{"as_of":"2026-08-18T02:58:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:ddbcc91c91edf6f4405cb84809990ddba5516441db1e08d9e8b86323a15db145","coverage":[{"denominator":63,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":63,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T20:13:58.317969Z","state":"measured"},{"denominator":63,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":63,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-17T06:30:58.91139+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/2507.03522/citation-record","integrity":"/paper/2507.03522/integrity","json":"/paper/2507.03522/citation-record.json","paper":"/paper/2507.03522"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:14:04.283040Z","title":"Efficient processing of deep neural networks: A tutorial and survey,","venue":null,"work_id":"73c18133-9656-4ee4-87a3-1add7a935ec9","year":2017},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:53.842071Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:5f29fcf09f13a62477579992c55cd6b881977d7d003b5c38e1a3f3be157ba34d","observation_id":"490bd61b-8262-415b-ae87-4d6fbaebd3cd","resolution":{"observed_at":"2026-08-06T20:14:04.288876Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:14:04.263729Z","title":"Anatomy of high-performance deep learning convolutions on simd architectures,","venue":null,"work_id":"82d3bdc4-4891-4663-bf9c-52574eab726b","year":2018},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:53.889218Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:08e5e4ac627bdd6000b6784848954d94258c74f21c41cc2e70041508ae6c47e4","observation_id":"c7272be5-e146-4634-839d-64538fe56163","resolution":{"observed_at":"2026-08-06T20:14:04.270121Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/s10586-018-2810-y","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T00:03:40.895421Z","title":"An implementation of matrix—matrix multiplication on the intel knl processor with avx-512,","venue":"Cluster Computing","work_id":"a99efe8a-b2ba-4f9d-91e0-073b009a136e","year":2018},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:53.953799Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:9ed5ee87d8d8c49f3b46e890e831141c286c9bf1d5b9108744346b2a21d1fba2","observation_id":"eac38bfc-af64-43f0-9ce6-ccb9559e6a62","resolution":{"observed_at":"2026-08-06T20:13:58.640232Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:14:04.234567Z","title":"Efficient direct convo- lution using long simd instructions,","venue":null,"work_id":"55609daf-eb7e-47e7-9b4e-eb6c38bf4b29","year":2023},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:54.045666Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:3f002d29cfbb809d27d4908d2f50a2844b7141a27f5a8c9d5f1019d1e877b01a","observation_id":"a1b97bae-23ff-453a-a349-b2e63ec9e117","resolution":{"observed_at":"2026-08-06T20:14:04.240628Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:14:04.214743Z","title":null,"venue":null,"work_id":"02cd6823-916d-4744-836a-6b71e1735101","year":2023},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:54.103788Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:60ee8420ce28fbb6e736e81da779a3cc715286d7bae55a0942c8f85d2bd07be9","observation_id":"7ed5c7f8-0f05-41d6-86d7-3d82be105de4","resolution":{"observed_at":"2026-08-06T20:14:04.220319Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2104.03142","last_updated":"2021-04-07T14:17:32Z","snapshot_observed_at":"2026-08-16T18:33:17.696211Z","submitted_at":"2021-04-07T14:17:32Z","title":"A matrix math facility for Power ISA(TM) processors","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2104.03142","snapshot_observed_at":"2026-08-06T20:13:54.231825Z","title":"A matrix math facility for power isa (tm) processors,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:54.231825Z"},"links":{"cited_paper":"/paper/2104.03142","citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:e05b910613d97258df82d39e3538e3acd136436208e4d4ee2070902da4744d95","observation_id":"11d88f5d-0eff-4bf5-b822-1544a221fd5c","resolution":{"observed_at":"2026-08-06T20:13:54.231825Z","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":"2026-08-06T20:14:04.194043Z","title":"Sifive intelligence extensions documentation,","venue":null,"work_id":"8460597e-f02a-4972-a046-9c980d92c95f","year":2024},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:54.274806Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:ff29665321dd72fd550f6e5b31951daefd64ce0a756ea8ee01cf6b575ae7b184","observation_id":"144c46e9-2d24-4259-b29d-506f67f3bb98","resolution":{"observed_at":"2026-08-06T20:14:04.200428Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:14:04.169358Z","title":"T-head risc-v matrix extension specification,","venue":null,"work_id":"d665317b-df0a-4f7d-add1-aa8379a10631","year":2024},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:54.368780Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:68245b48bd2fd46f6aee014d2329faba2f5bd3b2f41303fb5e26fb0e2c1fea13","observation_id":"cd045240-e33e-44cc-a45e-eb01b53c6f39","resolution":{"observed_at":"2026-08-06T20:14:04.177448Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:14:04.144027Z","title":"The power instruction set architecture