{"as_of":"2026-08-08T08:31:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:b9eb1b09f54fb7214eecec57c678611d025e3872c1330f42c86f8e362bf8b739","coverage":[{"denominator":38,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":38,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-11T11:26:33.422369Z","state":"measured"},{"denominator":38,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":38,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+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/2607.04921/citation-record","integrity":"/paper/2607.04921/integrity","json":"/paper/2607.04921/citation-record.json","paper":"/paper/2607.04921"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T11:26:33.422369Z","title":"neurons that fire together, wire together,","venue":null,"work_id":null,"year":1949},"citing_paper":{"arxiv_id":"2607.04921","last_updated":"2026-07-06T10:49:07Z","snapshot_observed_at":"2026-08-06T13:23:05.012134Z","submitted_at":"2026-07-06T10:49:07Z","title":"Efficient Perception in Automotive Detection and Tracking Using Neuromorphic Computing","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-07-11T11:26:33.422369Z"},"links":{"citing_paper":"/paper/2607.04921"},"observation_digest":"sha256:1902b897bcc5854d01d1c2c449795d97a4c937e90fdfd2ba55b5620f1a18c55c","observation_id":"6ea798fa-5175-4460-b171-8951f23fafd9","resolution":{"observed_at":"2026-07-11T11:26:33.422369Z","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":"2026-07-11T11:26:33.422369Z","title":"Networks of spiking neurons: The third generation of neural network models,","venue":null,"work_id":null,"year":1997},"citing_paper":{"arxiv_id":"2607.04921","last_updated":"2026-07-06T10:49:07Z","snapshot_observed_at":"2026-08-06T13:23:05.012134Z","submitted_at":"2026-07-06T10:49:07Z","title":"Efficient Perception in Automotive Detection and Tracking Using Neuromorphic Computing","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-07-11T11:26:33.422369Z"},"links":{"citing_paper":"/paper/2607.04921"},"observation_digest":"sha256:0474e84576e439d663dd24c99bb5220d894e886e975555ddc3a0e11a3b63d100","observation_id":"8d9d8781-85ff-4735-b57c-646ba9d8d29b","resolution":{"observed_at":"2026-07-11T11:26:33.422369Z","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":"2026-07-11T11:26:33.422369Z","title":"Towards spike-based machine intelligence with neuromorphic computing,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.04921","last_updated":"2026-07-06T10:49:07Z","snapshot_observed_at":"2026-08-06T13:23:05.012134Z","submitted_at":"2026-07-06T10:49:07Z","title":"Efficient Perception in Automotive Detection and Tracking Using Neuromorphic Computing","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-07-11T11:26:33.422369Z"},"links":{"citing_paper":"/paper/2607.04921"},"observation_digest":"sha256:c60f1177ffd7a5298ea6ac4c5780f8160fc369b2d70ce171f569559350d796f3","observation_id":"dfbd8ab6-7b81-45d9-84bb-ae4c274c97dd","resolution":{"observed_at":"2026-07-11T11:26:33.422369Z","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":"2026-07-11T11:26:33.422369Z","title":"Neuromorphic electronic systems,","venue":null,"work_id":null,"year":1990},"citing_paper":{"arxiv_id":"2607.04921","last_updated":"2026-07-06T10:49:07Z","snapshot_observed_at":"2026-08-06T13:23:05.012134Z","submitted_at":"2026-07-06T10:49:07Z","title":"Efficient Perception in Automotive Detection and Tracking Using Neuromorphic Computing","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-07-11T11:26:33.422369Z"},"links":{"citing_paper":"/paper/2607.04921"},"observation_digest":"sha256:325530ef2f3ca598efaa1f0639d9aabff43069cf7713e89a3cf5913de2e476c8","observation_id":"842da2c4-8f7a-4c33-83aa-d5b8b84b98f6","resolution":{"observed_at":"2026-07-11T11:26:33.422369Z","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":"2026-07-11T11:26:33.422369Z","title":"Memory and Information Processing in Neuromorphic Systems,","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2607.04921","last_updated":"2026-07-06T10:49:07Z","snapshot_observed_at":"2026-08-06T13:23:05.012134Z","submitted_at":"2026-07-06T10:49:07Z","title":"Efficient Perception in Automotive Detection and Tracking Using Neuromorphic Computing","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-07-11T11:26:33.422369Z"},"links":{"citing_paper":"/paper/2607.04921"},"observation_digest":"sha256:7bc15a115298a79a44ea680b46a63584cb10018cf67a323696940528829797e0","observation_id":"5526e7a9-bfe8-4c5a-a251-4f9c1ec53e11","resolution":{"observed_at":"2026-07-11T11:26:33.422369Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1705.06963","last_updated":"2017-05-19T12:41:32Z","snapshot_observed_at":"2026-08-02T05:54:37.535068Z","submitted_at":"2017-05-19T12:41:32Z","title":"A