{"as_of":"2026-08-08T03:20:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:dad10cc6a420c9c0feae4a52a138c494b2dec4bbe41df4b5f8b703499cdfa552","coverage":[{"denominator":14,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":14,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-03T17:26:41.428861Z","state":"measured"},{"denominator":14,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":14,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+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/2512.09786/citation-record","integrity":"/paper/2512.09786/integrity","json":"/paper/2512.09786/citation-record.json","paper":"/paper/2512.09786"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"1611.09482","last_updated":"2016-11-29T04:16:44Z","snapshot_observed_at":"2026-07-06T05:20:29.376547Z","submitted_at":"2016-11-29T04:16:44Z","title":"Fast Wavenet Generation Algorithm","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1611.09482","snapshot_observed_at":"2026-08-03T17:26:40.980063Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.09786","last_updated":"2026-05-27T09:22:43Z","snapshot_observed_at":"2026-08-07T23:22:55.694113Z","submitted_at":"2025-12-10T16:07:17Z","title":"TinyD\\'ej\\`aVu: Smaller RAM and Faster Inference with Neural Networks on MCUs for Sensor Data Streams","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-03T17:26:40.980063Z"},"links":{"cited_paper":"/paper/1611.09482","citing_paper":"/paper/2512.09786"},"observation_digest":"sha256:4426dddc89387c27f74e0846b7dbf5a06f4c679367365926a4b0c27f1f70ab00","observation_id":"c95e3ff0-da1a-47c5-9f4a-1de589a619ea","resolution":{"observed_at":"2026-08-03T17:26:40.980063Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.22489/cinc.2023","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:28:27.165013Z","title":null,"venue":null,"work_id":"7048e13f-82e2-447b-9a91-129e27d94ba6","year":2023},"citing_paper":{"arxiv_id":"2512.09786","last_updated":"2026-05-27T09:22:43Z","snapshot_observed_at":"2026-08-07T23:22:55.694113Z","submitted_at":"2025-12-10T16:07:17Z","title":"TinyD\\'ej\\`aVu: Smaller RAM and Faster Inference with Neural Networks on MCUs for Sensor Data Streams","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-03T17:26:41.047938Z"},"links":{"citing_paper":"/paper/2512.09786"},"observation_digest":"sha256:11ceced67ac10bf9d54991282689dd0d735ea5239ad195466ee33e5fdc2a3916","observation_id":"94e79134-a2ab-4ef1-8e1e-fe3065d3e205","resolution":{"observed_at":"2026-08-03T17:28:27.230598Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2202.07125","last_updated":"2023-05-11T21:47:52Z","snapshot_observed_at":"2026-08-06T09:46:00.800448Z","submitted_at":"2022-02-15T01:43:27Z","title":"Transformers in Time Series: A Survey","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2202.07125","snapshot_observed_at":"2026-08-03T17:26:41.216067Z","title":"Transformers in time series: A survey.arXiv preprint arXiv:2202.07125,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.09786","last_updated":"2026-05-27T09:22:43Z","snapshot_observed_at":"2026-08-07T23:22:55.694113Z","submitted_at":"2025-12-10T16:07:17Z","title":"TinyD\\'ej\\`aVu: Smaller RAM and Faster Inference with Neural Networks on MCUs for Sensor Data Streams","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-03T17:26:41.216067Z"},"links":{"cited_paper":"/paper/2202.07125","citing_paper":"/paper/2512.09786"},"observation_digest":"sha256:c3774dc91167e25213be208058b4a1cfd26594e3d0d8482f4f592e60da212142","observation_id":"66ce7fab-48c3-4327-8a51-476692af0969","resolution":{"observed_at":"2026-08-03T17:26:41.216067Z","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":"2026-08-03T17:26:41.428861Z","title":"Flextensor: