venue":"arXiv (Cornell University)","work_id":"7dad54d7-b04e-46f6-a691-73a220bcd3d9","year":2023},"citing_paper":{"arxiv_id":"2605.15695","last_updated":"2026-05-15T07:38:04Z","snapshot_observed_at":"2026-07-06T23:26:56.013191Z","submitted_at":"2026-05-15T07:38:04Z","title":"ParamSpMM: Adaptive and Efficient Sparse Matrix-Matrix Multiplication on GPUs for GNNs","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-19T19:35:51.992891Z"},"links":{"cited_paper":"/paper/2309.10285","citing_paper":"/paper/2605.15695"},"observation_digest":"sha256:89850e07ec529394fc3164c5892b4da2f58722f8c6b94c03643f617efadd5dc4","observation_id":"c139bd58-344c-4240-af5e-218b7f1200cc","resolution":{"observed_at":"2026-05-19T19:37:43.766024Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"9c44ba0c-d83a-4a64-a251-473958c96a2e","year":2019},"citing_paper":{"arxiv_id":"2605.15695","last_updated":"2026-05-15T07:38:04Z","snapshot_observed_at":"2026-07-06T23:26:56.013191Z","submitted_at":"2026-05-15T07:38:04Z","title":"ParamSpMM: Adaptive and Efficient Sparse Matrix-Matrix Multiplication on GPUs for GNNs","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-05-19T19:35:51.992891Z"},"links":{"citing_paper":"/paper/2605.15695"},"observation_digest":"sha256:04508e632c47e13fed1b298153957928f6f22b48cd9962012db8a4d145214fa4","observation_id":"02910f9e-5e8c-4013-9158-a783f209bf35","resolution":{"observed_at":"2026-05-19T19:37:44.120698Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"bfe22bf3-7103-45c7-a0fa-eda029d9d91f","year":2018},"citing_paper":{"arxiv_id":"2605.15695","last_updated":"2026-05-15T07:38:04Z","snapshot_observed_at":"2026-07-06T23:26:56.013191Z","submitted_at":"2026-05-15T07:38:04Z","title":"ParamSpMM: Adaptive and Efficient Sparse Matrix-Matrix Multiplication on GPUs for GNNs","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-05-19T19:35:51.992891Z"},"links":{"citing_paper":"/paper/2605.15695"},"observation_digest":"sha256:121a02842ac402c1ba8d0cf0b17f7282f32a978748a65274fe222867516110a5","observation_id":"b9b69ef1-5fa3-41b3-8b1b-4d41fabd2901","resolution":{"observed_at":"2026-05-19T19:37:44.191706Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"f24ca0f0-badb-488f-968f-ae62ce5ce15e","year":2011},"citing_paper":{"arxiv_id":"2605.15695","last_updated":"2026-05-15T07:38:04Z","snapshot_observed_at":"2026-07-06T23:26:56.013191Z","submitted_at":"2026-05-15T07:38:04Z","title":"ParamSpMM: Adaptive and Efficient Sparse Matrix-Matrix Multiplication on GPUs for GNNs","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-05-19T19:35:51.992891Z"},"links":{"citing_paper":"/paper/2605.15695"},"observation_digest":"sha256:d620aecca1a61df7c929fb374279bdbb5d58d204bdc610e3f5848873eb474007","observation_id":"4b082e5c-8e3b-48d6-a503-b2060d2c44b0","resolution":{"observed_at":"2026-05-19T19:37:44.189988Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-06-05T21:23:00.469572Z","title":"ICS ’22, New York, NY, USA (2022)","venue":null,"work_id":"30185929-d393-4730-b6f4-fdfc80c3d4c0","year":2022},"citing_paper":{"arxiv_id":"2605.15695","last_updated":"2026-05-15T07:38:04Z","snapshot_observed_at":"2026-07-06T23:26:56.013191Z","submitted_at":"2026-05-15T07:38:04Z","title":"ParamSpMM: Adaptive and Efficient Sparse Matrix-Matrix Multiplication on GPUs for GNNs","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-05-19T19:35:51.992891Z"},"links":{"citing_paper":"/paper/2605.15695"},"observation_digest":"sha256:3542243a7033a46ff60437cfa4201c55b47c79db47ded0cfce12a7d55670637d","observation_id":"704a10d7-ba66-4005-b22c-7f35628c2749","resolution":{"observed_at":"2026-05-19T19:37:44.119045Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2605.15695","last_updated":"2026-05-15T07:38:04Z","latest_version":1,"primary_category":"cs.DC","snapshot_observed_at":"2026-07-06T23:26:56.013191Z","submitted_at":"2026-05-15T07:38:04Z","title":"ParamSpMM: Adaptive and Efficient Sparse Matrix-Matrix Multiplication on GPUs for GNNs"},"reference_resolution":{"displayed":32,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":15,"verified_exact":1,"verified_fuzzy":15},"total_outbound_references":32},"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":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2605.15695."}