{"as_of":"2026-08-19T21:48:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:78c962afb9c26cc43883f106146144d6236659c5ae2e80952a4ddef8e37de4d2","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":8,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":8,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-19T06:32:44.657259+00:00","state":"measured"},{"denominator":8,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":8,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-16T11:33:44.904432Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-04T18:40:03.586792Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2109.11067","last_updated":"2021-09-18T19:57:13Z","snapshot_observed_at":"2026-08-19T19:33:42.402958Z","submitted_at":"2021-09-18T19:57:13Z","title":"Serving DNN Models with Multi-Instance GPUs: A Case of the Reconfigurable Machine Scheduling Problem","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2109.11067","snapshot_observed_at":"2026-08-09T14:07:23.231976Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2502.01909","last_updated":"2025-02-04T00:55:59Z","snapshot_observed_at":"2026-08-14T19:54:13.381958Z","submitted_at":"2025-02-04T00:55:59Z","title":"A Multi-Objective Framework for Optimizing GPU-Enabled VM Placement in Cloud Data Centers with Multi-Instance GPU Technology","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-09T14:07:23.231976Z"},"links":{"cited_paper":"/paper/2109.11067","citing_paper":"/paper/2502.01909"},"observation_digest":"sha256:b75bfd83b0d1142378eaac1db50ae6428ea34a5fea18e13cce8089b4b71e5e74","observation_id":"26aff3b3-5125-428b-907a-677809853bb3","resolution":{"observed_at":"2026-08-09T14:07:23.231976Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2109.11067","last_updated":"2021-09-18T19:57:13Z","snapshot_observed_at":"2026-08-19T19:33:42.402958Z","submitted_at":"2021-09-18T19:57:13Z","title":"Serving DNN Models with Multi-Instance GPUs: A Case of the Reconfigurable Machine Scheduling Problem","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2109.11067","snapshot_observed_at":"2026-08-16T11:33:44.904432Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2504.15465","last_updated":"2025-04-21T22:21:39Z","snapshot_observed_at":"2026-08-18T03:56:16.403370Z","submitted_at":"2025-04-21T22:21:39Z","title":"LithOS: An Operating System for Efficient Machine Learning on GPUs","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-16T11:33:44.904432Z"},"links":{"cited_paper":"/paper/2109.11067","citing_paper":"/paper/2504.15465"},"observation_digest":"sha256:9624e904fb46298e899edf94a8d57ff075abe00803109603a617350017d94287","observation_id":"01005658-83cf-4849-b28a-df9da56b85c2","resolution":{"observed_at":"2026-08-16T11:33:44.904432Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2109.11067","last_updated":"2021-09-18T19:57:13Z","snapshot_observed_at":"2026-08-19T19:33:42.402958Z","submitted_at":"2021-09-18T19:57:13Z","title":"Serving DNN Models with Multi-Instance GPUs: A Case of the Reconfigurable Machine Scheduling Problem","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2109.11067","snapshot_observed_at":"2026-08-15T17:01:11.442960Z","title":"Serving DNN models with multi-instance gpus: A case of the reconfigurable machine scheduling problem","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2508.18556","last_updated":"2025-08-25T23:15:49Z","snapshot_observed_at":"2026-08-17T15:57:39.944889Z","submitted_at":"2025-08-25T23:15:49Z","title":"Managing Multi Instance GPUs for High Throughput and Energy