{"as_of":"2026-08-08T11:34:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:e6ee3508ae47f3006005d12b6ed836c968cca3109ebd7d17846210dfc2aa8fe2","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":"2026-08-08T09:28:00.798775Z","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":"sha256:1b4e48a5651534416b93ad0096a1fb6856d620ba3514467e4d32d29970f1557f","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":"2026-08-08T09:28:00.798775Z","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":"sha256:58d959298fde405f7b1b9b999e039a8c2d0b722d34a4498a9e2933da827fbfc2","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":"2026-08-08T09:28:00.798775Z","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:f95351d770f0074b315c303b739b579cca44fff5609a4de5080f1646ced31b93","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":"2026-08-08T09:28:00.798775Z","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:aac2feda64dc70c80eab3f923eeef4cf35e6973ec34523049c8c9eb3d2d4f2b0","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":"2026-08-08T09:28:00.798775Z","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:e5508c5b75136f7866f18f10fbd6954ea7064a980ca42254b69bb6791411ff07","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":"2026-08-08T09:28:00.798775Z","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":"sha256:0bba388506a2bfadcb7c0d1a5bd89f2e9f022ea77b6ee289c6a9dea0b819a45b","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":"2026-08-08T09:28:00.798775Z","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":"sha256:0b6b0433ca81484f30dc870388d7bbe9da2871b84401a8cf8c62ce120dbadf73","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":"2026-08-08T09:28:00.798775Z","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:e3ffaa94a8b11cc80ce42ca29c4253ef30fc42315df94d3cf04bb452dedbaa62","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":"2026-08-08T09:28:00.798775Z","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":"sha256:14ad48d704f479c977d2c22f3bfd9a956869898637607976aceac0cefc79ee0c","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":"2026-08-08T09:28:00.798775Z","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":"sha256:61404e866469d155c031b3a5f63599b248beb8b7b5548b90bf18848b74e4c8d9","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":"2026-08-08T09:28:00.798775Z","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":"sha256:6d28a35d7779338f04465d4977e2eb2091eef30eb638e7fd059f5c0c7e74404e","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":"2026-08-08T09:28:00.798775Z","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:fba5ed8ab8802abe8b74415e39d44f65c5e9077589401c3b61df056b1a1dd107","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":"2026-08-08T09:28:00.798775Z","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":"sha256:2337e7761238ad4ad1abc9d2ba6b0336b3cb7f342124756f8c99f2f90d49618e","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":"2026-08-08T09:28:00.798775Z","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:ea993a80032c956f68bbeea6c318a162cfcb8b22a470464a1fa78414fccda55e","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":"2026-08-08T09:28:00.798775Z","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":"sha256:284d93bbf88590f34f4e778a39824f8ae3b79af1c82ff410df675cea2841ffc8","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":"2026-08-08T09:28:00.798775Z","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:da0a936a7cb18d9c4bc9a9bc1f03b7c5a9175dbc6755f72f6f271a5bfaec806d","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":"2026-08-08T09:28:00.798775Z","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":"sha256:8fb91dd165d7614212a941c75e2c130a91f66412738d6f1d66194074bfbe17ec","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":"2026-08-08T09:28:00.798775Z","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":"sha256:46c71dfec51399881e98b6fbfd2b666550489e66918b46a30863e3f333c8d7dd","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":"2026-08-08T09:28:00.798775Z","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:bbc09d42e92d249152db84c8b516c2e85d598bd163b809fb4204c6431ec954bf","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":"2026-08-08T09:28:00.798775Z","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":"sha256:03c057eb406926fe36b02b19915ed17364c01080c45c976bf299322342737bbc","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":"2026-08-08T09:28:00.798775Z","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:eda67ba698c5abc048cf6e98f437335b82f5c2c60a9ed88488c518aef3486412","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":"2026-08-08T09:28:00.798775Z","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:f8ade6a7cb8fb9c189c86b95a5a5bbf2f0b7a6f35b597feaca85b517968ad30a","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":"2026-08-08T09:28:00.798775Z","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":"sha256:1d95eb59f7c466615114e23a72580883c23f5a8420bc6cbacac0e9edc3348400","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":"2026-08-08T09:28:00.798775Z","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:d94c1bd12a52096d0aa657cfae29d4ecb213cc40db77a1b0e4e0474d95232f5c","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":"2026-08-08T09:28:00.798775Z","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":"sha256:6b118e6688de596d1dd8335b43281660131dd14f38363b91ae12bb51f4fa85eb","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":"2026-08-08T09:28:00.798775Z","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":"sha256:6f5baaef716a70dacd327c6195e94ede084153ef20617f949ad2354bbf853d80","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":"2026-08-08T09:28:00.798775Z","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":"sha256:4f1139497e65a7d238fb203d7ff79046c76968dc1733d74f469aaab85c14ec23","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":"2026-08-08T09:28:00.798775Z","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:f62f2c0aa591568c28fed0589fd8069c99b4052487226f5eb8065b23b0846c11","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":"2026-08-08T09:28:00.798775Z","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:a68df4b8e9a007b7961ad0562d86204afd0a008a5c609cd8d9a0bedb3cfc3782","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":"2026-08-08T09:28:00.798775Z","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":"sha256:86e82c313337e132e0975b98a1fa2438421f7b53ed90123f53e95dff3a926186","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":"2026-08-08T09:28:00.798775Z","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":"sha256:84135d391778185c7996346925e324eb0178bdb3d9254295312622da4abbf82e","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":"2026-08-08T09:28:00.798775Z","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":"sha256:168af6247bc001eec6567140c7b00b0c54351467f4c7dedd3b7cd4860ff9ebca","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":"2026-08-08T09:28:00.798775Z","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":"sha256:4893bb3c529888df469a26a355d0e4fca36557f486960a07969b5cf05a37cd09","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":"2026-08-08T09:28:00.798775Z","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:e7b5dd31d950161c86de59a548b31abfcb15071177081ec850e08489a1e8d139","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":"2026-08-08T09:28:00.798775Z","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:a477f3b957ea5ab7719bb13614b874311dc7b1d281f9819b0c07cffe3c06d02a","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":"2026-08-08T09:28:00.798775Z","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":"sha256:3c2d78ac68c335437569bdd25cfc05cff8f7ffda1198f9294ccc5ba31ad372a9","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":"2026-08-08T09:28:00.798775Z","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":"sha256:729b92dc13521b74ac46109f201f86962c67af248c109cebc9e8345074d45408","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":"2026-08-08T09:28:00.798775Z","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:f3bdacd2d9ad984bf92cd5bf5dd7a6bbe6f221f61ffa8db634868f33ee60e2ae","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":"2026-08-08T09:28:00.798775Z","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."}