An automatic schedule exploration and opti- mization framework for tensor computation on heteroge- neous system","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2512.09786","last_updated":"2026-05-27T09:22:43Z","snapshot_observed_at":"2026-08-07T23:22:55.694113Z","submitted_at":"2025-12-10T16:07:17Z","title":"TinyD\\'ej\\`aVu: Smaller RAM and Faster Inference with Neural Networks on MCUs for Sensor Data Streams","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-03T17:26:41.428861Z"},"links":{"citing_paper":"/paper/2512.09786"},"observation_digest":"sha256:a6639935a1404d18e9a3709e48a9ca6b1d429aa41c8f28c6bcfe74e1159cb987","observation_id":"29008ae1-f5c1-440d-9da5-38d51e90055e","resolution":{"observed_at":"2026-08-03T17:26:41.428861Z","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":"2026-08-03T17:26:41.133892Z","title":"The IREE Authors","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2512.09786","last_updated":"2026-05-27T09:22:43Z","snapshot_observed_at":"2026-08-07T23:22:55.694113Z","submitted_at":"2025-12-10T16:07:17Z","title":"TinyD\\'ej\\`aVu: Smaller RAM and Faster Inference with Neural Networks on MCUs for Sensor Data Streams","version":2},"reference_index":173,"source":"pdf_text","source_observed_at":"2026-08-03T17:26:41.133892Z"},"links":{"citing_paper":"/paper/2512.09786"},"observation_digest":"sha256:d85fc5bc758acc4f6af79e9418d2420dd2ac4fc04d330c236b980a7f692fcc90","observation_id":"6595b88a-0990-48b5-89be-2923bf08e91a","resolution":{"observed_at":"2026-08-03T17:26:41.133892Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1609.03499","last_updated":"2016-09-19T18:04:35Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2016-09-12T17:29:40Z","title":"WaveNet: A Generative Model for Raw Audio","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1609.03499","snapshot_observed_at":"2026-08-03T17:26:40.919835Z","title":"org/abs/1609.03499","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.09786","last_updated":"2026-05-27T09:22:43Z","snapshot_observed_at":"2026-08-07T23:22:55.694113Z","submitted_at":"2025-12-10T16:07:17Z","title":"TinyD\\'ej\\`aVu: Smaller RAM and Faster Inference with Neural Networks on MCUs for Sensor Data Streams","version":2},"reference_index":2016,"source":"pdf_text","source_observed_at":"2026-08-03T17:26:40.919835Z"},"links":{"cited_paper":"/paper/1609.03499","citing_paper":"/paper/2512.09786"},"observation_digest":"sha256:f62ea270d6392c3d6aad9c433e01d515eb1223556e61c532f043b01b83cfc56b","observation_id":"154622f4-9c8e-4caf-bcfd-3e36fdc24b60","resolution":{"observed_at":"2026-08-03T17:26:40.919835Z","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":"2026-08-03T17:26:40.685779Z","title":"and Baccelli, E","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.09786","last_updated":"2026-05-27T09:22:43Z","snapshot_observed_at":"2026-08-07T23:22:55.694113Z","submitted_at":"2025-12-10T16:07:17Z","title":"TinyD\\'ej\\`aVu: Smaller RAM and Faster Inference with Neural Networks on MCUs for Sensor Data Streams","version":2},"reference_index":2017,"source":"pdf_text","source_observed_at":"2026-08-03T17:26:40.685779Z"},"links":{"citing_paper":"/paper/2512.09786"},"observation_digest":"sha256:63e9c7279277853d69415a91a2ea75222481c89c753eb63f25d76633fb858c7a","observation_id":"05e9aca2-3592-4faf-b7c1-08d220bcbd79","resolution":{"observed_at":"2026-08-03T17:26:40.685779Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1803.01271","last_updated":"2018-04-19T14:32:38Z","snapshot_observed_at":"2026-07-06T06:26:27.965096Z","submitted_at":"2018-03-04T00:20:29Z","title":"An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1803.01271","snapshot_observed_at":"2026-08-03T17:26:40.504876Z","title":"arXiv:1803.01271 [cs]","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.09786","last_updated":"2026-05-27T09:22:43Z","snapshot_observed_at":"2026-08-07T23:22:55.694113Z","submitted_at":"2025-12-10T16:07:17Z","title":"TinyD\\'ej\\`aVu: Smaller RAM and Faster Inference with Neural Networks on MCUs for Sensor Data Streams","version":2},"reference_index":2018,"source":"pdf_text","source_observed_at":"2026-08-03T17:26:40.504876Z"},"links":{"cited_paper":"/paper/1803.01271","citing_paper":"/paper/2512.09786"},"observation_digest":"sha256:aba7dd877a421f2af3c073326adf082060e569cb12dde4515b8acf863b5a6628","observation_id":"1ad69676-6e85-40e5-bdef-689e31b82b2e","resolution":{"observed_at":"2026-08-03T17:26:40.504876Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1905.12322","last_updated":"2019-06-13T17:55:30Z","snapshot_observed_at":"2026-08-04T04:17:53.148033Z","submitted_at":"2019-05-29T10:50:32Z","title":"A Study of BFLOAT16 for Deep Learning Training","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1905.12322","snapshot_observed_at":"2026-08-03T17:26:40.823419Z","title":"T., Jammala- madaka, N., Huang, J., Yuen, H., et al","venue":null,"work_id":null,"year":1905},"citing_paper":{"arxiv_id":"2512.09786","last_updated":"2026-05-27T09:22:43Z","snapshot_observed_at":"2026-08-07T23:22:55.694113Z","submitted_at":"2025-12-10T16:07:17Z","title":"TinyD\\'ej\\`aVu: Smaller RAM and Faster Inference with Neural Networks on MCUs for Sensor Data Streams","version":2},"reference_index":2019,"source":"pdf_text","source_observed_at":"2026-08-03T17:26:40.823419Z"},"links":{"cited_paper":"/paper/1905.12322","citing_paper":"/paper/2512.09786"},"observation_digest":"sha256:b13239f29b33a376e5989da39f7471d8b4daeaf5065c52ffe7c8d22215278f08","observation_id":"090c5d92-be6b-43a1-9757-e54a5bb750e2","resolution":{"observed_at":"2026-08-03T17:26:40.823419Z","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":"2026-08-03T17:26:41.294275Z","title":"doi: 10.1109/TBCAS.2019.2959160","venue":null,"work_id":null,"year":1932},"citing_paper":{"arxiv_id":"2512.09786","last_updated":"2026-05-27T09:22:43Z","snapshot_observed_at":"2026-08-07T23:22:55.694113Z","submitted_at":"2025-12-10T16:07:17Z","title":"TinyD\\'ej\\`aVu: Smaller RAM and Faster Inference with Neural Networks on MCUs for Sensor Data Streams","version":2},"reference_index":2020,"source":"pdf_text","source_observed_at":"2026-08-03T17:26:41.294275Z"},"links":{"citing_paper":"/paper/2512.09786"},"observation_digest":"sha256:d1d5eda4f5fb4fb6dcdc553542d8eb959789042cce5eb49ea1b7dbc311dbbee1","observation_id":"5ad0555a-82e5-4af9-a021-6196a5702422","resolution":{"observed_at":"2026-08-03T17:26:41.294275Z","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":"2026-08-03T17:26:40.561640Z","title":"URL http://arxiv","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2512.09786","last_updated":"2026-05-27T09:22:43Z","snapshot_observed_at":"2026-08-07T23:22:55.694113Z","submitted_at":"2025-12-10T16:07:17Z","title":"TinyD\\'ej\\`aVu: Smaller RAM and Faster Inference with Neural Networks on MCUs for Sensor Data Streams","version":2},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-03T17:26:40.561640Z"},"links":{"citing_paper":"/paper/2512.09786"},"observation_digest":"sha256:e09acde112043f68a4734a0c1f09dbaec8d22247ba094b325c5b5e6d8d9d0a6a","observation_id":"0a2aa434-87bc-4043-a541-24c3bb66a3ba","resolution":{"observed_at":"2026-08-03T17:26:40.561640Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.17269","last_updated":"2025-01-28T19:57:55Z","snapshot_observed_at":"2026-07-06T20:27:37.265266Z","submitted_at":"2025-01-28T19:57:55Z","title":"A 