{"as_of":"2026-08-06T21:30:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:295c64b3c3509e1e31c8cd732214a4c34aec6e9a702d1d51b296ac72ec0cf3e6","coverage":[{"denominator":22,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":22,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-10T17:54:04.337239Z","state":"measured"},{"denominator":22,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":22,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-06T06:34:29.942622+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/2604.07286/citation-record","integrity":"/paper/2604.07286/integrity","json":"/paper/2604.07286/citation-record.json","paper":"/paper/2604.07286"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"What is the state of neural network pruning?","venue":null,"work_id":"edd865a5-1268-4284-a601-661f22d4fb01","year":2020},"citing_paper":{"arxiv_id":"2604.07286","last_updated":"2026-04-08T16:49:30Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-04-08T16:49:30Z","title":"CADENCE: Context-Adaptive Depth Estimation for Navigation and Computational Efficiency","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-10T17:54:04.337239Z"},"links":{"citing_paper":"/paper/2604.07286"},"observation_digest":"sha256:e853a5fc2e20066876dd076b2da17a00d74435f65cc39fcbf871cd8cced09682","observation_id":"5e708998-9684-4ac0-9a75-5d5bf73cc0be","resolution":{"observed_at":"2026-05-17T08:21:40.751997Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1503.02531","last_updated":"2015-03-09T15:44:49Z","snapshot_observed_at":"2026-07-06T04:11:24.157003Z","submitted_at":"2015-03-09T15:44:49Z","title":"Distilling the Knowledge in a Neural Network","version":1},"cited_work":{"arxiv_id":"1503.02531","doi":"10.1109/cvpr52733.2024.01515","metadata_source":"pith","pith_arxiv_id":"1503.02531","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Distilling the Knowledge in a Neural Network","venue":"stat.ML","work_id":"d927ab1f-17b8-4002-9d09-c3d55764fbad","year":2015},"citing_paper":{"arxiv_id":"2604.07286","last_updated":"2026-04-08T16:49:30Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-04-08T16:49:30Z","title":"CADENCE: Context-Adaptive Depth Estimation for Navigation and Computational Efficiency","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-10T17:54:04.337239Z"},"links":{"cited_paper":"/paper/1503.02531","citing_paper":"/paper/2604.07286"},"observation_digest":"sha256:ef836e524e6e6dd9b19ab028682e2de2dd14349aaf77b52e5dd500c1a27864e7","observation_id":"c7ddb3a6-6ef1-485a-8ea3-27f77892fe1d","resolution":{"observed_at":"2026-05-11T05:55:56.380393Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2206.07527","last_updated":"2022-06-24T13:02:01Z","snapshot_observed_at":"2026-07-06T13:21:05.911925Z","submitted_at":"2022-06-15T13:18:00Z","title":"QONNX: Representing Arbitrary-Precision Quantized Neural Networks","version":3},"cited_work":{"arxiv_id":"2206.07527","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2206.07527","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Qonnx: Repre- senting arbitrary-precision quantized neural networks","venue":null,"work_id":"4f860d55-6159-4cd3-a689-a2d66c963721","year":2022},"citing_paper":{"arxiv_id":"2604.07286","last_updated":"2026-04-08T16:49:30Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-04-08T16:49:30Z","title":"CADENCE: Context-Adaptive Depth Estimation for Navigation and Computational Efficiency","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-10T17:54:04.337239Z"},"links":{"cited_paper":"/paper/2206.07527","citing_paper":"/paper/2604.07286"},"observation_digest":"sha256:a59fe1fb644f77c702325dd3ee3fe43e9ac6ec6a9ae004d2c50cc621a626369f","observation_id":"c8042ffd-e06c-45af-bf1a-b6a15b4c3929","resolution":{"observed_at":"2026-05-11T05:55:56.391567Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Squeezenext: Hardware-aware neural network