{"as_of":"2026-08-20T09:29:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:97c9a685f98a85ea517c16a1f1ad878edf3b4585aedd9c32ee8319973522cdff","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":6,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":6,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-20T06:33:59.587034+00:00","state":"measured"},{"denominator":6,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":6,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-08T13:18:19.513815Z","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":"2026-05-20T14:03:20.548266Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2005.14187","last_updated":"2020-05-28T17:58:56Z","snapshot_observed_at":"2026-08-13T22:35:05.484443Z","submitted_at":"2020-05-28T17:58:56Z","title":"HAT: Hardware-Aware Transformers for Efficient Natural Language Processing","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2005.14187","snapshot_observed_at":"2026-08-08T13:18:19.513815Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2502.07277","last_updated":"2025-02-11T05:44:50Z","snapshot_observed_at":"2026-08-17T02:24:31.941590Z","submitted_at":"2025-02-11T05:44:50Z","title":"Enhancing Video Understanding: Deep Neural Networks for Spatiotemporal Analysis","version":1},"reference_index":142,"source":"pdf_text","source_observed_at":"2026-08-08T13:18:19.513815Z"},"links":{"cited_paper":"/paper/2005.14187","citing_paper":"/paper/2502.07277"},"observation_digest":"sha256:a1c65604fe65c2b524173ed2ba08663289d757488653d7f467765486bee8fb0a","observation_id":"6350fcda-26d6-4d17-9b4d-cd09efc560d9","resolution":{"observed_at":"2026-08-08T13:18:19.513815Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2005.14187","last_updated":"2020-05-28T17:58:56Z","snapshot_observed_at":"2026-08-13T22:35:05.484443Z","submitted_at":"2020-05-28T17:58:56Z","title":"HAT: Hardware-Aware Transformers for Efficient Natural Language Processing","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2005.14187","snapshot_observed_at":"2026-08-07T15:30:54.153630Z","title":"Hat: Hardware-aware transformers for efficient natural language processing","venue":null,"work_id":null,"year":2005},"citing_paper":{"arxiv_id":"2506.00020","last_updated":"2025-05-20T23:09:01Z","snapshot_observed_at":"2026-08-13T03:52:53.869618Z","submitted_at":"2025-05-20T23:09:01Z","title":"Hybrid SLC-MLC RRAM Mixed-Signal Processing-in-Memory Architecture for Transformer Acceleration via Gradient Redistribution","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-07T15:30:54.153630Z"},"links":{"cited_paper":"/paper/2005.14187","citing_paper":"/paper/2506.00020"},"observation_digest":"sha256:9c92fdb3abf60505a916ea9d14f27e268968482f71abd6f8c75116b9e6286a69","observation_id":"764fc092-3ef1-4749-9335-818ff233ae8c","resolution":{"observed_at":"2026-08-07T15:30:54.153630Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2005.14187","last_updated":"2020-05-28T17:58:56Z","snapshot_observed_at":"2026-08-13T22:35:05.484443Z","submitted_at":"2020-05-28T17:58:56Z","title":"HAT: Hardware-Aware Transformers for Efficient Natural Language Processing","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2005.14187","snapshot_observed_at":"2026-08-06T05:40:27.231960Z","title":"Hat: Hardware-aware transformers for efficient natural language processing,","venue":null,"work_id":null,"year":2005},"citing_paper":{"arxiv_id":"2508.01505","last_updated":"2025-08-02T22:06:39Z","snapshot_observed_at":"2026-08-19T13:43:37.397420Z","submitted_at":"2025-08-02T22:06:39Z","title":"ESM: A Framework for Building Effective Surrogate Models for Hardware-Aware Neural Architecture Search","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T05:40:27.231960Z"},"links":{"cited_paper":"/paper/2005.14187","citing_paper":"/paper/2508.01505"},"observation_digest":"sha256:febeb7b946a8e2711f1a270fb831d6281928b681e48c111503417503cc284087","observation_id":"41e028b0-5cc8-4434-b108-a62cc2395abf","resolution":{"observed_at":"2026-08-06T05:40:27.231960Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2005.14187","last_updated":"2020-05-28T17:58:56Z","snapshot_observed_at":"2026-08-13T22:35:05.484443Z","submitted_at":"2020-05-28T17:58:56Z","title":"HAT: Hardware-Aware Transformers for Efficient Natural Language Processing","version":1},"cited_work":{"arxiv_id":"2005.14187","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2005.14187","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"HAT: Hardware-aware transformers for efficient natural language processing","venue":null,"work_id":"174c02de-ddd7-4a89-8f4d-3df74cc56176","year":2020},"citing_paper":{"arxiv_id":"2510.14235","last_updated":"2026-02-03T02:30:05Z","snapshot_observed_at":"2026-08-12T20:14:22.026190Z","submitted_at":"2025-10-16T02:27:07Z","title":"Spiking Neural Network Architecture Search: A Survey","version":2},"reference_index":133,"source":"pdf_text","source_observed_at":"2026-05-18T07:00:27.719109Z"},"links":{"cited_paper":"/paper/2005.14187","citing_paper":"/paper/2510.14235"},"observation_digest":"sha256:c28fe006a7cea02562c547a24b6411a2c9f1b4d6e333b9ed5e9f1dc94b234fdd","observation_id":"008c97d1-befe-4b1d-a130-1c2ae6667e79","resolution":{"observed_at":"2026-05-18T07:01:01.380324Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2005.14187","last_updated":"2020-05-28T17:58:56Z","snapshot_observed_at":"2026-08-13T22:35:05.484443Z","submitted_at":"2020-05-28T17:58:56Z","title":"HAT: Hardware-Aware Transformers for Efficient Natural Language Processing","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2005.14187","snapshot_observed_at":"2026-08-04T09:03:09.479580Z","title":"Hat: Hardware-aware transformers for efficient natural language processing.arXiv preprint arXiv:2005.14187, 2020","venue":null,"work_id":null,"year":2005},"citing_paper":{"arxiv_id":"2510.17700","last_updated":"2026-05-29T13:56:08Z","snapshot_observed_at":"2026-08-18T23:32:52.492028Z","submitted_at":"2025-10-20T16:15:03Z","title":"Elastic ViTs from Pretrained Models without Retraining","version":2},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-04T09:03:09.479580Z"},"links":{"cited_paper":"/paper/2005.14187","citing_paper":"/paper/2510.17700"},"observation_digest":"sha256:88c5e1df4fac4230a25d789c745b2ede7fe2f3a435ae0f8f8972ed92af9d64c1","observation_id":"1426f90d-0bec-4efa-9e88-4c5e23b818a7","resolution":{"observed_at":"2026-08-04T09:03:09.479580Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2005.14187","last_updated":"2020-05-28T17:58:56Z","snapshot_observed_at":"2026-08-13T22:35:05.484443Z","submitted_at":"2020-05-28T17:58:56Z","title":"HAT: Hardware-Aware Transformers for Efficient Natural Language Processing","version":1},"cited_work":{"arxiv_id":"2005.14187","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2005.14187","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"HAT: Hardware-aware transformers for efficient natural language processing","venue":null,"work_id":"174c02de-ddd7-4a89-8f4d-3df74cc56176","year":2020},"citing_paper":{"arxiv_id":"2605.17653","last_updated":"2026-05-17T21:10:54Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-17T21:10:54Z","title":"LLMForge: Multi-Backend Hardware-Aware Neural Architecture Search with Infinite-Head Attention for Edge Language Models","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-20T13:58:55.899958Z"},"links":{"cited_paper":"/paper/2005.14187","citing_paper":"/paper/2605.17653"},"observation_digest":"sha256:33008cdf511a0d0fa1f1f2a498421c35a2f2f284ecaccd75c6c6c03be72dea2b","observation_id":"bbf602cb-026f-49af-bef0-dc48d8b4bcf8","resolution":{"observed_at":"2026-05-20T14:03:20.550972Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2005.14187/citation-record","integrity":"/paper/2005.14187/integrity","json":"/paper/2005.14187/citation-record.json","paper":"/paper/2005.14187"},"outbound":[],"paper":{"arxiv_id":"2005.14187","last_updated":"2020-05-28T17:58:56Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-13T22:35:05.484443Z","submitted_at":"2020-05-28T17:58:56Z","title":"HAT: Hardware-Aware Transformers for Efficient Natural Language Processing"},"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":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"thesis":"As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2005.14187."}