Survey of Neuromorphic Computing and Neural Networks in Hardware","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1705.06963","snapshot_observed_at":"2026-07-11T11:26:33.422369Z","title":"A Survey of Neuromorphic Computing and Neural Networks in Hardware,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.04921","last_updated":"2026-07-06T10:49:07Z","snapshot_observed_at":"2026-08-06T13:23:05.012134Z","submitted_at":"2026-07-06T10:49:07Z","title":"Efficient Perception in Automotive Detection and Tracking Using Neuromorphic Computing","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-07-11T11:26:33.422369Z"},"links":{"cited_paper":"/paper/1705.06963","citing_paper":"/paper/2607.04921"},"observation_digest":"sha256:fc0c960598492115c32574fc7f50dc585285dfec0b50b42e1876b7d522e842ef","observation_id":"a9522b65-7fcd-4f5a-a4cc-51a087ef6f74","resolution":{"observed_at":"2026-07-11T11:26:33.422369Z","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":"2026-07-11T11:26:33.422369Z","title":"A quantitative description of membrane current and its application to conduction and excitation in nerve,","venue":null,"work_id":null,"year":1952},"citing_paper":{"arxiv_id":"2607.04921","last_updated":"2026-07-06T10:49:07Z","snapshot_observed_at":"2026-08-06T13:23:05.012134Z","submitted_at":"2026-07-06T10:49:07Z","title":"Efficient Perception in Automotive Detection and Tracking Using Neuromorphic Computing","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-07-11T11:26:33.422369Z"},"links":{"citing_paper":"/paper/2607.04921"},"observation_digest":"sha256:efc1ec44e2ff0e5e434fc85108be2991f3c20510de6996eb3336cbace7e0aca0","observation_id":"463118a5-39af-41d1-bb78-a1d7c59473aa","resolution":{"observed_at":"2026-07-11T11:26:33.422369Z","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":"2026-07-11T11:26:33.422369Z","title":"Loihi: A Neuromorphic Manycore Processor with On-Chip Learning,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.04921","last_updated":"2026-07-06T10:49:07Z","snapshot_observed_at":"2026-08-06T13:23:05.012134Z","submitted_at":"2026-07-06T10:49:07Z","title":"Efficient Perception in Automotive Detection and Tracking Using Neuromorphic Computing","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-07-11T11:26:33.422369Z"},"links":{"citing_paper":"/paper/2607.04921"},"observation_digest":"sha256:483b8f10c0f039538a6503a354d902f146992bbeaf324db0a2c3a403e9ffc329","observation_id":"d5586b4f-0243-468b-8ccb-f741ad88ce18","resolution":{"observed_at":"2026-07-11T11:26:33.422369Z","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":"2026-07-11T11:26:33.422369Z","title":"BrainChip Showcases AI Benchmarks & Improved Edge Device Metrics,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.04921","last_updated":"2026-07-06T10:49:07Z","snapshot_observed_at":"2026-08-06T13:23:05.012134Z","submitted_at":"2026-07-06T10:49:07Z","title":"Efficient Perception in Automotive Detection and Tracking Using Neuromorphic Computing","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-07-11T11:26:33.422369Z"},"links":{"citing_paper":"/paper/2607.04921"},"observation_digest":"sha256:79013131b7f79e5fd168b9fe30c6b8ac20c55a5279a74788fbe500dde329d8b7","observation_id":"744626af-2b05-4b0e-9049-7a05ea4d155a","resolution":{"observed_at":"2026-07-11T11:26:33.422369Z","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":"2026-07-11T11:26:33.422369Z","title":"Available: https://brainchip.com/brainchip-showcases-compelling- benchmarks-and-recommends-better-metrics-for-ai- devices-at-the-edge/","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.04921","last_updated":"2026-07-06T10:49:07Z","snapshot_observed_at":"2026-08-06T13:23:05.012134Z","submitted_at":"2026-07-06T10:49:07Z","title":"Efficient Perception in Automotive Detection and Tracking Using Neuromorphic Computing","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-07-11T11:26:33.422369Z"},"links":{"citing_paper":"/paper/2607.04921"},"observation_digest":"sha256:ec2da341eeaae02574a277b7d5ab411249e422c0197cb8f7c0dfee7a8ce482e7","observation_id":"9528865e-bf12-4b5e-90ff-b1061037afa7","resolution":{"observed_at":"2026-07-11T11:26:33.422369Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1506.02640","last_updated":"2016-05-09T22:22:11Z","snapshot_observed_at":"2026-07-06T04:20:15.965140Z","submitted_at":"2015-06-08T19:52:52Z","title":"You