{"as_of":"2026-08-13T05:16:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2a070b7af7f6d0d051a4aee009bbb7e6997c7b144126ca1fdc38b7aaa61cd90c","coverage":[{"denominator":28,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":28,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T13:20:20.292906Z","state":"measured"},{"denominator":28,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":28,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-12T06:34:41.77262+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/2411.16342/citation-record","integrity":"/paper/2411.16342/integrity","json":"/paper/2411.16342/citation-record.json","paper":"/paper/2411.16342"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T13:20:20.172566Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.16342","last_updated":"2024-11-25T12:38:59Z","snapshot_observed_at":"2026-08-12T13:11:15.927535Z","submitted_at":"2024-11-25T12:38:59Z","title":"A Data-Driven Approach to Dataflow-Aware Online Scheduling for Graph Neural Network Inference","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-12T13:20:20.172566Z"},"links":{"citing_paper":"/paper/2411.16342"},"observation_digest":"sha256:3bc3df2340f4015921c2f53d0abb1f89a8ab399937385bf905ac692354ee10b1","observation_id":"1029c49b-1ac6-4ce1-9336-61ebc918796e","resolution":{"observed_at":"2026-08-12T13:20:20.172566Z","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":"2026-08-12T13:20:20.668618Z","title":null,"venue":null,"work_id":"946e6e18-b003-4f86-ae5b-e0089f9b0874","year":2024},"citing_paper":{"arxiv_id":"2411.16342","last_updated":"2024-11-25T12:38:59Z","snapshot_observed_at":"2026-08-12T13:11:15.927535Z","submitted_at":"2024-11-25T12:38:59Z","title":"A Data-Driven Approach to Dataflow-Aware Online Scheduling for Graph Neural Network Inference","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-12T13:20:20.177663Z"},"links":{"citing_paper":"/paper/2411.16342"},"observation_digest":"sha256:771804bc8855903a37c4af41c83c66a57ee29cfd989b8d9431a7bcbc96d0ae20","observation_id":"4d177bac-964a-4d45-8c05-bc4704f349b6","resolution":{"observed_at":"2026-08-12T13:20:20.673226Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:20:20.654348Z","title":null,"venue":null,"work_id":"9e1c017d-e712-4061-a0a3-cb4a347001e4","year":null},"citing_paper":{"arxiv_id":"2411.16342","last_updated":"2024-11-25T12:38:59Z","snapshot_observed_at":"2026-08-12T13:11:15.927535Z","submitted_at":"2024-11-25T12:38:59Z","title":"A Data-Driven Approach to Dataflow-Aware Online Scheduling for Graph Neural Network Inference","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-12T13:20:20.182174Z"},"links":{"citing_paper":"/paper/2411.16342"},"observation_digest":"sha256:9c6556548666168c7e0a827816baeb7228692e68bb7d608dd723a94188f568ac","observation_id":"2f6187e9-ada9-441e-9def-676533ae3cbd","resolution":{"observed_at":"2026-08-12T13:20:20.659132Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2003.00982","last_updated":"2022-12-28T04:57:24Z","snapshot_observed_at":"2026-08-10T00:17:51.124629Z","submitted_at":"2020-03-02T15:58:46Z","title":"Benchmarking Graph Neural Networks","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2003.00982","snapshot_observed_at":"2026-08-12T13:20:20.186697Z","title":"Joshi, Anh Tuan Luu, Thomas Laurent, Yoshua Bengio, and Xavier Bresson","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.16342","last_updated":"2024-11-25T12:38:59Z","snapshot_observed_at":"2026-08-12T13:11:15.927535Z","submitted_at":"2024-11-25T12:38:59Z","title":"A Data-Driven Approach to Dataflow-Aware Online Scheduling for Graph Neural Network