{"as_of":"2026-08-10T16:37:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:ac39dcd05c09c4c6c5e5bfa92e0fac0e17dcee272a481b9e66a3f1a680e457b3","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":23,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":23,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":23,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":23,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T15:09:51.386022Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-04T13:19:50.534492Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1605.04711","last_updated":"2022-11-20T14:21:55Z","snapshot_observed_at":"2026-07-06T04:56:23.954139Z","submitted_at":"2016-05-16T10:21:25Z","title":"Ternary Weight Networks","version":3},"cited_work":{"arxiv_id":"1605.04711","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1605.04711","snapshot_observed_at":"2026-07-04T13:19:50.534492Z","title":"Ternary weight networks","venue":null,"work_id":"0648c619-efa7-4e61-891b-d0706e11f803","year":2016},"citing_paper":{"arxiv_id":"1609.08144","last_updated":"2016-10-08T19:10:41Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2016-09-26T19:59:55Z","title":"Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-05-12T15:21:28.893842Z"},"links":{"cited_paper":"/paper/1605.04711","citing_paper":"/paper/1609.08144"},"observation_digest":"sha256:fb517fa5920e81b9081db4818f3e42b5130bf9f6e446e769aaedbc1450a51c05","observation_id":"e79354ed-e6a9-43f4-9fa3-4a5c2549b874","resolution":{"observed_at":"2026-05-12T15:21:28.922526Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1605.04711","last_updated":"2022-11-20T14:21:55Z","snapshot_observed_at":"2026-07-06T04:56:23.954139Z","submitted_at":"2016-05-16T10:21:25Z","title":"Ternary Weight Networks","version":3},"cited_work":{"arxiv_id":"1605.04711","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1605.04711","snapshot_observed_at":"2026-07-04T13:19:50.534492Z","title":"Ternary weight networks","venue":null,"work_id":"0648c619-efa7-4e61-891b-d0706e11f803","year":2016},"citing_paper":{"arxiv_id":"1907.00593","last_updated":"2019-07-01T07:59:39Z","snapshot_observed_at":"2026-07-06T08:03:58.999596Z","submitted_at":"2019-07-01T07:59:39Z","title":"Weight Normalization based Quantization for Deep Neural Network Compression","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-25T11:45:08.973181Z"},"links":{"cited_paper":"/paper/1605.04711","citing_paper":"/paper/1907.00593"},"observation_digest":"sha256:ec174f7f99c662eeefba9c9f49b8ac2968f38bf84e4f4b5c4192152793b5dca2","observation_id":"997c3b96-bfaa-411d-bdcf-90fc31b2fa67","resolution":{"observed_at":"2026-05-25T11:45:45.056664Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1605.04711","last_updated":"2022-11-20T14:21:55Z","snapshot_observed_at":"2026-07-06T04:56:23.954139Z","submitted_at":"2016-05-16T10:21:25Z","title":"Ternary Weight Networks","version":3},"cited_work":{"arxiv_id":"1605.04711","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1605.04711","snapshot_observed_at":"2026-07-04T13:19:50.534492Z","title":"Ternary weight networks","venue":null,"work_id":"0648c619-efa7-4e61-891b-d0706e11f803","year":2016},"citing_paper":{"arxiv_id":"1907.07220","last_updated":"2019-07-16T19:11:01Z","snapshot_observed_at":"2026-07-06T08:08:08.790847Z","submitted_at":"2019-07-16T19:11:01Z","title":"Learning Multimodal Fixed-Point Weights using Gradient Descent","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-24T20:50:37.401966Z"},"links":{"cited_paper":"/paper/1605.04711","citing_paper":"/paper/1907.07220"},"observation_digest":"sha256:5316861fc4b0a75749054fe8cfff16e9bb09feb23dfa3ec06dd20e0db201e133","observation_id":"fbc0a9f7-dc55-4deb-b08c-36662cae542a","resolution":{"observed_at":"2026-05-24T20:54:54.723909Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1605.04711","last_updated":"2022-11-20T14:21:55Z","snapshot_observed_at":"2026-07-06T04:56:23.954139Z","submitted_at":"2016-05-16T10:21:25Z","title":"Ternary