design","venue":null,"work_id":"4e1d3a9e-2a4b-4b98-9230-e58efba7dd7c","year":2018},"citing_paper":{"arxiv_id":"2604.07286","last_updated":"2026-04-08T16:49:30Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-04-08T16:49:30Z","title":"CADENCE: Context-Adaptive Depth Estimation for Navigation and Computational Efficiency","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-10T17:54:04.337239Z"},"links":{"citing_paper":"/paper/2604.07286"},"observation_digest":"sha256:b1996ca2d027f80df52544d1767633d37e03279a880328ee9e4138d0df95c79c","observation_id":"44e38800-9041-4d6f-903d-b0a08f6748f1","resolution":{"observed_at":"2026-05-17T08:21:40.754934Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Videoedge: Processing camera streams using hierarchical clusters","venue":null,"work_id":"5c567a3f-8b60-488c-acc2-a0807877e35b","year":2018},"citing_paper":{"arxiv_id":"2604.07286","last_updated":"2026-04-08T16:49:30Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-04-08T16:49:30Z","title":"CADENCE: Context-Adaptive Depth Estimation for Navigation and Computational Efficiency","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-10T17:54:04.337239Z"},"links":{"citing_paper":"/paper/2604.07286"},"observation_digest":"sha256:611f9d7aac47e88c42726260a1e4ce251d40b91e974924bf4973406f941f8c21","observation_id":"8918f046-8061-4470-9b64-4c877e989ec5","resolution":{"observed_at":"2026-05-17T08:21:40.748832Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"An overview of adaptive dynamic deep neural networks via slimmable and gated ar- chitectures","venue":null,"work_id":"795997c2-54fa-4fd5-bd13-67df5e8d21e7","year":2024},"citing_paper":{"arxiv_id":"2604.07286","last_updated":"2026-04-08T16:49:30Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-04-08T16:49:30Z","title":"CADENCE: Context-Adaptive Depth Estimation for Navigation and Computational Efficiency","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-10T17:54:04.337239Z"},"links":{"citing_paper":"/paper/2604.07286"},"observation_digest":"sha256:1dcda7876526878686e0ebc75c5a5d621fcb89ef9b49cc9e3f17c390da2409af","observation_id":"9a2b5b11-4a18-462f-b21a-10bc4b7e5c54","resolution":{"observed_at":"2026-05-17T08:21:40.713444Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Single-image real-time rain removal based on depth-guided non-local features","venue":null,"work_id":"30f390f9-cb20-411a-a89a-55ad025fa7ff","year":2021},"citing_paper":{"arxiv_id":"2604.07286","last_updated":"2026-04-08T16:49:30Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-04-08T16:49:30Z","title":"CADENCE: Context-Adaptive Depth Estimation for Navigation and Computational Efficiency","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-10T17:54:04.337239Z"},"links":{"citing_paper":"/paper/2604.07286"},"observation_digest":"sha256:6d6f8ba07c68ad23942a6894420a8a1d8f7bb2ac86d2d812db8d0ea9f619e5a0","observation_id":"786f5e6d-bce9-4466-8587-f52ba8368dc8","resolution":{"observed_at":"2026-05-17T08:21:40.709434Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Navislim: Adaptive context-aware navigation and sensing via dynamic slimmable networks","venue":null,"work_id":"b48fc533-b981-4c84-ac92-4dc0892b30fa","year":2024},"citing_paper":{"arxiv_id":"2604.07286","last_updated":"2026-04-08T16:49:30Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-04-08T16:49:30Z","title":"CADENCE: Context-Adaptive Depth Estimation for Navigation and Computational Efficiency","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-10T17:54:04.337239Z"},"links":{"citing_paper":"/paper/2604.07286"},"observation_digest":"sha256:c60bc23a459738249a63b7889533c634362050ff73acab9907b490c332dffc63","observation_id":"89cd29a5-b54f-4327-ac0f-1b97a9124e06","resolution":{"observed_at":"2026-05-17T08:21:40.720933Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Airsim: High-fidelity visual and physical simulation for autonomous