Inference","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-12T13:20:20.186697Z"},"links":{"cited_paper":"/paper/2003.00982","citing_paper":"/paper/2411.16342"},"observation_digest":"sha256:a39df833e737b7b56b7cd62f338a46aa06ba3f3fe8670fefb99aa0c0a3d887f2","observation_id":"50a1f877-41ed-4bf7-8bb2-c7dae1b6420e","resolution":{"observed_at":"2026-08-12T13:20:20.186697Z","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":"2026-08-12T13:20:20.639903Z","title":null,"venue":null,"work_id":"a0cb3c40-ca89-4c1e-8303-217a013e4fb1","year":2022},"citing_paper":{"arxiv_id":"2411.16342","last_updated":"2024-11-25T12:38:59Z","snapshot_observed_at":"2026-08-12T13:11:15.927535Z","submitted_at":"2024-11-25T12:38:59Z","title":"A Data-Driven Approach to Dataflow-Aware Online Scheduling for Graph Neural Network Inference","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-12T13:20:20.191435Z"},"links":{"citing_paper":"/paper/2411.16342"},"observation_digest":"sha256:1daf385fb09d134a7dae235156422ea63e4e998ab146d87a36d08f6b45ea4745","observation_id":"54592498-a98a-4de6-8129-5c4ec35130a1","resolution":{"observed_at":"2026-08-12T13:20:20.644392Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:20:20.195804Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2411.16342","last_updated":"2024-11-25T12:38:59Z","snapshot_observed_at":"2026-08-12T13:11:15.927535Z","submitted_at":"2024-11-25T12:38:59Z","title":"A Data-Driven Approach to Dataflow-Aware Online Scheduling for Graph Neural Network Inference","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-12T13:20:20.195804Z"},"links":{"citing_paper":"/paper/2411.16342"},"observation_digest":"sha256:646e7ab6f6a8bd618f2d8c26ce412c5c374230f7a24dc362a4c1fdabd006f9fe","observation_id":"5a8881ae-2fce-423c-9e34-da9112de6196","resolution":{"observed_at":"2026-08-12T13:20:20.195804Z","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":"2026-08-12T13:20:20.200103Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2411.16342","last_updated":"2024-11-25T12:38:59Z","snapshot_observed_at":"2026-08-12T13:11:15.927535Z","submitted_at":"2024-11-25T12:38:59Z","title":"A Data-Driven Approach to Dataflow-Aware Online Scheduling for Graph Neural Network Inference","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-12T13:20:20.200103Z"},"links":{"citing_paper":"/paper/2411.16342"},"observation_digest":"sha256:8a9fb2d3f87f83447d470b95e8cf754b79fae15f818e8e6458d7493068e7fc99","observation_id":"5533018e-f2c8-4bde-b983-cadb8f82d1c0","resolution":{"observed_at":"2026-08-12T13:20:20.200103Z","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":"2026-08-12T13:20:20.607366Z","title":null,"venue":null,"work_id":"7d851abf-51f4-416f-a7fb-52b082b410ce","year":null},"citing_paper":{"arxiv_id":"2411.16342","last_updated":"2024-11-25T12:38:59Z","snapshot_observed_at":"2026-08-12T13:11:15.927535Z","submitted_at":"2024-11-25T12:38:59Z","title":"A Data-Driven Approach to Dataflow-Aware Online Scheduling for Graph Neural Network Inference","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-12T13:20:20.204854Z"},"links":{"citing_paper":"/paper/2411.16342"},"observation_digest":"sha256:ec11b2b8085b8e5a0dfc3d8b7afc517d9ba06085ff164909495a3dde11c0c67c","observation_id":"efda7786-8229-492c-9ad5-2f3fc59fec79","resolution":{"observed_at":"2026-08-12T13:20:20.612251Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:20:20.578616Z","title":null,"venue":null,"work_id":"3636839f-63af-48f5-9fc5-66515ce62ab8","year":2017},"citing_paper":{"arxiv_id":"2411.16342","last_updated":"2024-11-25T12:38:59Z","snapshot_observed_at":"2026-08-12T13:11:15.927535Z","submitted_at":"2024-11-25T12:38:59Z","title":"A Data-Driven Approach to Dataflow-Aware Online Scheduling for Graph Neural Network Inference","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-12T13:20:20.213328Z"},"links":{"citing_paper":"/paper/2411.16342"},"observation_digest":"sha256:174bf2f38a951786c716a76529a099b04bdb9d7bf3cf5ab35149bb8386b8e412","observation_id":"dab0fbda-b834-4ca3-a0e5-cead58088b4a","resolution":{"observed_at":"2026-08-12T13:20:20.583126Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:20:20.564513Z","title":null,"venue":null,"work_id":"64545800-cf71-4fa3-be88-96b370df2110","year":2023},"citing_paper":{"arxiv_id":"2411.16342","last_updated":"2024-11-25T12:38:59Z","snapshot_observed_at":"2026-08-12T13:11:15.927535Z","submitted_at":"2024-11-25T12:38:59Z","title":"A