1-D CNN inference engine for constrained platforms","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.17269","snapshot_observed_at":"2026-08-03T17:26:40.878298Z","title":"A 1-d cnn inference engine for constrained platforms.arXiv preprint arXiv:2501.17269,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.09786","last_updated":"2026-05-27T09:22:43Z","snapshot_observed_at":"2026-08-07T23:22:55.694113Z","submitted_at":"2025-12-10T16:07:17Z","title":"TinyD\\'ej\\`aVu: Smaller RAM and Faster Inference with Neural Networks on MCUs for Sensor Data Streams","version":2},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-03T17:26:40.878298Z"},"links":{"cited_paper":"/paper/2501.17269","citing_paper":"/paper/2512.09786"},"observation_digest":"sha256:38e6f4d0346d994b7ea77b810a13de69bde18991ff2137431722474b8b237627","observation_id":"3bcfc501-9e6b-4e08-bfc6-a3d3aa149dd2","resolution":{"observed_at":"2026-08-03T17:26:40.878298Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.21060","last_updated":"2024-05-31T17:50:01Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-05-31T17:50:01Z","title":"Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.21060","snapshot_observed_at":"2026-08-03T17:26:40.615016Z","title":"org/abs/2405.21060","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.09786","last_updated":"2026-05-27T09:22:43Z","snapshot_observed_at":"2026-08-07T23:22:55.694113Z","submitted_at":"2025-12-10T16:07:17Z","title":"TinyD\\'ej\\`aVu: Smaller RAM and Faster Inference with Neural Networks on MCUs for Sensor Data Streams","version":2},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-03T17:26:40.615016Z"},"links":{"cited_paper":"/paper/2405.21060","citing_paper":"/paper/2512.09786"},"observation_digest":"sha256:3427f25138340fff13d4fe21e67b60526fed0fd111db87b89f1d54fd38237526","observation_id":"069384ca-0ebd-4646-bcf1-38c579b7bb8d","resolution":{"observed_at":"2026-08-03T17:26:40.615016Z","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":"2026-08-03T17:26:40.753418Z","title":"RIOT-ML: toolkit for over-the-air secure updates and performance evaluation of TinyML models.Annals of Telecommunications, pp","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2512.09786","last_updated":"2026-05-27T09:22:43Z","snapshot_observed_at":"2026-08-07T23:22:55.694113Z","submitted_at":"2025-12-10T16:07:17Z","title":"TinyD\\'ej\\`aVu: Smaller RAM and Faster Inference with Neural Networks on MCUs for Sensor Data Streams","version":2},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-03T17:26:40.753418Z"},"links":{"citing_paper":"/paper/2512.09786"},"observation_digest":"sha256:cc18a35ebe28d75f03d9a2dc6cb1f431a9d4745906db4f366efb06a2351affd6","observation_id":"b9937e53-fcc1-4efa-8cb4-d78941290197","resolution":{"observed_at":"2026-08-03T17:26:40.753418Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2512.09786","last_updated":"2026-05-27T09:22:43Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-07T23:22:55.694113Z","submitted_at":"2025-12-10T16:07:17Z","title":"TinyD\\'ej\\`aVu: Smaller RAM and Faster Inference with Neural Networks on MCUs for Sensor Data Streams"},"reference_resolution":{"displayed":14,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":12,"verified_exact":1,"verified_fuzzy":0},"total_outbound_references":14},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:2512.09786."}