{"as_of":"2026-08-16T03:48:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:b1dd705748300e1492a67d1a9a648cb0b75da2cdf7578c2d9f9d6394acfc685c","coverage":[{"denominator":12,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":12,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T21:46:23.630488Z","state":"measured"},{"denominator":12,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":12,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-15T06:32:42.880941+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/2501.04141/citation-record","integrity":"/paper/2501.04141/integrity","json":"/paper/2501.04141/citation-record.json","paper":"/paper/2501.04141"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:46:23.855608Z","title":"Photonics for artificial intelligence and neuromorphic computing","venue":null,"work_id":"f73e8f7a-2044-4e59-90b7-4aaa214d3e2a","year":2021},"citing_paper":{"arxiv_id":"2501.04141","last_updated":"2025-01-07T21:09:16Z","snapshot_observed_at":"2026-08-16T01:39:42.688006Z","submitted_at":"2025-01-07T21:09:16Z","title":"Hardware-In-The-Loop Training of a 4f Optical Correlator with Logarithmic Complexity Reduction for CNNs","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-10T21:46:23.575833Z"},"links":{"citing_paper":"/paper/2501.04141"},"observation_digest":"sha256:a859260ff3f7e4ba0bc5964ebdb23f5ee914f0ce3b66e45452b3bd096388a4dd","observation_id":"54efe714-d7f3-4820-9bb8-c95e0eb2a6f1","resolution":{"observed_at":"2026-08-10T21:46:23.861944Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-10T21:46:23.837014Z","title":"Massively parallel amplitude-only fourier neural network","venue":null,"work_id":"ceb92ea1-e2ba-47de-9eb7-75d94d988d70","year":2020},"citing_paper":{"arxiv_id":"2501.04141","last_updated":"2025-01-07T21:09:16Z","snapshot_observed_at":"2026-08-16T01:39:42.688006Z","submitted_at":"2025-01-07T21:09:16Z","title":"Hardware-In-The-Loop Training of a 4f Optical Correlator with Logarithmic Complexity Reduction for CNNs","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-10T21:46:23.580690Z"},"links":{"citing_paper":"/paper/2501.04141"},"observation_digest":"sha256:ca9558403105c52299f3c39f0b7444bc0025908620b0f89e57def0fd6504ae86","observation_id":"0c1dcae4-20d9-4dfc-9ae8-0137e15e123e","resolution":{"observed_at":"2026-08-10T21:46:23.843902Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-10T21:46:23.819344Z","title":"Hybrid training of optical neural networks","venue":null,"work_id":"87b126c2-f35a-4fd4-9109-b626acdefda3","year":2022},"citing_paper":{"arxiv_id":"2501.04141","last_updated":"2025-01-07T21:09:16Z","snapshot_observed_at":"2026-08-16T01:39:42.688006Z","submitted_at":"2025-01-07T21:09:16Z","title":"Hardware-In-The-Loop Training of a 4f Optical Correlator with Logarithmic Complexity Reduction for CNNs","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-10T21:46:23.585522Z"},"links":{"citing_paper":"/paper/2501.04141"},"observation_digest":"sha256:12d05a61cfe5d913cc28fb34a03cba599ef854510548a653270908e96078e90c","observation_id":"f6ea0351-e6be-4fa9-8044-858587954065","resolution":{"observed_at":"2026-08-10T21:46:23.825103Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-10T21:46:23.798603Z","title":"Signal propagation: The framework for learning and inference in a forward pass","venue":null,"work_id":"17176944-85de-4519-a5b2-228fb505e3ad","year":2023},"citing_paper":{"arxiv_id":"2501.04141","last_updated":"2025-01-07T21:09:16Z","snapshot_observed_at":"2026-08-16T01:39:42.688006Z","submitted_at":"2025-01-07T21:09:16Z","title":"Hardware-In-The-Loop Training of a 4f Optical Correlator with Logarithmic Complexity Reduction for