Data-Driven Approach to Dataflow-Aware Online Scheduling for Graph Neural Network Inference","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-12T13:20:20.217351Z"},"links":{"citing_paper":"/paper/2411.16342"},"observation_digest":"sha256:b31f452f25325695c2010f69feffb6269d290c0723a2f1f447e394db26d8d0b2","observation_id":"5c0f8b39-08c1-494c-b9bb-3dfb53115291","resolution":{"observed_at":"2026-08-12T13:20:20.568883Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1609.02907","last_updated":"2017-02-22T09:55:36Z","snapshot_observed_at":"2026-07-06T05:10:16.862707Z","submitted_at":"2016-09-09T19:48:41Z","title":"Semi-Supervised Classification with Graph Convolutional Networks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1609.02907","snapshot_observed_at":"2026-08-12T13:20:20.222057Z","title":"Kipf and Max Welling","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2411.16342","last_updated":"2024-11-25T12:38:59Z","snapshot_observed_at":"2026-08-12T13:11:15.927535Z","submitted_at":"2024-11-25T12:38:59Z","title":"A Data-Driven Approach to Dataflow-Aware Online Scheduling for Graph Neural Network Inference","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-12T13:20:20.222057Z"},"links":{"cited_paper":"/paper/1609.02907","citing_paper":"/paper/2411.16342"},"observation_digest":"sha256:57cf9513985bb976b4935fd7f5d9b290879b2c6882f39290300836606227e96d","observation_id":"09cb02e5-ce63-4262-8695-442906ced1fe","resolution":{"observed_at":"2026-08-12T13:20:20.222057Z","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":"2026-08-12T13:20:20.226633Z","title":"Kolodziej, Mohsen Aznaveh, Matthew Bullock, Jarrett David, Timothy A","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2411.16342","last_updated":"2024-11-25T12:38:59Z","snapshot_observed_at":"2026-08-12T13:11:15.927535Z","submitted_at":"2024-11-25T12:38:59Z","title":"A Data-Driven Approach to Dataflow-Aware Online Scheduling for Graph Neural Network Inference","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-12T13:20:20.226633Z"},"links":{"citing_paper":"/paper/2411.16342"},"observation_digest":"sha256:f0780a949650b60d7a6276dea97c29483cbb7534007e3aa03f06e6513534fd3d","observation_id":"594696cc-4aeb-45cf-b106-93cd71e2429e","resolution":{"observed_at":"2026-08-12T13:20:20.226633Z","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":"2026-08-12T13:20:20.539503Z","title":null,"venue":null,"work_id":"0eaecbe4-8d96-4a5c-80f1-3ba8dfc60d68","year":1977},"citing_paper":{"arxiv_id":"2411.16342","last_updated":"2024-11-25T12:38:59Z","snapshot_observed_at":"2026-08-12T13:11:15.927535Z","submitted_at":"2024-11-25T12:38:59Z","title":"A Data-Driven Approach to Dataflow-Aware Online Scheduling for Graph Neural Network Inference","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-12T13:20:20.235238Z"},"links":{"citing_paper":"/paper/2411.16342"},"observation_digest":"sha256:0aafcc17f69bb1dc4b9084c1303b295e8685c0d35b178ead483019a41312d59d","observation_id":"4a6eb8ce-22e5-47c2-81f0-da4b66d8b699","resolution":{"observed_at":"2026-08-12T13:20:20.544589Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:20:20.525870Z","title":null,"venue":null,"work_id":"a121283e-d83b-4879-9fe8-50ee6aad9cc3","year":2023},"citing_paper":{"arxiv_id":"2411.16342","last_updated":"2024-11-25T12:38:59Z","snapshot_observed_at":"2026-08-12T13:11:15.927535Z","submitted_at":"2024-11-25T12:38:59Z","title":"A Data-Driven Approach to Dataflow-Aware Online Scheduling for Graph Neural Network Inference","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-12T13:20:20.239504Z"},"links":{"citing_paper":"/paper/2411.16342"},"observation_digest":"sha256:5310ce86a2620e675aad143029c20495c3027c1681774b9cbd3d7b5baf90cda7","observation_id":"ddad35e3-deba-4a42-9537-bab31bc0613b","resolution":{"observed_at":"2026-08-12T13:20:20.530152Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:20:20.511655Z","title":null,"venue":null,"work_id":"795119bc-1155-48f6-94ad-adb8cbb3221a","year":2021},"citing_paper":{"arxiv_id":"2411.16342","last_updated":"2024-11-25T12:38:59Z","snapshot_observed_at":"2026-08-12T13:11:15.927535Z","submitted_at":"2024-11-25T12:38:59Z","title":"A