Only Look Once: Unified, Real-Time Object Detection","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1506.02640","snapshot_observed_at":"2026-07-11T11:26:33.422369Z","title":"You Only Look Once: Unified, Real-Time Object Detection,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2607.04921","last_updated":"2026-07-06T10:49:07Z","snapshot_observed_at":"2026-08-06T13:23:05.012134Z","submitted_at":"2026-07-06T10:49:07Z","title":"Efficient Perception in Automotive Detection and Tracking Using Neuromorphic Computing","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-07-11T11:26:33.422369Z"},"links":{"cited_paper":"/paper/1506.02640","citing_paper":"/paper/2607.04921"},"observation_digest":"sha256:1769cd1b1df2cbd5724f48f5d173d5bf6495702d2c98e43df1c54a8193bb5fc2","observation_id":"7d81edea-3b43-4c5a-aed1-25804931d03a","resolution":{"observed_at":"2026-07-11T11:26:33.422369Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.20708","last_updated":"2025-04-15T11:34:30Z","snapshot_observed_at":"2026-08-02T02:25:21.270573Z","submitted_at":"2024-07-30T10:04:16Z","title":"Integer-Valued Training and Spike-Driven Inference Spiking Neural Network for High-performance and Energy-efficient Object Detection","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.20708","snapshot_observed_at":"2026-07-11T11:26:33.422369Z","title":"Integer- Valued Training and Spike-Driven Inference Spiking Neural Network for High-performance and Energy- efficient Object Detection,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.04921","last_updated":"2026-07-06T10:49:07Z","snapshot_observed_at":"2026-08-06T13:23:05.012134Z","submitted_at":"2026-07-06T10:49:07Z","title":"Efficient Perception in Automotive Detection and Tracking Using Neuromorphic Computing","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-07-11T11:26:33.422369Z"},"links":{"cited_paper":"/paper/2407.20708","citing_paper":"/paper/2607.04921"},"observation_digest":"sha256:5ec6a2b53f608bdb2bb74787b8c115cf189f7ac3dddaec7ef36a04a8d88170c0","observation_id":"21929a63-8e09-4643-9b9b-4862a0b92c88","resolution":{"observed_at":"2026-07-11T11:26:33.422369Z","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":"2026-07-11T11:26:33.422369Z","title":"Lapicque’s introduction of the integrate- and-fire model neuron (1907),","venue":null,"work_id":null,"year":1907},"citing_paper":{"arxiv_id":"2607.04921","last_updated":"2026-07-06T10:49:07Z","snapshot_observed_at":"2026-08-06T13:23:05.012134Z","submitted_at":"2026-07-06T10:49:07Z","title":"Efficient Perception in Automotive Detection and Tracking Using Neuromorphic Computing","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-07-11T11:26:33.422369Z"},"links":{"citing_paper":"/paper/2607.04921"},"observation_digest":"sha256:716d76e4698e30884726dbf46e038b4878195443ae5d242bb4f79977362564b2","observation_id":"474d060a-5957-450a-9cc3-f7d490a65190","resolution":{"observed_at":"2026-07-11T11:26:33.422369Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/s00422-006-0068-6","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A Review of the Integrate-and-fire Neuron Model: I. Homogeneous Synaptic Input,","venue":"Biological Cybernetics","work_id":"fcde5bc3-b76e-4eff-8183-7d58f49067c4","year":2006},"citing_paper":{"arxiv_id":"2607.04921","last_updated":"2026-07-06T10:49:07Z","snapshot_observed_at":"2026-08-06T13:23:05.012134Z","submitted_at":"2026-07-06T10:49:07Z","title":"Efficient Perception in Automotive Detection and Tracking Using Neuromorphic Computing","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-07-11T11:26:33.422369Z"},"links":{"citing_paper":"/paper/2607.04921"},"observation_digest":"sha256:eb188bb4b1b3817b13e9dff98188e6130c5ae145e2d1e57afe65950e26cbdf25","observation_id":"aef461f8-a52a-4992-80d2-be36216e4bf9","resolution":{"observed_at":"2026-07-11T11:27:58.105991Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-07-11T23:49:31.084432+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T23:49:31.084432+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1038/s41467-025-62251-6","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A multisynaptic spiking neuron for simultaneously encoding spatiotemporal dynamics,","venue":"Nature Communications","work_id":"ad8978b8-5ac1-4331-b099-4fad1c582226","year":2025},"citing_paper":{"arxiv_id":"2607.04921","last_updated":"2026-07-06T10:49:07Z","snapshot_observed_at":"2026-08-06T13:23:05.012134Z","submitted_at":"2026-07-06T10:49:07Z","title":"Efficient