Savings","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-15T17:01:11.442960Z"},"links":{"cited_paper":"/paper/2109.11067","citing_paper":"/paper/2508.18556"},"observation_digest":"sha256:6cdeb18a95163153ea1b5cb5681fb3461366f3a314a6e3361719f9582b5b1b2c","observation_id":"988b1264-4700-4582-a371-e6fdcb4a0a28","resolution":{"observed_at":"2026-08-15T17:01:11.442960Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2109.11067","last_updated":"2021-09-18T19:57:13Z","snapshot_observed_at":"2026-08-19T19:33:42.402958Z","submitted_at":"2021-09-18T19:57:13Z","title":"Serving DNN Models with Multi-Instance GPUs: A Case of the Reconfigurable Machine Scheduling Problem","version":1},"cited_work":{"arxiv_id":"2109.11067","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2109.11067","snapshot_observed_at":"2026-07-04T18:40:03.586792Z","title":"Serving DNN models with multi-instance gpus: A case of the reconfigurable machine scheduling problem.CoRR, abs/2109.11067","venue":null,"work_id":"39f85ae5-38dd-418a-a21a-2849450c695c","year":2021},"citing_paper":{"arxiv_id":"2604.08451","last_updated":"2026-04-09T16:49:01Z","snapshot_observed_at":"2026-08-15T16:37:49.497151Z","submitted_at":"2026-04-09T16:49:01Z","title":"Taming GPU Underutilization via Static Partitioning and Fine-grained CPU Offloading","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-10T16:47:49.174774Z"},"links":{"cited_paper":"/paper/2109.11067","citing_paper":"/paper/2604.08451"},"observation_digest":"sha256:d3016f3ce838ffe5cdb24e60af48f3e09bb3d34a7d0b137de0106f9d8ac0811a","observation_id":"caa5332c-f1ed-42d9-9fe6-c8b9a1aa4ff5","resolution":{"observed_at":"2026-05-11T08:11:02.927786Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2109.11067","last_updated":"2021-09-18T19:57:13Z","snapshot_observed_at":"2026-08-19T19:33:42.402958Z","submitted_at":"2021-09-18T19:57:13Z","title":"Serving DNN Models with Multi-Instance GPUs: A Case of the Reconfigurable Machine Scheduling Problem","version":1},"cited_work":{"arxiv_id":"2109.11067","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2109.11067","snapshot_observed_at":"2026-07-04T18:40:03.586792Z","title":"Serving DNN models with multi-instance gpus: A case of the reconfigurable machine scheduling problem.CoRR, abs/2109.11067","venue":null,"work_id":"39f85ae5-38dd-418a-a21a-2849450c695c","year":2021},"citing_paper":{"arxiv_id":"2605.01352","last_updated":"2026-05-02T09:54:20Z","snapshot_observed_at":"2026-08-11T04:08:27.421527Z","submitted_at":"2026-05-02T09:54:20Z","title":"VUDA: Breaking CUDA-Vulkan Isolation for Spatial Sharing of Compute and Graphics on the Same GPU","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-05-10T16:02:19.312951Z"},"links":{"cited_paper":"/paper/2109.11067","citing_paper":"/paper/2605.01352"},"observation_digest":"sha256:48be130fc2603587730e80fa31331e95a450cefa93f14e100f93415b8b0bf3d0","observation_id":"72dfad48-0103-423a-9e58-0e36644ea527","resolution":{"observed_at":"2026-05-11T09:26:01.106266Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2109.11067","last_updated":"2021-09-18T19:57:13Z","snapshot_observed_at":"2026-08-19T19:33:42.402958Z","submitted_at":"2021-09-18T19:57:13Z","title":"Serving DNN Models with Multi-Instance GPUs: A Case of the Reconfigurable Machine Scheduling Problem","version":1},"cited_work":{"arxiv_id":"2109.11067","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2109.11067","snapshot_observed_at":"2026-07-04T18:40:03.586792Z","title":"Serving DNN models with multi-instance gpus: A case of the reconfigurable machine scheduling problem.CoRR, abs/2109.11067","venue":null,"work_id":"39f85ae5-38dd-418a-a21a-2849450c695c","year":2021},"citing_paper":{"arxiv_id":"2606.25082","last_updated":"2026-06-23T18:41:20Z","snapshot_observed_at":"2026-08-05T02:42:00.396448Z","submitted_at":"2026-06-23T18:41:20Z","title":"Energy Efficient Scheduling of AI/ML Workloads on Multi Instance GPUs with Dynamic