Data-Driven Approach to Dataflow-Aware Online Scheduling for Graph Neural Network Inference","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-12T13:20:20.243992Z"},"links":{"citing_paper":"/paper/2411.16342"},"observation_digest":"sha256:8316d6e87d598378c64b86c139868c1d4ba1e23571dce13f9c6bef5d3e1b58a2","observation_id":"75d11f77-9f64-46cd-9f19-44cc14fa9d00","resolution":{"observed_at":"2026-08-12T13:20:20.516223Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2007.08663","last_updated":"2020-07-16T21:46:33Z","snapshot_observed_at":"2026-08-06T13:06:20.395369Z","submitted_at":"2020-07-16T21:46:33Z","title":"TUDataset: A collection of benchmark datasets for learning with graphs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2007.08663","snapshot_observed_at":"2026-08-12T13:20:20.248111Z","title":"Kriege, Franka Bause, Kristian Kersting, Petra Mutzel, and Marion Neumann","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2411.16342","last_updated":"2024-11-25T12:38:59Z","snapshot_observed_at":"2026-08-12T13:11:15.927535Z","submitted_at":"2024-11-25T12:38:59Z","title":"A Data-Driven Approach to Dataflow-Aware Online Scheduling for Graph Neural Network Inference","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-12T13:20:20.248111Z"},"links":{"cited_paper":"/paper/2007.08663","citing_paper":"/paper/2411.16342"},"observation_digest":"sha256:c747d7dbe1cfa9ee59b99e0bcd0cc3e22c0847271608b17a8b4725ba577d39eb","observation_id":"4e72a6fb-580f-497f-bd3b-87663fc17026","resolution":{"observed_at":"2026-08-12T13:20:20.248111Z","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":"2026-08-12T13:20:20.497547Z","title":null,"venue":null,"work_id":"4d7cf6b8-19ef-4b80-809d-95cd0361edf0","year":2023},"citing_paper":{"arxiv_id":"2411.16342","last_updated":"2024-11-25T12:38:59Z","snapshot_observed_at":"2026-08-12T13:11:15.927535Z","submitted_at":"2024-11-25T12:38:59Z","title":"A Data-Driven Approach to Dataflow-Aware Online Scheduling for Graph Neural Network Inference","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-12T13:20:20.252476Z"},"links":{"citing_paper":"/paper/2411.16342"},"observation_digest":"sha256:a2246af6ad302b3255a79127eeb75153b38bb2e71c535415819ec30c196f2ea1","observation_id":"4ab86d85-422e-472a-8ef2-7fdd9864c8a8","resolution":{"observed_at":"2026-08-12T13:20:20.501945Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:20:20.482083Z","title":null,"venue":null,"work_id":"ed76893b-7de4-4575-9d24-cefc2fda9c26","year":1998},"citing_paper":{"arxiv_id":"2411.16342","last_updated":"2024-11-25T12:38:59Z","snapshot_observed_at":"2026-08-12T13:11:15.927535Z","submitted_at":"2024-11-25T12:38:59Z","title":"A Data-Driven Approach to Dataflow-Aware Online Scheduling for Graph Neural Network Inference","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-12T13:20:20.256682Z"},"links":{"citing_paper":"/paper/2411.16342"},"observation_digest":"sha256:a89ee3aa2b25eb24ad21a60196a2ecea5f6f750ef4102007e550db56fcfac3d8","observation_id":"4c7976fd-6b59-4516-b26e-d82ec1bdba68","resolution":{"observed_at":"2026-08-12T13:20:20.487612Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:20:20.261391Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.16342","last_updated":"2024-11-25T12:38:59Z","snapshot_observed_at":"2026-08-12T13:11:15.927535Z","submitted_at":"2024-11-25T12:38:59Z","title":"A Data-Driven Approach to Dataflow-Aware Online Scheduling for Graph Neural Network