Perception in Automotive Detection and Tracking Using Neuromorphic Computing","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-07-11T11:26:33.422369Z"},"links":{"citing_paper":"/paper/2607.04921"},"observation_digest":"sha256:3b0d2fdb2d7516fa72fea197d399271543f031f8f3991b1b0b38353037900d77","observation_id":"2ea9ef9e-3b2b-4ab2-ba66-4a979781e84f","resolution":{"observed_at":"2026-07-11T11:27:58.067293Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-07-11T23:49:31.413195+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T23:49:31.413195+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1038/s41467-023-44614-z","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Temporal dendritic heterogeneity incorporated with spiking neural networks for learning multi-timescale dynamics,","venue":"Nature Communications","work_id":"0a767537-6cbe-4267-b99d-1e3eefa664c7","year":2024},"citing_paper":{"arxiv_id":"2607.04921","last_updated":"2026-07-06T10:49:07Z","snapshot_observed_at":"2026-08-06T13:23:05.012134Z","submitted_at":"2026-07-06T10:49:07Z","title":"Efficient Perception in Automotive Detection and Tracking Using Neuromorphic Computing","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-07-11T11:26:33.422369Z"},"links":{"citing_paper":"/paper/2607.04921"},"observation_digest":"sha256:45aa3f28863e506dd8b74f209c6132256b78e8e23f7465ec5d288b5dab468863","observation_id":"65738d85-8aff-4945-9aed-3b304da33ed9","resolution":{"observed_at":"2026-07-11T11:27:58.051598Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-07-11T23:49:31.73634+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T23:49:31.73634+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-07-11T11:26:33.422369Z","title":"Synaptic plasticity: taming the beast,","venue":null,"work_id":null,"year":2000},"citing_paper":{"arxiv_id":"2607.04921","last_updated":"2026-07-06T10:49:07Z","snapshot_observed_at":"2026-08-06T13:23:05.012134Z","submitted_at":"2026-07-06T10:49:07Z","title":"Efficient Perception in Automotive Detection and Tracking Using Neuromorphic Computing","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-07-11T11:26:33.422369Z"},"links":{"citing_paper":"/paper/2607.04921"},"observation_digest":"sha256:ddae7bf94e5e8806993fb1aa292a966e9d33d947af2331f8cb749cb8436a832f","observation_id":"ff358045-576b-4465-b966-9318926a5de3","resolution":{"observed_at":"2026-07-11T11:26:33.422369Z","resolver_source":null,"status":"malformed_identifier"},"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":"2026-07-11T11:26:33.422369Z","title":"Spike Timing–Dependent Plasticity: A Hebbian Learning Rule,","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2607.04921","last_updated":"2026-07-06T10:49:07Z","snapshot_observed_at":"2026-08-06T13:23:05.012134Z","submitted_at":"2026-07-06T10:49:07Z","title":"Efficient Perception in Automotive Detection and Tracking Using Neuromorphic Computing","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-07-11T11:26:33.422369Z"},"links":{"citing_paper":"/paper/2607.04921"},"observation_digest":"sha256:2b30b2de4b446a00e3329c3ccfd40d34ad7e27bc47e4aac9bff3ac7c7a33772e","observation_id":"e1219d10-6889-4035-96b8-d27da125b1ac","resolution":{"observed_at":"2026-07-11T11:26:33.422369Z","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":"2026-07-11T11:26:33.422369Z","title":null,"venue":null,"work_id":null,"year":1949},"citing_paper":{"arxiv_id":"2607.04921","last_updated":"2026-07-06T10:49:07Z","snapshot_observed_at":"2026-08-06T13:23:05.012134Z","submitted_at":"2026-07-06T10:49:07Z","title":"Efficient Perception in Automotive Detection and Tracking Using Neuromorphic Computing","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-07-11T11:26:33.422369Z"},"links":{"citing_paper":"/paper/2607.04921"},"observation_digest":"sha256:aadbbedb30cd3908b450b904713b71f35b1f8f6420fa6085d9787bc2cdce0d01","observation_id":"4f3818ab-232c-4fb0-989c-024293c2825c","resolution":{"observed_at":"2026-07-11T11:26:33.422369Z","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":"2026-07-11T11:26:33.422369Z","title":"Surrogate Gradient Learning in Spiking Neural Networks: Bringing the Power of Gradient-Based Optimization to Spiking Neural Networks,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.04921","last_updated":"2026-07-06T10:49:07Z","snapshot_observed_at":"2026-08-06T13:23:05.012134Z","submitted_at":"2026-07-06T10:49:07Z","title":"Efficient Perception in Automotive Detection and Tracking Using Neuromorphic