Weight Networks","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1605.04711","snapshot_observed_at":"2026-08-10T15:09:51.386022Z","title":"Ternary weight networks,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2501.14495","last_updated":"2025-01-24T13:51:47Z","snapshot_observed_at":"2026-08-10T15:03:49.702090Z","submitted_at":"2025-01-24T13:51:47Z","title":"BILLNET: A Binarized Conv3D-LSTM Network with Logic-gated residual architecture for hardware-efficient video inference","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-10T15:09:51.386022Z"},"links":{"cited_paper":"/paper/1605.04711","citing_paper":"/paper/2501.14495"},"observation_digest":"sha256:641428e146f0bb3eda80aefe78124ff951b951d1cac2ac9b1f8697b782b48b34","observation_id":"1c82684e-8196-4fac-af12-57e983e43e56","resolution":{"observed_at":"2026-08-10T15:09:51.386022Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1605.04711","last_updated":"2022-11-20T14:21:55Z","snapshot_observed_at":"2026-07-06T04:56:23.954139Z","submitted_at":"2016-05-16T10:21:25Z","title":"Ternary Weight Networks","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1605.04711","snapshot_observed_at":"2026-08-07T19:04:45.624168Z","title":null,"venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2502.10216","last_updated":"2025-08-12T07:34:30Z","snapshot_observed_at":"2026-08-08T07:46:40.733541Z","submitted_at":"2025-02-14T15:10:43Z","title":"Forget the Data and Fine-Tuning! Just Fold the Network to Compress","version":2},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-08-07T19:04:45.624168Z"},"links":{"cited_paper":"/paper/1605.04711","citing_paper":"/paper/2502.10216"},"observation_digest":"sha256:142d1a39b4428ccd3587a83ddf59185cc5f3043255c68864fd6cb56f0297c1a2","observation_id":"da936086-d311-4845-81c0-cedf217746c0","resolution":{"observed_at":"2026-08-07T19:04:45.624168Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1605.04711","last_updated":"2022-11-20T14:21:55Z","snapshot_observed_at":"2026-07-06T04:56:23.954139Z","submitted_at":"2016-05-16T10:21:25Z","title":"Ternary Weight Networks","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1605.04711","snapshot_observed_at":"2026-08-07T15:43:04.335248Z","title":"arXiv preprint arXiv:1605.04711 (2016)","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2505.14303","last_updated":"2026-07-15T16:03:28Z","snapshot_observed_at":"2026-08-07T15:34:41.909989Z","submitted_at":"2025-05-20T12:54:48Z","title":"Optimizing Binary and Ternary Neural Network Inference on RRAM Crossbars using CIM-Explorer","version":3},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T15:43:04.335248Z"},"links":{"cited_paper":"/paper/1605.04711","citing_paper":"/paper/2505.14303"},"observation_digest":"sha256:362d652a36fc6229e4f3f1bb91e133099c2fe137258618dba68f31c56544b797","observation_id":"f4f21833-47cd-41d5-816f-a411ca08ccc7","resolution":{"observed_at":"2026-08-07T15:43:04.335248Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1605.04711","last_updated":"2022-11-20T14:21:55Z","snapshot_observed_at":"2026-07-06T04:56:23.954139Z","submitted_at":"2016-05-16T10:21:25Z","title":"Ternary Weight Networks","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1605.04711","snapshot_observed_at":"2026-08-06T16:09:08.001032Z","title":null,"venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2507.14481","last_updated":"2025-07-19T04:32:04Z","snapshot_observed_at":"2026-08-09T01:41:09.088488Z","submitted_at":"2025-07-19T04:32:04Z","title":"DFQ-ViT: Data-Free Quantization