Inference","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-12T13:20:20.261391Z"},"links":{"citing_paper":"/paper/2411.16342"},"observation_digest":"sha256:aa7e1fb1da3dd13fdf6e5ef7996741d40c2d7f84449eef154af1a6805122fd0c","observation_id":"3e3731ce-ba29-4e12-a596-067bedb2a824","resolution":{"observed_at":"2026-08-12T13:20:20.261391Z","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":"2026-08-12T13:20:20.270086Z","title":null,"venue":null,"work_id":null,"year":1968},"citing_paper":{"arxiv_id":"2411.16342","last_updated":"2024-11-25T12:38:59Z","snapshot_observed_at":"2026-08-12T13:11:15.927535Z","submitted_at":"2024-11-25T12:38:59Z","title":"A Data-Driven Approach to Dataflow-Aware Online Scheduling for Graph Neural Network Inference","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-12T13:20:20.270086Z"},"links":{"citing_paper":"/paper/2411.16342"},"observation_digest":"sha256:4a74ae13dc31feb44880015c0fee55495885653a1b10c6f501561cd91e9adef4","observation_id":"949682ee-9787-401f-98ce-9b7add695207","resolution":{"observed_at":"2026-08-12T13:20:20.270086Z","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":"2026-08-12T13:20:20.449263Z","title":null,"venue":null,"work_id":"2ac64a1f-2a56-46e7-8ff4-5831c3b9e464","year":2002},"citing_paper":{"arxiv_id":"2411.16342","last_updated":"2024-11-25T12:38:59Z","snapshot_observed_at":"2026-08-12T13:11:15.927535Z","submitted_at":"2024-11-25T12:38:59Z","title":"A Data-Driven Approach to Dataflow-Aware Online Scheduling for Graph Neural Network Inference","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-12T13:20:20.274685Z"},"links":{"citing_paper":"/paper/2411.16342"},"observation_digest":"sha256:457f1c45cee302069f561273f0ea39f0f1b826970b5df7698c2f6cd8ec9d9d26","observation_id":"e36a6354-3cf4-4f4a-8597-cd70cfd3c83f","resolution":{"observed_at":"2026-08-12T13:20:20.453898Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:20:20.265866Z","title":"In 2023 IEEE International Symposium on High- Performance Computer Architecture (HPCA)","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.16342","last_updated":"2024-11-25T12:38:59Z","snapshot_observed_at":"2026-08-12T13:11:15.927535Z","submitted_at":"2024-11-25T12:38:59Z","title":"A Data-Driven Approach to Dataflow-Aware Online Scheduling for Graph Neural Network Inference","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-12T13:20:20.265866Z"},"links":{"citing_paper":"/paper/2411.16342"},"observation_digest":"sha256:4166910d9b7fdba7cb979baf08e26bda95b1e091011910aa85c671501cd649c9","observation_id":"6fb26aaf-44e3-43b1-8c0f-7953b9ac2c5d","resolution":{"observed_at":"2026-08-12T13:20:20.265866Z","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":"2026-08-12T13:20:20.282995Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2411.16342","last_updated":"2024-11-25T12:38:59Z","snapshot_observed_at":"2026-08-12T13:11:15.927535Z","submitted_at":"2024-11-25T12:38:59Z","title":"A Data-Driven Approach to Dataflow-Aware Online Scheduling for Graph Neural Network Inference","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-12T13:20:20.282995Z"},"links":{"citing_paper":"/paper/2411.16342"},"observation_digest":"sha256:e7c04c0f30bb047c255d3b43d53ee50b2d36327533ee22252dfeb24eddbceddd","observation_id":"a848eead-67dc-449c-b8a4-bc4ffdd9210c","resolution":{"observed_at":"2026-08-12T13:20:20.282995Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2205.13901","last_updated":"2022-05-27T11:12:50Z","snapshot_observed_at":"2026-08-04T09:11:55.237277Z","submitted_at":"2022-05-27T11:12:50Z","title":"Bias Reduction via Cooperative Bargaining in Synthetic Graph Dataset Generation","version":1},"cited_work":{"arxiv_id":"2205.13901","doi":null,"metadata_source":"pith","pith_arxiv_id":"2205.13901","snapshot_observed_at":"2026-08-12T13:20:20.355193Z","title":"Bias Reduction via Cooperative Bargaining in Synthetic Graph Dataset Generation","venue":"cs.LG","work_id":"abd12042-b70f-4e9a-a4cf-6d6dbcd88aa6","year":2022},"citing_paper":{"arxiv_id":"2411.16342","last_updated":"2024-11-25T12:38:59Z","snapshot_observed_at":"2026-08-12T13:11:15.927535Z","submitted_at":"2024-11-25T12:38:59Z","title":"A Data-Driven Approach to Dataflow-Aware Online Scheduling for Graph Neural Network