Computing","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-07-11T11:26:33.422369Z"},"links":{"citing_paper":"/paper/2607.04921"},"observation_digest":"sha256:30661d1ddcc2f86e3eb34a4b813d8b57c132367a1725cc1e427a744af223f30f","observation_id":"dba71834-e5a0-46c1-91dd-8e90781a6cac","resolution":{"observed_at":"2026-07-11T11:26:33.422369Z","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":"2026-07-11T11:26:33.422369Z","title":"The Remarkable Robustness of Surrogate Gradient Learning for Instilling Complex Function in Spiking Neural Networks,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.04921","last_updated":"2026-07-06T10:49:07Z","snapshot_observed_at":"2026-08-06T13:23:05.012134Z","submitted_at":"2026-07-06T10:49:07Z","title":"Efficient Perception in Automotive Detection and Tracking Using Neuromorphic Computing","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-07-11T11:26:33.422369Z"},"links":{"citing_paper":"/paper/2607.04921"},"observation_digest":"sha256:91cd72c9598416851ed4ef6777ed89da40cce6c916fb80f2df0d836caeb0cb9c","observation_id":"707c0df2-2084-4037-b903-522328d3911f","resolution":{"observed_at":"2026-07-11T11:26:33.422369Z","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":"2026-07-11T11:26:33.422369Z","title":"Training Deep Spiking Neural Networks Using Backpropagation,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2607.04921","last_updated":"2026-07-06T10:49:07Z","snapshot_observed_at":"2026-08-06T13:23:05.012134Z","submitted_at":"2026-07-06T10:49:07Z","title":"Efficient Perception in Automotive Detection and Tracking Using Neuromorphic Computing","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-07-11T11:26:33.422369Z"},"links":{"citing_paper":"/paper/2607.04921"},"observation_digest":"sha256:2d16a630e1e237afc13decf35774ff291dfe0aed587f80387e8c7535b7de2bbf","observation_id":"8453cbab-79cb-4b7e-b176-2ef05b2c0011","resolution":{"observed_at":"2026-07-11T11:26:33.422369Z","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":"2015.728069","doi":"10.1109/ijcnn.2015.7280696","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Fast-classifying, high-accuracy spiking deep networks through weight and threshold balancing,","venue":null,"work_id":"f34b42ab-048c-4fa9-bfbf-ac838476e527","year":2015},"citing_paper":{"arxiv_id":"2607.04921","last_updated":"2026-07-06T10:49:07Z","snapshot_observed_at":"2026-08-06T13:23:05.012134Z","submitted_at":"2026-07-06T10:49:07Z","title":"Efficient Perception in Automotive Detection and Tracking Using Neuromorphic Computing","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-07-11T11:26:33.422369Z"},"links":{"citing_paper":"/paper/2607.04921"},"observation_digest":"sha256:de96da8d234ec4bf1d9747cbe2c6f7c60b94aa341d8ba89353f349b7ae852211","observation_id":"2e060be2-6e94-4d99-8f52-e52cedab3abe","resolution":{"observed_at":"2026-07-11T11:27:58.097058Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-07-11T23:49:32.802183+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T23:49:32.802183+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-07-11T11:26:33.422369Z","title":"Conversion of Continuous-Valued Deep Networks to Efficient Event-Driven Networks for Image Classification,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.04921","last_updated":"2026-07-06T10:49:07Z","snapshot_observed_at":"2026-08-06T13:23:05.012134Z","submitted_at":"2026-07-06T10:49:07Z","title":"Efficient Perception in Automotive Detection and Tracking Using Neuromorphic Computing","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-07-11T11:26:33.422369Z"},"links":{"citing_paper":"/paper/2607.04921"},"observation_digest":"sha256:93b81b8deab584c8232dbcf6bc3f8711a6967d2073d485698e09d4b933bb90e5","observation_id":"b8881011-ef50-4ec1-a76c-9207f8de26b1","resolution":{"observed_at":"2026-07-11T11:26:33.422369Z","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":"2026-07-11T11:26:33.422369Z","title":"Competitive Hebbian learning through spike-timing-dependent synaptic plasticity,","venue":null,"work_id":null,"year":2000},"citing_paper":{"arxiv_id":"2607.04921","last_updated":"2026-07-06T10:49:07Z","snapshot_observed_at":"2026-08-06T13:23:05.012134Z","submitted_at":"2026-07-06T10:49:07Z","title":"Efficient Perception in Automotive Detection and Tracking Using Neuromorphic Computing","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-07-11T11:26:33.422369Z"},"links":{"citing_paper":"/paper/2607.04921"},"observation_digest":"sha256:e00ab0324ec777ee0c67e052a377842bc2a68ee63cdfb267446bab5c8ffe7be8","observation_id":"18972174-d7a9-4ad4-a9b0-486547ba928b","resolution":{"observed_at":"2026-07-11T11:26:33.422369Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1145/3266229","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"STDP-based