for Vision Transformers without Fine-tuning","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:08.001032Z"},"links":{"cited_paper":"/paper/1605.04711","citing_paper":"/paper/2507.14481"},"observation_digest":"sha256:f197ffc3fa122cf68421d358538b4bb97781604b0fb4d899a340bee5cc6465f4","observation_id":"6da3d452-503b-4e7f-b8ab-a0e78515e32c","resolution":{"observed_at":"2026-08-06T16:09:08.001032Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1605.04711","last_updated":"2022-11-20T14:21:55Z","snapshot_observed_at":"2026-07-06T04:56:23.954139Z","submitted_at":"2016-05-16T10:21:25Z","title":"Ternary Weight Networks","version":3},"cited_work":{"arxiv_id":"1605.04711","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1605.04711","snapshot_observed_at":"2026-07-04T13:19:50.534492Z","title":"Ternary weight networks","venue":null,"work_id":"0648c619-efa7-4e61-891b-d0706e11f803","year":2016},"citing_paper":{"arxiv_id":"2507.16079","last_updated":"2026-04-25T14:40:47Z","snapshot_observed_at":"2026-08-03T02:40:20.493603Z","submitted_at":"2025-07-21T21:29:33Z","title":"A Lower Bound for the Number of Linear Regions of Ternary ReLU Regression Neural Networks","version":2},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-05-19T03:27:12.956489Z"},"links":{"cited_paper":"/paper/1605.04711","citing_paper":"/paper/2507.16079"},"observation_digest":"sha256:8f48a886c343fa995e76bfcf6961a629f077707619b5038c927c23afda09cf60","observation_id":"dffe1159-20b7-4089-bdc3-aae1db301e08","resolution":{"observed_at":"2026-05-19T03:32:01.758364Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1605.04711","last_updated":"2022-11-20T14:21:55Z","snapshot_observed_at":"2026-07-06T04:56:23.954139Z","submitted_at":"2016-05-16T10:21:25Z","title":"Ternary Weight Networks","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1605.04711","snapshot_observed_at":"2026-08-05T14:11:15.494158Z","title":"Ternary weight networks","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2509.00133","last_updated":"2025-08-29T14:17:05Z","snapshot_observed_at":"2026-08-08T20:41:35.689089Z","submitted_at":"2025-08-29T14:17:05Z","title":"Latent-Space Mean-Field Theory for Deep BitNet-like Training: Constrained Gradient Flows with Smooth Quantization and STE Limits","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-05T14:11:15.494158Z"},"links":{"cited_paper":"/paper/1605.04711","citing_paper":"/paper/2509.00133"},"observation_digest":"sha256:e7b9b118fe0efea87b67462d9ff31dc095c1a8f55d14c1365cdf769012a663d3","observation_id":"bdba1c5e-aef7-421a-94e0-e4d71cfe5e8a","resolution":{"observed_at":"2026-08-05T14:11:15.494158Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1605.04711","last_updated":"2022-11-20T14:21:55Z","snapshot_observed_at":"2026-07-06T04:56:23.954139Z","submitted_at":"2016-05-16T10:21:25Z","title":"Ternary Weight Networks","version":3},"cited_work":{"arxiv_id":"1605.04711","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1605.04711","snapshot_observed_at":"2026-07-04T13:19:50.534492Z","title":"Ternary weight networks","venue":null,"work_id":"0648c619-efa7-4e61-891b-d0706e11f803","year":2016},"citing_paper":{"arxiv_id":"2604.08474","last_updated":"2026-04-09T17:13:15Z","snapshot_observed_at":"2026-08-03T02:08:49.186412Z","submitted_at":"2026-04-09T17:13:15Z","title":"Quantization Impact on the Accuracy and Communication Efficiency Trade-off in Federated Learning for Aerospace Predictive Maintenance","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-10T18:07:39.340273Z"},"links":{"cited_paper":"/paper/1605.04711","citing_paper":"/paper/2604.08474"},"observation_digest":"sha256:4deaf95507ff7ac520fbaaecb55b7418fb6e39563b06073d9284e436e91a9d19","observation_id":"e5c95b08-1749-4acc-bfa5-2143be40776e","resolution":{"observed_at":"2026-05-11T05:26:02.217795Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1605.04711","last_updated":"2022-11-20T14:21:55Z","snapshot_observed_at":"2026-07-06T04:56:23.954139Z","submitted_at":"2016-05-16T10:21:25Z","title":"Ternary