Inference","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-12T13:20:20.287269Z"},"links":{"cited_paper":"/paper/2205.13901","citing_paper":"/paper/2411.16342"},"observation_digest":"sha256:355a5063e3d184199c2a7159ee3bc52d6719845580ef36aa09139c14836d4216","observation_id":"a099f3c2-3578-4f34-926b-029c8f145b99","resolution":{"observed_at":"2026-08-12T13:20:20.362597Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:20:20.278797Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2411.16342","last_updated":"2024-11-25T12:38:59Z","snapshot_observed_at":"2026-08-12T13:11:15.927535Z","submitted_at":"2024-11-25T12:38:59Z","title":"A Data-Driven Approach to Dataflow-Aware Online Scheduling for Graph Neural Network Inference","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-12T13:20:20.278797Z"},"links":{"citing_paper":"/paper/2411.16342"},"observation_digest":"sha256:707e57e6ee9fb928ec7da909a322063e5f8ef06ae4ae8e38d781d2ae2d586f03","observation_id":"7e9c3d5c-cbf7-47d6-90ea-2beb951561c4","resolution":{"observed_at":"2026-08-12T13:20:20.278797Z","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":"2026-08-12T13:20:20.416930Z","title":null,"venue":null,"work_id":"274d4b04-c79e-46a5-98e9-122172051400","year":2020},"citing_paper":{"arxiv_id":"2411.16342","last_updated":"2024-11-25T12:38:59Z","snapshot_observed_at":"2026-08-12T13:11:15.927535Z","submitted_at":"2024-11-25T12:38:59Z","title":"A Data-Driven Approach to Dataflow-Aware Online Scheduling for Graph Neural Network Inference","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-12T13:20:20.292906Z"},"links":{"citing_paper":"/paper/2411.16342"},"observation_digest":"sha256:86ac47549d21f028ba25d9b3148dd290503c610cd7d4feb04921cdfbc6559031","observation_id":"7173e4ff-6ec8-4dff-83ea-7759febd47cd","resolution":{"observed_at":"2026-08-12T13:20:20.421410Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:20:20.230922Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.16342","last_updated":"2024-11-25T12:38:59Z","snapshot_observed_at":"2026-08-12T13:11:15.927535Z","submitted_at":"2024-11-25T12:38:59Z","title":"A Data-Driven Approach to Dataflow-Aware Online Scheduling for Graph Neural Network Inference","version":1},"reference_index":1244,"source":"pdf_text","source_observed_at":"2026-08-12T13:20:20.230922Z"},"links":{"citing_paper":"/paper/2411.16342"},"observation_digest":"sha256:5c21e089b433db06c9ee04b50a6c913ee081014a2abf04fd900c5d4bf38fe47c","observation_id":"be9620f5-1a33-4cf2-913c-a7ba2038fc81","resolution":{"observed_at":"2026-08-12T13:20:20.230922Z","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":"2026-08-12T13:20:20.592840Z","title":"In 2023 IEEE 5th International Conference on Artificial Intelligence Circuits and Systems (AICAS)","venue":null,"work_id":"d7d59afb-9d4c-4b06-94e9-0e82617171a1","year":2023},"citing_paper":{"arxiv_id":"2411.16342","last_updated":"2024-11-25T12:38:59Z","snapshot_observed_at":"2026-08-12T13:11:15.927535Z","submitted_at":"2024-11-25T12:38:59Z","title":"A Data-Driven Approach to Dataflow-Aware Online Scheduling for Graph Neural Network Inference","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-12T13:20:20.209177Z"},"links":{"citing_paper":"/paper/2411.16342"},"observation_digest":"sha256:538f65e6b99ecdcb6335bea47a2f3354b00fc0f5a45ec3c683929096b621c349","observation_id":"3496bb4a-6a41-4c50-8a35-1eff22983ce7","resolution":{"observed_at":"2026-08-12T13:20:20.597580Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2411.16342","last_updated":"2024-11-25T12:38:59Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-12T13:11:15.927535Z","submitted_at":"2024-11-25T12:38:59Z","title":"A Data-Driven Approach to Dataflow-Aware Online Scheduling for Graph Neural Network Inference"},"reference_resolution":{"displayed":28,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":25,"verified_exact":1,"verified_fuzzy":1},"total_outbound_references":28},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:2411.16342."}