{"as_of":"2026-08-12T15:54:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2f20860c3c09db1ab72330dcc5f657f97cbe69199ee6e612306ce0d52131b67d","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":4,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":4,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-12T06:34:41.77262+00:00","state":"measured"},{"denominator":4,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":4,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T13:04:27.633501Z","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":"2026-05-23T05:22:35.212988Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2305.05954","last_updated":"2023-05-19T07:50:16Z","snapshot_observed_at":"2026-08-04T06:43:28.735044Z","submitted_at":"2023-05-10T07:48:08Z","title":"Enhancing the Performance of Transformer-based Spiking Neural Networks by SNN-optimized Downsampling with Precise Gradient Backpropagation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.05954","snapshot_observed_at":"2026-08-11T13:04:27.633501Z","title":"Enhanc- ing the performance of transformer-based spiking neural net- works by improved downsampling with precise gradient back- propagation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.13553","last_updated":"2024-12-18T07:07:38Z","snapshot_observed_at":"2026-08-11T17:13:49.227129Z","submitted_at":"2024-12-18T07:07:38Z","title":"Combining Aggregated Attention and Transformer Architecture for Accurate and Efficient Performance of Spiking Neural Networks","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-11T13:04:27.633501Z"},"links":{"cited_paper":"/paper/2305.05954","citing_paper":"/paper/2412.13553"},"observation_digest":"sha256:2ded1a2c11f8b6f10b4aeaa6fcd345ed87573f182660fc2b655a5d494b68aa76","observation_id":"1125d456-94c6-4790-8e18-fe77ea784087","resolution":{"observed_at":"2026-08-11T13:04:27.633501Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.05954","last_updated":"2023-05-19T07:50:16Z","snapshot_observed_at":"2026-08-04T06:43:28.735044Z","submitted_at":"2023-05-10T07:48:08Z","title":"Enhancing the Performance of Transformer-based Spiking Neural Networks by SNN-optimized Downsampling with Precise Gradient Backpropagation","version":3},"cited_work":{"arxiv_id":"2305.05954","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2305.05954","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Enhancing the performance of transformer-based spiking neural networks by snn-optimized downsampling with precise gradient backpropagation","venue":null,"work_id":"e462a5b0-03cf-442f-8d07-064d0c784205","year":2023},"citing_paper":{"arxiv_id":"2501.06786","last_updated":"2026-04-11T01:25:59Z","snapshot_observed_at":"2026-08-06T12:09:27.959442Z","submitted_at":"2025-01-12T11:48:19Z","title":"Temporal-Aware Spiking Transformer Hashing Based on 3D-DWT","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-05-23T05:19:28.832183Z"},"links":{"cited_paper":"/paper/2305.05954","citing_paper":"/paper/2501.06786"},"observation_digest":"sha256:f6d2bf6dd2ab66acb2816dfb4dd3fb46103375b84c1c17d6a026abcd483d9784","observation_id":"51e811ff-d42c-4a42-9ed0-122fc18a6eae","resolution":{"observed_at":"2026-05-23T05:22:35.216586Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.05954","last_updated":"2023-05-19T07:50:16Z","snapshot_observed_at":"2026-08-04T06:43:28.735044Z","submitted_at":"2023-05-10T07:48:08Z","title":"Enhancing the Performance of Transformer-based Spiking Neural Networks by SNN-optimized Downsampling with Precise Gradient Backpropagation","version":3},"cited_work":{"arxiv_id":"2305.05954","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2305.05954","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Enhancing the performance of transformer-based spiking neural networks by snn-optimized downsampling with precise gradient backpropagation","venue":null,"work_id":"e462a5b0-03cf-442f-8d07-064d0c784205","year":2023},"citing_paper":{"arxiv_id":"2604.12365","last_updated":"2026-04-14T06:53:51Z","snapshot_observed_at":"2026-07-06T23:00:37.144068Z","submitted_at":"2026-04-14T06:53:51Z","title":"Adaptive Spiking Neurons for Vision and Language Modeling","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-05-10T14:28:41.685107Z"},"links":{"cited_paper":"/paper/2305.05954","citing_paper":"/paper/2604.12365"},"observation_digest":"sha256:363dc879de0cd8971bf1e5a5611bbb15d42862f3741938621db7e8d62e7f451a","observation_id":"7c2aa211-445c-4043-bfd2-446f199c2a81","resolution":{"observed_at":"2026-05-10T14:30:30.726715Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.05954","last_updated":"2023-05-19T07:50:16Z","snapshot_observed_at":"2026-08-04T06:43:28.735044Z","submitted_at":"2023-05-10T07:48:08Z","title":"Enhancing the Performance of Transformer-based Spiking Neural Networks by SNN-optimized Downsampling with Precise Gradient Backpropagation","version":3},"cited_work":{"arxiv_id":"2305.05954","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2305.05954","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Enhancing the performance of transformer-based spiking neural networks by snn-optimized downsampling with precise gradient backpropagation","venue":null,"work_id":"e462a5b0-03cf-442f-8d07-064d0c784205","year":2023},"citing_paper":{"arxiv_id":"2605.13887","last_updated":"2026-05-12T02:08:08Z","snapshot_observed_at":"2026-08-08T19:16:17.990563Z","submitted_at":"2026-05-12T02:08:08Z","title":"Breaking Global Self-Attention Bottlenecks in Transformer-based Spiking Neural Networks with Local Structure-Aware Self-Attention","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-05-15T06:17:49.425564Z"},"links":{"cited_paper":"/paper/2305.05954","citing_paper":"/paper/2605.13887"},"observation_digest":"sha256:a8cae86f4cfd0e6f78b0289cc9c705693d460f4e0543ad46a2ce33dd29eaa8bd","observation_id":"fd8d6d5d-d6d9-417f-b449-050599b84e62","resolution":{"observed_at":"2026-05-15T06:19:49.668990Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2305.05954/citation-record","integrity":"/paper/2305.05954/integrity","json":"/paper/2305.05954/citation-record.json","paper":"/paper/2305.05954"},"outbound":[],"paper":{"arxiv_id":"2305.05954","last_updated":"2023-05-19T07:50:16Z","latest_version":3,"primary_category":"cs.NE","snapshot_observed_at":"2026-08-04T06:43:28.735044Z","submitted_at":"2023-05-10T07:48:08Z","title":"Enhancing the Performance of Transformer-based Spiking Neural Networks by SNN-optimized Downsampling with Precise Gradient Backpropagation"},"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":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"thesis":"As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2305.05954."}