Weight Networks","version":3},"cited_work":{"arxiv_id":"1605.04711","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1605.04711","snapshot_observed_at":"2026-07-04T13:19:50.534492Z","title":"Ternary weight networks","venue":null,"work_id":"0648c619-efa7-4e61-891b-d0706e11f803","year":2016},"citing_paper":{"arxiv_id":"2604.20913","last_updated":"2026-04-22T02:42:10Z","snapshot_observed_at":"2026-07-06T23:07:36.996629Z","submitted_at":"2026-04-22T02:42:10Z","title":"FairyFuse: Multiplication-Free LLM Inference on CPUs via Fused Ternary Kernels","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-10T01:15:51.105340Z"},"links":{"cited_paper":"/paper/1605.04711","citing_paper":"/paper/2604.20913"},"observation_digest":"sha256:a3f018da844efdad14935581bf059558036cd597b10abbf40dfeafd411c08b1f","observation_id":"13e41782-e43c-4066-bfa2-eefc3f3e6606","resolution":{"observed_at":"2026-05-11T13:41:04.747151Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1605.04711","last_updated":"2022-11-20T14:21:55Z","snapshot_observed_at":"2026-07-06T04:56:23.954139Z","submitted_at":"2016-05-16T10:21:25Z","title":"Ternary Weight Networks","version":3},"cited_work":{"arxiv_id":"1605.04711","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1605.04711","snapshot_observed_at":"2026-07-04T13:19:50.534492Z","title":"Ternary weight networks","venue":null,"work_id":"0648c619-efa7-4e61-891b-d0706e11f803","year":2016},"citing_paper":{"arxiv_id":"2604.26979","last_updated":"2026-07-16T12:20:14Z","snapshot_observed_at":"2026-08-02T15:26:24.042235Z","submitted_at":"2026-04-28T13:29:51Z","title":"Multibit neural inference in a N-ary crossbar architecture","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-07T14:26:57.976909Z"},"links":{"cited_paper":"/paper/1605.04711","citing_paper":"/paper/2604.26979"},"observation_digest":"sha256:eb171ff6737336c9db88b78f136c662dee0ef38d8d56a85766b0828f3f9d933a","observation_id":"e046ab5d-ad40-4c73-bc29-06a9860ce64d","resolution":{"observed_at":"2026-05-12T00:46:12.485949Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1605.04711","last_updated":"2022-11-20T14:21:55Z","snapshot_observed_at":"2026-07-06T04:56:23.954139Z","submitted_at":"2016-05-16T10:21:25Z","title":"Ternary Weight Networks","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1605.04711","snapshot_observed_at":"2026-08-02T15:26:25.793477Z","title":"& Yan, J","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2604.26979","last_updated":"2026-07-16T12:20:14Z","snapshot_observed_at":"2026-08-02T15:26:24.042235Z","submitted_at":"2026-04-28T13:29:51Z","title":"Multibit neural inference in a N-ary crossbar architecture","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-02T15:26:25.793477Z"},"links":{"cited_paper":"/paper/1605.04711","citing_paper":"/paper/2604.26979"},"observation_digest":"sha256:7430b3e7ef2daf034d4231c5d6a04385fd01cead4764b973c94fca9190046454","observation_id":"46cf677f-1c54-4926-ace0-939c720914c9","resolution":{"observed_at":"2026-08-02T15:26:25.793477Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1605.04711","last_updated":"2022-11-20T14:21:55Z","snapshot_observed_at":"2026-07-06T04:56:23.954139Z","submitted_at":"2016-05-16T10:21:25Z","title":"Ternary Weight Networks","version":3},"cited_work":{"arxiv_id":"1605.04711","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1605.04711","snapshot_observed_at":"2026-07-04T13:19:50.534492Z","title":"Ternary weight