vehicles","venue":null,"work_id":"deacd37d-00b9-4d61-bb7a-f79914a2c908","year":2018},"citing_paper":{"arxiv_id":"2604.07286","last_updated":"2026-04-08T16:49:30Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-04-08T16:49:30Z","title":"CADENCE: Context-Adaptive Depth Estimation for Navigation and Computational Efficiency","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-10T17:54:04.337239Z"},"links":{"citing_paper":"/paper/2604.07286"},"observation_digest":"sha256:805ef13eed006c2f8ae84bc4a4a1624246e047f9000f9db9c8eb920766bd5d3e","observation_id":"a2fc3e1d-fb32-4bad-8478-56a67e882ffe","resolution":{"observed_at":"2026-05-17T08:21:40.739249Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Representation learning for event-based visuomotor policies","venue":null,"work_id":"c38fa8c5-3120-444c-ad6c-e07a0214659c","year":2021},"citing_paper":{"arxiv_id":"2604.07286","last_updated":"2026-04-08T16:49:30Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-04-08T16:49:30Z","title":"CADENCE: Context-Adaptive Depth Estimation for Navigation and Computational Efficiency","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-10T17:54:04.337239Z"},"links":{"citing_paper":"/paper/2604.07286"},"observation_digest":"sha256:b72684168fdd7b087e10734b2456830e36b240b9c3ae4385985014c125d54f5e","observation_id":"84c995a4-76c7-4b3a-8250-4730d07349b2","resolution":{"observed_at":"2026-05-17T08:21:40.717231Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Split computing and early exiting for deep learning applications: Survey and research challenges","venue":null,"work_id":"7ca1de45-6c43-4b9d-80d6-80dec2f0393c","year":2022},"citing_paper":{"arxiv_id":"2604.07286","last_updated":"2026-04-08T16:49:30Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-04-08T16:49:30Z","title":"CADENCE: Context-Adaptive Depth Estimation for Navigation and Computational Efficiency","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-10T17:54:04.337239Z"},"links":{"citing_paper":"/paper/2604.07286"},"observation_digest":"sha256:75b331351bccb667664c4c56d2d5fd796ebd1879fb9d9fa87ae38e305ce9f2a8","observation_id":"9c4c6a7b-66f5-4765-a5c4-548f25598ca3","resolution":{"observed_at":"2026-05-17T08:21:40.728779Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1812.08928","last_updated":"2018-12-21T03:36:48Z","snapshot_observed_at":"2026-08-02T06:18:15.521345Z","submitted_at":"2018-12-21T03:36:48Z","title":"Slimmable Neural Networks","version":1},"cited_work":{"arxiv_id":"1812.08928","doi":null,"metadata_source":"pith","pith_arxiv_id":"1812.08928","snapshot_observed_at":"2026-06-28T19:32:34.818109Z","title":"Slimmable Neural Networks","venue":"cs.CV","work_id":"823e73f8-1c8a-4ee9-bbef-19e3369c5223","year":2018},"citing_paper":{"arxiv_id":"2604.07286","last_updated":"2026-04-08T16:49:30Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-04-08T16:49:30Z","title":"CADENCE: Context-Adaptive Depth Estimation for Navigation and Computational Efficiency","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-10T17:54:04.337239Z"},"links":{"cited_paper":"/paper/1812.08928","citing_paper":"/paper/2604.07286"},"observation_digest":"sha256:a2f052f31018d3dbec01ea7b3b1931e3a459611ddcc95e77ea16355cd76d35c2","observation_id":"49ba37f6-e467-4426-ac32-1233bb365756","resolution":{"observed_at":"2026-05-11T05:55:56.399467Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Hydrafu- sion: Context-aware selective sensor fusion for robust and efficient autonomous vehicle perception","venue":null,"work_id":"71327269-ad0e-4c0b-8fb5-1b1d265f3d6d","year":2022},"citing_paper":{"arxiv_id":"2604.07286","last_updated":"2026-04-08T16:49:30Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-04-08T16:49:30Z","title":"CADENCE: Context-Adaptive Depth Estimation for Navigation and Computational Efficiency","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-10T17:54:04.337239Z"},"links":{"citing_paper":"/paper/2604.07286"},"observation_digest":"sha256:48781dcb18905a672f3d3a80e5ab2fba73340c9f1e2bec65aa12e84c5caf4065","observation_id":"8a43ac18-b00e-4c33-94ca-b63fba69bd1e","resolution":{"observed_at":"2026-05-17T08:21:40.735809Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Testudo: Col- laborative intelligence for latency-critical autonomous systems","venue":null,"work_id":"34976144-4325-4391-8d82-b367bc709dca","year":2022},"citing_paper":{"arxiv_id":"2604.07286","last_updated":"2026-04-08T16:49:30Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-04-08T16:49:30Z","title":"CADENCE: Context-Adaptive Depth Estimation for Navigation and Computational Efficiency","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-10T17:54:04.337239Z"},"links":{"citing_paper":"/paper/2604.07286"},"observation_digest":"sha256:8a7e1a59c20687b16e79170cf2f0df2f97a50f928a635c4f42246b2df3f8480f","observation_id":"0cea474b-352e-44f6-82b7-88a76d1dedf8","resolution":{"observed_at":"2026-05-17T08:21:40.745392Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Dynamic slimmable denoising network","venue":null,"work_id":"7d674c08-2117-4d61-98e2-a8eeec65c121","year":2023},"citing_paper":{"arxiv_id":"2604.07286","last_updated":"2026-04-08T16:49:30Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-04-08T16:49:30Z","title":"CADENCE: Context-Adaptive Depth Estimation for Navigation and Computational Efficiency","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-10T17:54:04.337239Z"},"links":{"citing_paper":"/paper/2604.07286"},"observation_digest":"sha256:515748f8e118560c92a35a2c50fa44405b20cdba5a6db3a61d319ae727559c24","observation_id":"3bc12a04-d7b7-404c-9b65-9784adc3fe64","resolution":{"observed_at":"2026-05-17T08:21:40.701517Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Repmono: a lightweight self-supervised monocular depth estimation architecture for high-speed inference","venue":null,"work_id":"06d42a70-0299-47fd-a96d-34ce0de286a7","year":2024},"citing_paper":{"arxiv_id":"2604.07286","last_updated":"2026-04-08T16:49:30Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-04-08T16:49:30Z","title":"CADENCE: Context-Adaptive Depth Estimation for Navigation and Computational Efficiency","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-10T17:54:04.337239Z"},"links":{"citing_paper":"/paper/2604.07286"},"observation_digest":"sha256:de5be153a1e13cfa0fd6743245b9c3d049b60b588480ecea389b57ebe8c47de0","observation_id":"795774ec-d5f4-4169-b514-3f6bd6874510","resolution":{"observed_at":"2026-05-17T08:21:40.691234Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Improving accuracy and efficiency of monocular depth estimation in power grid environments using point cloud optimization and knowledge distillation","venue":null,"work_id":"38bc62de-05be-4d69-b162-e869e91c223f","year":2024},"citing_paper":{"arxiv_id":"2604.07286","last_updated":"2026-04-08T16:49:30Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-04-08T16:49:30Z","title":"CADENCE: Context-Adaptive Depth Estimation for Navigation and Computational Efficiency","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-10T17:54:04.337239Z"},"links":{"citing_paper":"/paper/2604.07286"},"observation_digest":"sha256:8e38eccaca27928ff13e8b5aa7458f0a91ed84b6dcbd623c4134a2ff5e3041cb","observation_id":"1c4eef94-4fb3-4d00-b758-952e16fbad71","resolution":{"observed_at":"2026-05-17T08:21:40.705113Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Navisplit: Dynamic multi-branch split dnns for efficient distributed autonomous navigation","venue":null,"work_id":"5d253c9a-cc29-4bea-abc1-d85b8865ba58","year":2024},"citing_paper":{"arxiv_id":"2604.07286","last_updated":"2026-04-08T16:49:30Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-04-08T16:49:30Z","title":"CADENCE: Context-Adaptive Depth Estimation for Navigation and Computational