CNNs","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-10T21:46:23.590554Z"},"links":{"citing_paper":"/paper/2501.04141"},"observation_digest":"sha256:178e60205b3add09ebdb21959d40c9adb18a628cacfe9fa1624659eaf0cdb4c5","observation_id":"5fcfcf35-6e5c-4be4-b181-74d41296db5e","resolution":{"observed_at":"2026-08-10T21:46:23.806445Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2212.13345","last_updated":"2022-12-27T02:54:46Z","snapshot_observed_at":"2026-08-13T13:14:04.763006Z","submitted_at":"2022-12-27T02:54:46Z","title":"The Forward-Forward Algorithm: Some Preliminary Investigations","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2212.13345","snapshot_observed_at":"2026-08-10T21:46:23.595642Z","title":"The forward-forward algorithm: Some preliminary investigations","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.04141","last_updated":"2025-01-07T21:09:16Z","snapshot_observed_at":"2026-08-16T01:39:42.688006Z","submitted_at":"2025-01-07T21:09:16Z","title":"Hardware-In-The-Loop Training of a 4f Optical Correlator with Logarithmic Complexity Reduction for CNNs","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-10T21:46:23.595642Z"},"links":{"cited_paper":"/paper/2212.13345","citing_paper":"/paper/2501.04141"},"observation_digest":"sha256:86211b66b3534ee91d7fbf32f2d799a039f0f49393eabec52cd22d6aa677fc30","observation_id":"eea5b510-b9db-4431-bebb-280bf835d18a","resolution":{"observed_at":"2026-08-10T21:46:23.595642Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:46:23.777538Z","title":"Error-driven input modulation: Solving the credit assignment problem without a backward pass","venue":null,"work_id":"070911a3-e56a-4847-b522-9445770cad1a","year":2022},"citing_paper":{"arxiv_id":"2501.04141","last_updated":"2025-01-07T21:09:16Z","snapshot_observed_at":"2026-08-16T01:39:42.688006Z","submitted_at":"2025-01-07T21:09:16Z","title":"Hardware-In-The-Loop Training of a 4f Optical Correlator with Logarithmic Complexity Reduction for CNNs","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-10T21:46:23.600901Z"},"links":{"citing_paper":"/paper/2501.04141"},"observation_digest":"sha256:e525ccafb9cd4fe3c2e6713f6add652f6d9b9d88b2f49dcfbc7f3c00dfc0f9d3","observation_id":"34ace6c6-4291-40a5-a51c-7a26607900ca","resolution":{"observed_at":"2026-08-10T21:46:23.784775Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-10T21:46:23.757724Z","title":"Suitability of forward-forward and pepita learning to mlcommons-tiny benchmarks","venue":null,"work_id":"649d85ea-cbff-4d24-bc04-5aae1bdb07da","year":2023},"citing_paper":{"arxiv_id":"2501.04141","last_updated":"2025-01-07T21:09:16Z","snapshot_observed_at":"2026-08-16T01:39:42.688006Z","submitted_at":"2025-01-07T21:09:16Z","title":"Hardware-In-The-Loop Training of a 4f Optical Correlator with Logarithmic Complexity Reduction for CNNs","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-10T21:46:23.606471Z"},"links":{"citing_paper":"/paper/2501.04141"},"observation_digest":"sha256:404b473d91232f012318c86b3a4e935f3eb0b14ff79916619c0f6402f2d4b020","observation_id":"157cbeb2-fdb9-40b7-a089-01a249eae8cb","resolution":{"observed_at":"2026-08-10T21:46:23.765227Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-10T21:46:23.737227Z","title":"Fully forward mode training for optical neural networks","venue":null,"work_id":"836da94f-7bbc-4cc4-af4a-d96b9c97875c","year":2024},"citing_paper":{"arxiv_id":"2501.04141","last_updated":"2025-01-07T21:09:16Z","snapshot_observed_at":"2026-08-16T01:39:42.688006Z","submitted_at":"2025-01-07T21:09:16Z","title":"Hardware-In-The-Loop Training of a 4f Optical Correlator with Logarithmic Complexity Reduction for CNNs","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-10T21:46:23.611094Z"},"links":{"citing_paper":"/paper/2501.04141"},"observation_digest":"sha256:42596a7b2433f9e8b277d5551d4bdab77027ec63557ccd944fd77452fb6e8fbc","observation_id":"057a76f9-2f5d-4b1c-9ee4-5e5e118e3c71","resolution":{"observed_at":"2026-08-10T21:46:23.744288Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-10T21:46:23.719319Z","title":"Forward--forward