Repartitioning","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-06-25T22:34:03.839748Z"},"links":{"cited_paper":"/paper/2109.11067","citing_paper":"/paper/2606.25082"},"observation_digest":"sha256:c4584274e953ced9ff026a3572e28a1234a637fcee3783069fff2137b3d1bf9c","observation_id":"cae2280d-cf63-4988-8bf9-d787993ac4a3","resolution":{"observed_at":"2026-07-04T18:40:03.588241Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2109.11067","last_updated":"2021-09-18T19:57:13Z","snapshot_observed_at":"2026-08-19T19:33:42.402958Z","submitted_at":"2021-09-18T19:57:13Z","title":"Serving DNN Models with Multi-Instance GPUs: A Case of the Reconfigurable Machine Scheduling Problem","version":1},"cited_work":{"arxiv_id":"2109.11067","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2109.11067","snapshot_observed_at":"2026-07-04T18:40:03.586792Z","title":"Serving DNN models with multi-instance gpus: A case of the reconfigurable machine scheduling problem.CoRR, abs/2109.11067","venue":null,"work_id":"39f85ae5-38dd-418a-a21a-2849450c695c","year":2021},"citing_paper":{"arxiv_id":"2606.29775","last_updated":"2026-06-29T04:35:48Z","snapshot_observed_at":"2026-08-15T08:30:37.699938Z","submitted_at":"2026-06-29T04:35:48Z","title":"SMART-MIG: A Learning Framework for Scalable and Energy-Efficient GPU Scheduling","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-06-30T04:46:46.384753Z"},"links":{"cited_paper":"/paper/2109.11067","citing_paper":"/paper/2606.29775"},"observation_digest":"sha256:26f1d19212c3025a204df81c885f33925caa6ad2a2af8cae5510b97d331aa5d8","observation_id":"7aa7a2f2-7614-4d97-883e-f00381ed38ec","resolution":{"observed_at":"2026-06-30T16:14:54.091294Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2109.11067","last_updated":"2021-09-18T19:57:13Z","snapshot_observed_at":"2026-08-19T19:33:42.402958Z","submitted_at":"2021-09-18T19:57:13Z","title":"Serving DNN Models with Multi-Instance GPUs: A Case of the Reconfigurable Machine Scheduling Problem","version":1},"cited_work":{"arxiv_id":"2109.11067","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2109.11067","snapshot_observed_at":"2026-07-04T18:40:03.586792Z","title":"Serving DNN models with multi-instance gpus: A case of the reconfigurable machine scheduling problem.CoRR, abs/2109.11067","venue":null,"work_id":"39f85ae5-38dd-418a-a21a-2849450c695c","year":2021},"citing_paper":{"arxiv_id":"2606.30391","last_updated":"2026-06-29T14:44:24Z","snapshot_observed_at":"2026-08-12T14:42:47.843409Z","submitted_at":"2026-06-29T14:44:24Z","title":"Energy-Aware Scheduling for Serverless LLM Serving on Shared GPUs","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-06-30T03:41:51.034169Z"},"links":{"cited_paper":"/paper/2109.11067","citing_paper":"/paper/2606.30391"},"observation_digest":"sha256:215610d9efbde6c4e98a78f97789f007b3ed3cbcdd2cb001a755ef5020c7f069","observation_id":"1722af82-9967-481f-952e-29062533e439","resolution":{"observed_at":"2026-07-01T15:15:48.681322Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2109.11067/citation-record","integrity":"/paper/2109.11067/integrity","json":"/paper/2109.11067/citation-record.json","paper":"/paper/2109.11067"},"outbound":[],"paper":{"arxiv_id":"2109.11067","last_updated":"2021-09-18T19:57:13Z","latest_version":1,"primary_category":"cs.DC","snapshot_observed_at":"2026-08-19T19:33:42.402958Z","submitted_at":"2021-09-18T19:57:13Z","title":"Serving DNN Models with Multi-Instance GPUs: A Case of the Reconfigurable Machine Scheduling Problem"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"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":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"thesis":"As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2109.11067."}