networks","venue":null,"work_id":"0648c619-efa7-4e61-891b-d0706e11f803","year":2016},"citing_paper":{"arxiv_id":"2605.10989","last_updated":"2026-05-24T06:06:44Z","snapshot_observed_at":"2026-07-06T23:22:52.369277Z","submitted_at":"2026-05-09T09:52:38Z","title":"SURGE: Surrogate Gradient Adaptation in Binary Neural Networks","version":1},"reference_index":96,"source":"arxiv_source","source_observed_at":"2026-05-13T06:37:12.626356Z"},"links":{"cited_paper":"/paper/1605.04711","citing_paper":"/paper/2605.10989"},"observation_digest":"sha256:43e17affa51caa8032d43802073529319d6dded1246966ac4e2e905ee347a092","observation_id":"67ef8a8e-77e7-4314-b6ff-cd84c64ca606","resolution":{"observed_at":"2026-05-13T06:37:26.559659Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1605.04711","last_updated":"2022-11-20T14:21:55Z","snapshot_observed_at":"2026-07-06T04:56:23.954139Z","submitted_at":"2016-05-16T10:21:25Z","title":"Ternary Weight Networks","version":3},"cited_work":{"arxiv_id":"1605.04711","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1605.04711","snapshot_observed_at":"2026-07-04T13:19:50.534492Z","title":"Ternary weight networks","venue":null,"work_id":"0648c619-efa7-4e61-891b-d0706e11f803","year":2016},"citing_paper":{"arxiv_id":"2605.10989","last_updated":"2026-05-24T06:06:44Z","snapshot_observed_at":"2026-07-06T23:22:52.369277Z","submitted_at":"2026-05-09T09:52:38Z","title":"SURGE: Surrogate Gradient Adaptation in Binary Neural Networks","version":2},"reference_index":96,"source":"arxiv_source","source_observed_at":"2026-05-19T17:49:19.281712Z"},"links":{"cited_paper":"/paper/1605.04711","citing_paper":"/paper/2605.10989"},"observation_digest":"sha256:b3122c3f327d5bc73092dcacd1adc942dfeae55ed1fd7f6470e05d3d303ca296","observation_id":"3ff40d1a-c71b-4819-af76-9dde00bd0541","resolution":{"observed_at":"2026-05-19T17:52:42.899012Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1605.04711","last_updated":"2022-11-20T14:21:55Z","snapshot_observed_at":"2026-07-06T04:56:23.954139Z","submitted_at":"2016-05-16T10:21:25Z","title":"Ternary Weight Networks","version":3},"cited_work":{"arxiv_id":"1605.04711","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1605.04711","snapshot_observed_at":"2026-07-04T13:19:50.534492Z","title":"Ternary weight networks","venue":null,"work_id":"0648c619-efa7-4e61-891b-d0706e11f803","year":2016},"citing_paper":{"arxiv_id":"2605.19630","last_updated":"2026-05-19T10:11:10Z","snapshot_observed_at":"2026-07-06T23:30:21.283826Z","submitted_at":"2026-05-19T10:11:10Z","title":"EMO-BOOST: Emotion-Augmented Audio-Visual Features for Improved Generalization in Deepfake Detection","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-20T05:47:45.259359Z"},"links":{"cited_paper":"/paper/1605.04711","citing_paper":"/paper/2605.19630"},"observation_digest":"sha256:a2c0085a911d1218f1e407f3b4fc7d2ab1d9c7287c3c9ce9bbe408bad36c85bf","observation_id":"ef11572e-34eb-4f00-9be3-1098a99f116a","resolution":{"observed_at":"2026-05-20T05:48:04.334050Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1605.04711","last_updated":"2022-11-20T14:21:55Z","snapshot_observed_at":"2026-07-06T04:56:23.954139Z","submitted_at":"2016-05-16T10:21:25Z","title":"Ternary Weight Networks","version":3},"cited_work":{"arxiv_id":"1605.04711","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1605.04711","snapshot_observed_at":"2026-07-04T13:19:50.534492Z","title":"Ternary weight networks","venue":null,"work_id":"0648c619-efa7-4e61-891b-d0706e11f803","year":2016},"citing_paper":{"arxiv_id":"2605.21171","last_updated":"2026-05-20T13:41:53Z","snapshot_observed_at":"2026-07-06T23:31:37.061253Z","submitted_at":"2026-05-20T13:41:53Z","title":"FTerViT: Fully Ternary Vision