training of an optical neural network","venue":null,"work_id":"9a67af8c-aa1c-47ff-a42d-9d1d093921a5","year":2023},"citing_paper":{"arxiv_id":"2501.04141","last_updated":"2025-01-07T21:09:16Z","snapshot_observed_at":"2026-08-16T01:39:42.688006Z","submitted_at":"2025-01-07T21:09:16Z","title":"Hardware-In-The-Loop Training of a 4f Optical Correlator with Logarithmic Complexity Reduction for CNNs","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-10T21:46:23.615828Z"},"links":{"citing_paper":"/paper/2501.04141"},"observation_digest":"sha256:5097ac8d38dff8901527102b616bf8da8083143d940b0a168ca7ac5c19b40144","observation_id":"91c1c419-cec3-4231-a916-315cfc81ae0f","resolution":{"observed_at":"2026-08-10T21:46:23.725332Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-10T21:46:23.699651Z","title":"Backpropagation-free training of deep physical neural networks","venue":null,"work_id":"22ce76ad-31e2-45fd-88b3-29f4e67fe321","year":2023},"citing_paper":{"arxiv_id":"2501.04141","last_updated":"2025-01-07T21:09:16Z","snapshot_observed_at":"2026-08-16T01:39:42.688006Z","submitted_at":"2025-01-07T21:09:16Z","title":"Hardware-In-The-Loop Training of a 4f Optical Correlator with Logarithmic Complexity Reduction for CNNs","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-10T21:46:23.620513Z"},"links":{"citing_paper":"/paper/2501.04141"},"observation_digest":"sha256:42e3d0f7532575162e6b65e9335287074ad0b2fa9883273856dfed3c29b84139","observation_id":"fc6a684d-a6c3-4f18-8ce8-ddc73501e714","resolution":{"observed_at":"2026-08-10T21:46:23.707347Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-10T21:46:23.625309Z","title":", \" * write output.state after.block = add.period write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2501.04141","last_updated":"2025-01-07T21:09:16Z","snapshot_observed_at":"2026-08-16T01:39:42.688006Z","submitted_at":"2025-01-07T21:09:16Z","title":"Hardware-In-The-Loop Training of a 4f Optical Correlator with Logarithmic Complexity Reduction for CNNs","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-10T21:46:23.625309Z"},"links":{"citing_paper":"/paper/2501.04141"},"observation_digest":"sha256:e80610493e41dd112f333e36157869ca0eccfc48cdaa028c0fdde14028726d6d","observation_id":"9c025320-19fb-439b-94f1-54ba446a2624","resolution":{"observed_at":"2026-08-10T21:46:23.625309Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:46:23.630488Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2501.04141","last_updated":"2025-01-07T21:09:16Z","snapshot_observed_at":"2026-08-16T01:39:42.688006Z","submitted_at":"2025-01-07T21:09:16Z","title":"Hardware-In-The-Loop Training of a 4f Optical Correlator with Logarithmic Complexity Reduction for CNNs","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-10T21:46:23.630488Z"},"links":{"citing_paper":"/paper/2501.04141"},"observation_digest":"sha256:0fb464303b7f3d00ec7eb175e92714159d6ac968c290336538b504084790e02c","observation_id":"a8d59878-688c-4ae0-ad70-abe1c51689a6","resolution":{"observed_at":"2026-08-10T21:46:23.630488Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2501.04141","last_updated":"2025-01-07T21:09:16Z","latest_version":1,"primary_category":"cs.NE","snapshot_observed_at":"2026-08-16T01:39:42.688006Z","submitted_at":"2025-01-07T21:09:16Z","title":"Hardware-In-The-Loop Training of a 4f Optical Correlator with Logarithmic Complexity Reduction for CNNs"},"reference_resolution":{"displayed":12,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":3,"verified_exact":0,"verified_fuzzy":9},"total_outbound_references":12},"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":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 0 inbound Pith citation observations for arXiv:2501.04141."}