Unsupervised Feature Learning using Convolution- over-time in Spiking Neural Networks for Energy- Efficient Neuromorphic Computing,","venue":"ACM Journal on Emerging Technologies in Computing Systems","work_id":"97f97210-5aa1-40d5-b1d0-eacb162eaa17","year":2018},"citing_paper":{"arxiv_id":"2607.04921","last_updated":"2026-07-06T10:49:07Z","snapshot_observed_at":"2026-08-06T13:23:05.012134Z","submitted_at":"2026-07-06T10:49:07Z","title":"Efficient Perception in Automotive Detection and Tracking Using Neuromorphic Computing","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-07-11T11:26:33.422369Z"},"links":{"citing_paper":"/paper/2607.04921"},"observation_digest":"sha256:01ac1f68a6e261dad3d0c4b4394cacd5e37374c721fc31bc07e6f35b789078f8","observation_id":"c372bf9a-711f-48aa-bf17-13ff8583ea8a","resolution":{"observed_at":"2026-07-11T11:27:58.025775Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-07-11T23:49:33.369699+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T23:49:33.369699+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2023.329301","doi":"10.1109/tnano.2023.3293011","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"On-Chip Unsupervised Learning Using STDP in a Spiking Neural Network,","venue":"IEEE Transactions on Nanotechnology","work_id":"3f1d15bc-30bd-4a9b-89f1-dc55615559b5","year":2023},"citing_paper":{"arxiv_id":"2607.04921","last_updated":"2026-07-06T10:49:07Z","snapshot_observed_at":"2026-08-06T13:23:05.012134Z","submitted_at":"2026-07-06T10:49:07Z","title":"Efficient Perception in Automotive Detection and Tracking Using Neuromorphic Computing","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-07-11T11:26:33.422369Z"},"links":{"citing_paper":"/paper/2607.04921"},"observation_digest":"sha256:89bcc2897bd9c6c07966eab22683ae1965598ea1dab5779e47ba56a838c8ea34","observation_id":"679b2d36-b516-45ac-8be4-bc6dedc6a6a1","resolution":{"observed_at":"2026-07-11T11:27:58.041825Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-07-11T23:49:33.615758+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T23:49:33.615758+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/978-3-319-70096-0_10","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"An STDP-Based Supervised Learning Algorithm for Spiking Neural Networks,","venue":"Lecture notes in computer science","work_id":"b212b415-5adc-42f4-b3a6-a88fe770e66b","year":2017},"citing_paper":{"arxiv_id":"2607.04921","last_updated":"2026-07-06T10:49:07Z","snapshot_observed_at":"2026-08-06T13:23:05.012134Z","submitted_at":"2026-07-06T10:49:07Z","title":"Efficient Perception in Automotive Detection and Tracking Using Neuromorphic Computing","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-07-11T11:26:33.422369Z"},"links":{"citing_paper":"/paper/2607.04921"},"observation_digest":"sha256:fcd7133e1df8156b10e8524a0abbc9dbf70394e39157ccb3c0615207ba3b92a9","observation_id":"080c50f3-53bd-4f0c-824c-2093e47c21dd","resolution":{"observed_at":"2026-07-11T11:27:58.110893Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-07-11T23:49:33.883825+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T23:49:33.883825+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-07-11T11:26:33.422369Z","title":"Spatio- Temporal Backpropagation for Training High- Performance Spiking Neural Networks,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.04921","last_updated":"2026-07-06T10:49:07Z","snapshot_observed_at":"2026-08-06T13:23:05.012134Z","submitted_at":"2026-07-06T10:49:07Z","title":"Efficient Perception in Automotive Detection and Tracking Using Neuromorphic Computing","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-07-11T11:26:33.422369Z"},"links":{"citing_paper":"/paper/2607.04921"},"observation_digest":"sha256:290b83192d638b4ab88dd96b3ba9993907a9871d5ccdc53c8f070a41dd97a53e","observation_id":"58d004f1-e3b3-4399-bf3d-63338c7aefcc","resolution":{"observed_at":"2026-07-11T11:26:33.422369Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1901.09948","last_updated":"2019-05-03T16:24:45Z","snapshot_observed_at":"2026-07-06T07:29:33.628905Z","submitted_at":"2019-01-28T19:13:55Z","title":"Surrogate Gradient Learning in Spiking Neural Networks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1901.09948","snapshot_observed_at":"2026-07-11T11:26:33.422369Z","title":"Surrogate