Transformer","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-21T05:59:54.807460Z"},"links":{"cited_paper":"/paper/1605.04711","citing_paper":"/paper/2605.21171"},"observation_digest":"sha256:f3ac29adca43ad850c837469387b78d725f4a8e3ecf478eec857d90f62d4ae78","observation_id":"b9b09f42-7bdb-441f-8896-3abca9d65e9d","resolution":{"observed_at":"2026-05-21T06:03:59.472187Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1605.04711","last_updated":"2022-11-20T14:21:55Z","snapshot_observed_at":"2026-07-06T04:56:23.954139Z","submitted_at":"2016-05-16T10:21:25Z","title":"Ternary Weight Networks","version":3},"cited_work":{"arxiv_id":"1605.04711","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1605.04711","snapshot_observed_at":"2026-07-04T13:19:50.534492Z","title":"Ternary weight networks","venue":null,"work_id":"0648c619-efa7-4e61-891b-d0706e11f803","year":2016},"citing_paper":{"arxiv_id":"2605.30814","last_updated":"2026-05-29T04:05:46Z","snapshot_observed_at":"2026-08-07T05:01:44.076167Z","submitted_at":"2026-05-29T04:05:46Z","title":"A Reconfigurable Computing In-Memory Macro with Charge-sharing-based Weighted Accumulator","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-06-28T20:44:49.356774Z"},"links":{"cited_paper":"/paper/1605.04711","citing_paper":"/paper/2605.30814"},"observation_digest":"sha256:7e87bd5a685b871642d7039b02ca81f9594db0df048d17091054d885e8a49a8d","observation_id":"6eb432b6-0f07-4425-a3bb-56cf0e52f4e9","resolution":{"observed_at":"2026-06-28T20:52:37.885224Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1605.04711","last_updated":"2022-11-20T14:21:55Z","snapshot_observed_at":"2026-07-06T04:56:23.954139Z","submitted_at":"2016-05-16T10:21:25Z","title":"Ternary Weight Networks","version":3},"cited_work":{"arxiv_id":"1605.04711","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1605.04711","snapshot_observed_at":"2026-07-04T13:19:50.534492Z","title":"Ternary weight networks","venue":null,"work_id":"0648c619-efa7-4e61-891b-d0706e11f803","year":2016},"citing_paper":{"arxiv_id":"2606.13054","last_updated":"2026-06-11T08:37:20Z","snapshot_observed_at":"2026-08-08T04:41:50.401399Z","submitted_at":"2026-06-11T08:37:20Z","title":"TWLA: Achieving Ternary Weights and Low-Bit Activations for LLMs via Post-Training Quantization","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-06-27T07:37:59.122704Z"},"links":{"cited_paper":"/paper/1605.04711","citing_paper":"/paper/2606.13054"},"observation_digest":"sha256:00322c98dc5f36cbbc94b76a9cb854fecc77bbb6bdb2feebab9b0c5f1c6a5bd8","observation_id":"f599e4a6-36a0-458d-9c8f-8073527078ef","resolution":{"observed_at":"2026-07-03T13:38:19.687353Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1605.04711","last_updated":"2022-11-20T14:21:55Z","snapshot_observed_at":"2026-07-06T04:56:23.954139Z","submitted_at":"2016-05-16T10:21:25Z","title":"Ternary Weight Networks","version":3},"cited_work":{"arxiv_id":"1605.04711","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1605.04711","snapshot_observed_at":"2026-07-04T13:19:50.534492Z","title":"Ternary weight networks","venue":null,"work_id":"0648c619-efa7-4e61-891b-d0706e11f803","year":2016},"citing_paper":{"arxiv_id":"2606.22249","last_updated":"2026-06-20T22:22:26Z","snapshot_observed_at":"2026-08-06T20:47:52.441640Z","submitted_at":"2026-06-20T22:22:26Z","title":"On the Expressive Power of Weight Quantization in Large Language Models","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-06-26T11:53:45.787243Z"},"links":{"cited_paper":"/paper/1605.04711","citing_paper":"/paper/2606.22249"},"observation_digest":"sha256:43d4ee41c5bbd85bd2ff35aed80211ba7f67f3897799ce40b1065c66140e169b","observation_id":"fe4ff7cd-ee66-4af0-a606-50be94046415","resolution":{"observed_at":"2026-07-04T08:19:44.233326Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1605.04711","last_updated":"2022-11-20T14:21:55Z","snapshot_observed_at":"2026-07-06T04:56:23.954139Z","submitted_at":"2016-05-16T10:21:25Z","title":"Ternary