Efficiency","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-10T17:54:04.337239Z"},"links":{"citing_paper":"/paper/2604.07286"},"observation_digest":"sha256:e0ebd8aa778ac0722541a4ddb39ab4a03351c6ea8d8468fa3928389ec104ca76","observation_id":"1dbb82dc-501c-436f-9383-b89bd948484a","resolution":{"observed_at":"2026-05-17T08:21:40.742363Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Energy-quality scalable monocular depth estimation on low-power cpus","venue":null,"work_id":"9607f3be-8df4-4313-8958-fd35fc50c1b1","year":2021},"citing_paper":{"arxiv_id":"2604.07286","last_updated":"2026-04-08T16:49:30Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-04-08T16:49:30Z","title":"CADENCE: Context-Adaptive Depth Estimation for Navigation and Computational Efficiency","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-10T17:54:04.337239Z"},"links":{"citing_paper":"/paper/2604.07286"},"observation_digest":"sha256:14f84c029372839c09b2d4c172878235085a9226155de65e7e71ca5629968295","observation_id":"e4e1b278-59c4-47d1-8e40-fd4903655ddd","resolution":{"observed_at":"2026-05-17T08:21:40.693729Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-06T21:42:56.665699Z","title":"Human-level control through deep reinforcement learning","venue":null,"work_id":"3c7dd272-8c5d-423e-b9ea-34518c6babf6","year":2015},"citing_paper":{"arxiv_id":"2604.07286","last_updated":"2026-04-08T16:49:30Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-04-08T16:49:30Z","title":"CADENCE: Context-Adaptive Depth Estimation for Navigation and Computational Efficiency","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-10T17:54:04.337239Z"},"links":{"citing_paper":"/paper/2604.07286"},"observation_digest":"sha256:5c60b6212cde70536971d715ba12ec9cdf8bdad69bc63920ba7bb829a666cf12","observation_id":"155e7b3e-3e20-43e0-aac1-989fc52b6b29","resolution":{"observed_at":"2026-05-17T08:21:40.697116Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Deep reinforcement learning with double q-learning","venue":null,"work_id":"f5fd7884-0658-46ad-af6e-22a73d92b378","year":2016},"citing_paper":{"arxiv_id":"2604.07286","last_updated":"2026-04-08T16:49:30Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-04-08T16:49:30Z","title":"CADENCE: Context-Adaptive Depth Estimation for Navigation and Computational Efficiency","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-10T17:54:04.337239Z"},"links":{"citing_paper":"/paper/2604.07286"},"observation_digest":"sha256:cdb393ee097a1fce1c76debc9fddb9271dcdca326e7a2d85ecfa670cd9c60253","observation_id":"04db3107-b917-4abf-b5da-f05f2f21c389","resolution":{"observed_at":"2026-05-17T08:21:40.732062Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T02:40:38.322266Z","title":"A formal basis for the heuristic determination of minimum cost paths","venue":null,"work_id":"94003d76-6ef5-4f88-b7a0-29e231445fb0","year":1968},"citing_paper":{"arxiv_id":"2604.07286","last_updated":"2026-04-08T16:49:30Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-04-08T16:49:30Z","title":"CADENCE: Context-Adaptive Depth Estimation for Navigation and Computational Efficiency","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-10T17:54:04.337239Z"},"links":{"citing_paper":"/paper/2604.07286"},"observation_digest":"sha256:9d66306167fe23fdb6045d0b69675879641c9fa3ff34e109876303308c29e945","observation_id":"8a388ba8-f03e-441f-be36-70649e2c66a5","resolution":{"observed_at":"2026-05-17T08:21:40.725026Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2604.07286","last_updated":"2026-04-08T16:49:30Z","latest_version":1,"primary_category":"cs.RO","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-04-08T16:49:30Z","title":"CADENCE: Context-Adaptive Depth Estimation for Navigation and Computational Efficiency"},"reference_resolution":{"displayed":22,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":3,"verified_fuzzy":19},"total_outbound_references":22},"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":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"thesis":"As of 6 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2604.07286."}