Gradient Learning in Spiking Neural Networks,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.04921","last_updated":"2026-07-06T10:49:07Z","snapshot_observed_at":"2026-08-06T13:23:05.012134Z","submitted_at":"2026-07-06T10:49:07Z","title":"Efficient Perception in Automotive Detection and Tracking Using Neuromorphic Computing","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-07-11T11:26:33.422369Z"},"links":{"cited_paper":"/paper/1901.09948","citing_paper":"/paper/2607.04921"},"observation_digest":"sha256:5ce6b667ddf6b3b6e761e10c263f3307bcfa3043017f3695fcb55c15393c4aef","observation_id":"38b98ebd-df4d-4dbe-baeb-75b0b5ef6525","resolution":{"observed_at":"2026-07-11T11:26:33.422369Z","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":"2026-07-11T11:26:33.422369Z","title":"Backpropagation through time: what it does and how to do it,","venue":null,"work_id":null,"year":1990},"citing_paper":{"arxiv_id":"2607.04921","last_updated":"2026-07-06T10:49:07Z","snapshot_observed_at":"2026-08-06T13:23:05.012134Z","submitted_at":"2026-07-06T10:49:07Z","title":"Efficient Perception in Automotive Detection and Tracking Using Neuromorphic Computing","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-07-11T11:26:33.422369Z"},"links":{"citing_paper":"/paper/2607.04921"},"observation_digest":"sha256:c556a15b53e8bb115ea7cc66fe2b0732c21174cf1811181e01c90ad683591e7a","observation_id":"f03fbcaa-4b74-4f4e-8a3c-a6116bbc4708","resolution":{"observed_at":"2026-07-11T11:26:33.422369Z","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":"2026-07-11T11:26:33.422369Z","title":"Are we ready for autonomous driving? The KITTI vision benchmark suite,","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2607.04921","last_updated":"2026-07-06T10:49:07Z","snapshot_observed_at":"2026-08-06T13:23:05.012134Z","submitted_at":"2026-07-06T10:49:07Z","title":"Efficient Perception in Automotive Detection and Tracking Using Neuromorphic Computing","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-07-11T11:26:33.422369Z"},"links":{"citing_paper":"/paper/2607.04921"},"observation_digest":"sha256:4283a0cfe237418cdc13df6aa521a58be4688e1080f88ce4d216d1c9c8d047fe","observation_id":"f3ef01ce-d04d-405a-ac24-bcfe1150c910","resolution":{"observed_at":"2026-07-11T11:26:33.422369Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1805.04687","last_updated":"2020-04-08T09:25:06Z","snapshot_observed_at":"2026-08-07T07:17:42.650855Z","submitted_at":"2018-05-12T09:24:21Z","title":"BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1805.04687","snapshot_observed_at":"2026-07-11T11:26:33.422369Z","title":"BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.04921","last_updated":"2026-07-06T10:49:07Z","snapshot_observed_at":"2026-08-06T13:23:05.012134Z","submitted_at":"2026-07-06T10:49:07Z","title":"Efficient Perception in Automotive Detection and Tracking Using Neuromorphic Computing","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-07-11T11:26:33.422369Z"},"links":{"cited_paper":"/paper/1805.04687","citing_paper":"/paper/2607.04921"},"observation_digest":"sha256:20606768ca63f17dddc83ad47b5462cd496cafda2f2ca236e49b8cffe64dd2d8","observation_id":"6ddddf5d-4c47-4ad0-849e-2ccb29c11058","resolution":{"observed_at":"2026-07-11T11:26:33.422369Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2006.04388","last_updated":"2020-06-08T07:24:33Z","snapshot_observed_at":"2026-07-06T09:26:52.676528Z","submitted_at":"2020-06-08T07:24:33Z","title":"Generalized Focal Loss: Learning Qualified and Distributed Bounding Boxes for Dense Object Detection","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2006.04388","snapshot_observed_at":"2026-07-11T11:26:33.422369Z","title":"Generalized Focal Loss: Learning Qualified and Distributed Bounding Boxes for Dense Object Detection,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.04921","last_updated":"2026-07-06T10:49:07Z","snapshot_observed_at":"2026-08-06T13:23:05.012134Z","submitted_at":"2026-07-06T10:49:07Z","title":"Efficient Perception in Automotive Detection and Tracking Using Neuromorphic Computing","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-07-11T11:26:33.422369Z"},"links":{"cited_paper":"/paper/2006.04388","citing_paper":"/paper/2607.04921"},"observation_digest":"sha256:aad659eb275f4ded5d82e7402a9479a274a94e19ee36c0fbb6aa1e4fde758f0e","observation_id":"aa10ea11-f6e9-4607-b8ec-5923b39e18ca","resolution":{"observed_at":"2026-07-11T11:26:33.422369Z","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":"2026-07-11T11:26:33.422369Z","title":"HOTA: A Higher Order Metric for Evaluating Multi-object Tracking,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.04921","last_updated":"2026-07-06T10:49:07Z","snapshot_observed_at":"2026-08-06T13:23:05.012134Z","submitted_at":"2026-07-06T10:49:07Z","title":"Efficient Perception in Automotive Detection and Tracking Using Neuromorphic Computing","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-07-11T11:26:33.422369Z"},"links":{"citing_paper":"/paper/2607.04921"},"observation_digest":"sha256:cb4a43e04d7f8096a0ff15080e21f1c7429a6b673074e00e0de0fe4685205268","observation_id":"3aef4bb9-577a-49ec-adc6-73323980c2ed","resolution":{"observed_at":"2026-07-11T11:26:33.422369Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2206.14651","last_updated":"2022-07-07T15:36:49Z","snapshot_observed_at":"2026-08-06T22:11:02.627602Z","submitted_at":"2022-06-29T13:45:03Z","title":"BoT-SORT: Robust Associations Multi-Pedestrian Tracking","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2206.14651","snapshot_observed_at":"2026-07-11T11:26:33.422369Z","title":"BoT- SORT: Robust Associations Multi-Pedestrian Tracking,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.04921","last_updated":"2026-07-06T10:49:07Z","snapshot_observed_at":"2026-08-06T13:23:05.012134Z","submitted_at":"2026-07-06T10:49:07Z","title":"Efficient Perception in Automotive Detection and Tracking Using Neuromorphic Computing","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-07-11T11:26:33.422369Z"},"links":{"cited_paper":"/paper/2206.14651","citing_paper":"/paper/2607.04921"},"observation_digest":"sha256:650b441ae4b8357b96f74c0efaf4bfd1ac39f416a3d17d985ca14d075430cd7f","observation_id":"45597d0a-5e63-424f-a301-5abca618fc23","resolution":{"observed_at":"2026-07-11T11:26:33.422369Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2208.11434","last_updated":"2022-08-24T11:00:27Z","snapshot_observed_at":"2026-07-06T13:44:56.079012Z","submitted_at":"2022-08-24T11:00:27Z","title":"YOLOPv2: Better, Faster, Stronger for Panoptic Driving Perception","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.11434","snapshot_observed_at":"2026-07-11T11:26:33.422369Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.04921","last_updated":"2026-07-06T10:49:07Z","snapshot_observed_at":"2026-08-06T13:23:05.012134Z","submitted_at":"2026-07-06T10:49:07Z","title":"Efficient Perception in Automotive Detection and Tracking Using Neuromorphic Computing","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-07-11T11:26:33.422369Z"},"links":{"cited_paper":"/paper/2208.11434","citing_paper":"/paper/2607.04921"},"observation_digest":"sha256:b03d56e8f97b2d0c88e1d29d2881234277e908f01292dc9fb87cfb397293e20e","observation_id":"cb0e4baf-3023-4a96-aa3f-58f6f7429797","resolution":{"observed_at":"2026-07-11T11:26:33.422369Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2110.06864","last_updated":"2022-04-07T16:36:24Z","snapshot_observed_at":"2026-08-07T00:46:09.184516Z","submitted_at":"2021-10-13T17:01:26Z","title":"ByteTrack: Multi-Object Tracking by Associating Every Detection Box","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2110.06864","snapshot_observed_at":"2026-07-11T11:26:33.422369Z","title":"ByteTrack: Multi-Object Tracking by Associating Every Detection Box,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.04921","last_updated":"2026-07-06T10:49:07Z","snapshot_observed_at":"2026-08-06T13:23:05.012134Z","submitted_at":"2026-07-06T10:49:07Z","title":"Efficient Perception in Automotive Detection and Tracking Using Neuromorphic Computing","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-07-11T11:26:33.422369Z"},"links":{"cited_paper":"/paper/2110.06864","citing_paper":"/paper/2607.04921"},"observation_digest":"sha256:843679bcad7b832d3727ba66e3caa4092efcaae717b1a383ec1255e3f70ea6f6","observation_id":"9b2b5ed8-0979-458a-8c5e-20a8c775fef2","resolution":{"observed_at":"2026-07-11T11:26:33.422369Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.04921","last_updated":"2026-07-06T10:49:07Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-06T13:23:05.012134Z","submitted_at":"2026-07-06T10:49:07Z","title":"Efficient Perception in Automotive Detection and Tracking Using Neuromorphic Computing"},"reference_resolution":{"displayed":38,"state_counts":{"malformed_identifier":3,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":28,"verified_exact":7,"verified_fuzzy":0},"total_outbound_references":38},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2607.04921."}