Weight Networks","version":3},"cited_work":{"arxiv_id":"1605.04711","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1605.04711","snapshot_observed_at":"2026-07-04T13:19:50.534492Z","title":"Ternary weight networks","venue":null,"work_id":"0648c619-efa7-4e61-891b-d0706e11f803","year":2016},"citing_paper":{"arxiv_id":"2606.26650","last_updated":"2026-06-25T06:24:02Z","snapshot_observed_at":"2026-08-07T13:58:30.530066Z","submitted_at":"2026-06-25T06:24:02Z","title":"CAT-Q: Cost-efficient and Accurate Ternary Quantization for LLMs","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-06-26T05:21:12.916984Z"},"links":{"cited_paper":"/paper/1605.04711","citing_paper":"/paper/2606.26650"},"observation_digest":"sha256:23c98ded1a09d93414dff6b789b3b305e9e9d9651708f7f9b083d3d26f179779","observation_id":"44e375dc-b890-49ff-aa30-80c2d13034da","resolution":{"observed_at":"2026-07-04T13:19:50.536501Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1605.04711","last_updated":"2022-11-20T14:21:55Z","snapshot_observed_at":"2026-07-06T04:56:23.954139Z","submitted_at":"2016-05-16T10:21:25Z","title":"Ternary Weight Networks","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1605.04711","snapshot_observed_at":"2026-08-02T05:02:32.547154Z","title":null,"venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2607.13511","last_updated":"2026-07-15T07:04:32Z","snapshot_observed_at":"2026-08-09T18:22:29.760947Z","submitted_at":"2026-07-15T07:04:32Z","title":"ExTernD: Expanded-Rank Ternary Decomposition Ternary LLM PTQ with Accuracy Approaching Any Quantization Level","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-02T05:02:32.547154Z"},"links":{"cited_paper":"/paper/1605.04711","citing_paper":"/paper/2607.13511"},"observation_digest":"sha256:45346eff6ba9b83adbd2939f6393e245484ce7864cda7f6a47119fa08860a8fd","observation_id":"b40a251a-68f6-405d-93de-bcaf3ad2a5ea","resolution":{"observed_at":"2026-08-02T05:02:32.547154Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1605.04711","last_updated":"2022-11-20T14:21:55Z","snapshot_observed_at":"2026-07-06T04:56:23.954139Z","submitted_at":"2016-05-16T10:21:25Z","title":"Ternary Weight Networks","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1605.04711","snapshot_observed_at":"2026-08-08T12:00:53.833004Z","title":"Ternary weight networks.arXiv preprint arXiv:1605.04711, 2016","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2608.05499","last_updated":"2026-08-06T01:09:50Z","snapshot_observed_at":"2026-08-09T23:10:57.451578Z","submitted_at":"2026-08-06T01:09:50Z","title":"APQF: Agentic Profiling-Guided Structured Pruning and Mixed-Precision Quantization with Adaptive Fine-Tuning","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-08T12:00:53.833004Z"},"links":{"cited_paper":"/paper/1605.04711","citing_paper":"/paper/2608.05499"},"observation_digest":"sha256:461b5d587ce1ba9e8f036ec04421066ff2d90458eb8f3f6c45c2c1d6e4324170","observation_id":"b10a39b5-722c-433f-a0c8-b031381073d6","resolution":{"observed_at":"2026-08-08T12:00:53.833004Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/1605.04711/citation-record","integrity":"/paper/1605.04711/integrity","json":"/paper/1605.04711/citation-record.json","paper":"/paper/1605.04711"},"outbound":[],"paper":{"arxiv_id":"1605.04711","last_updated":"2022-11-20T14:21:55Z","latest_version":3,"primary_category":"cs.CV","snapshot_observed_at":"2026-07-06T04:56:23.954139Z","submitted_at":"2016-05-16T10:21:25Z","title":"Ternary Weight Networks"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 23 inbound Pith citation observations for arXiv:1605.04711."}