v3.1,","venue":null,"work_id":"8596e3ed-25bf-4288-ab37-ce9c74f64409","year":2024},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:54.449410Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:d2bc7a80dda250a4ffd8127f838df6ff28d7c104693658d3bdd376e9a1a47c9a","observation_id":"46f7cc35-d400-4950-a9c9-6c2102d78ed0","resolution":{"observed_at":"2026-08-06T20:14:04.151007Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:14:04.117366Z","title":"The scalable matrix extension (sme), for armv9-a,","venue":null,"work_id":"2cb086a0-af44-47af-b2dc-0f39e9a02132","year":2024},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:54.489610Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:5d04a5de325e228baa6268f97ec56fc903a9fa5bbe1ff76ab60df6922b6b1bc8","observation_id":"fe858a97-64ee-4833-9daa-0aca2612e8b2","resolution":{"observed_at":"2026-08-06T20:14:04.124589Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:14:04.092565Z","title":"Knights landing: Second-generation intel xeon phi product,","venue":null,"work_id":"fdcd5ea6-7a5f-4d2d-8c62-ec295d8bf73f","year":2016},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:54.556475Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:90d659f19179a931c8ed7138b17c8b8e29e46916b10d536decf2afbc1ecf36f9","observation_id":"deaf4ef7-3df7-4d0c-ba8d-3b8b59f41587","resolution":{"observed_at":"2026-08-06T20:14:04.099076Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:14:04.073989Z","title":"Co-Design for A64FX Manycore Processor and","venue":null,"work_id":"5f4ce519-86d4-49d6-8ea0-2d8dee8b8e47","year":2020},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:54.645143Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:13c9b1450a8fad56fd4fad1c28cec14a504de50b9d0b696c8a96ae8a5bde2b36","observation_id":"96429c10-c32a-4aec-97a5-147557639163","resolution":{"observed_at":"2026-08-06T20:14:04.079124Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:14:04.056837Z","title":"The risc-v vector extension,","venue":null,"work_id":"47a3ea36-a5a7-4d25-bce6-3a9a612ec969","year":2024},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:54.709577Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:b0f939233a2b57cc257dd36ee5cb155713e9df5646c5a7c52f40562c42527220","observation_id":"14ff66f2-fc21-4198-8e60-e67f95404001","resolution":{"observed_at":"2026-08-06T20:14:04.061779Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:14:04.039112Z","title":"The arm scalable vector extension,","venue":null,"work_id":"777a9e00-a431-4fea-8415-6fae7e76a1a6","year":2017},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:54.802004Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:77321b8264a0dd781848a59b8c51e67336485b2b554356cb9d131798c152ba50","observation_id":"2476f8ee-e1d8-4106-8d34-5bd157a3b03e","resolution":{"observed_at":"2026-08-06T20:14:04.045117Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:13:54.854188Z","title":"Deep residual learning for image recognition,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:54.854188Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:2277e1308f0fad217674a02d12c9aa7357ecf0ddb4b7a4cdfc173253156f27b8","observation_id":"f5d410b6-9281-4db9-8892-c98f98ede781","resolution":{"observed_at":"2026-08-06T20:13:54.854188Z","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":"2026-08-06T20:13:54.914981Z","title":"Rethinking the inception architecture for computer vision,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:54.914981Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:351d9b41be68c3e458e17c1079275d841a64fb2e81c5ca7affca616559be0a9a","observation_id":"06e8bef5-2699-4b0a-932a-c87df2716060","resolution":{"observed_at":"2026-08-06T20:13:54.914981Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1409.1556","last_updated":"2015-04-10T16:25:04Z","snapshot_observed_at":"2026-08-17T19:17:06.411141Z","submitted_at":"2014-09-04T19:48:04Z","title":"Very Deep Convolutional Networks for Large-Scale Image Recognition","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1409.1556","snapshot_observed_at":"2026-08-06T20:13:55.015898Z","title":"Very deep convolutional networks for large-scale image recognition,","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:55.015898Z"},"links":{"cited_paper":"/paper/1409.1556","citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:2623e7a4a09df519f6374e5d7a14f18e4addb28c02ce81d95b71bcca24a0ec67","observation_id":"3c48838a-ed69-4582-940d-2b1229884b5f","resolution":{"observed_at":"2026-08-06T20:13:55.015898Z","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":"2026-08-06T20:13:55.063041Z","title":"You only look once: Unified, real-time object detection,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:55.063041Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:a42411164b854ff1e03271175d2ded6c543ecfda3125d5e1a49bc5dcb0065a3b","observation_id":"1df15764-4b0e-4309-8766-7e611a424369","resolution":{"observed_at":"2026-08-06T20:13:55.063041Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1602.07360","last_updated":"2016-11-04T21:26:08Z","snapshot_observed_at":"2026-08-14T22:09:04.541956Z","submitted_at":"2016-02-24T00:09:45Z","title":"SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1602.07360","snapshot_observed_at":"2026-08-06T20:13:55.125054Z","title":"Squeezenet: Alexnet-level accuracy with 50x fewer parameters and¡ 0.5 mb model size,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:55.125054Z"},"links":{"cited_paper":"/paper/1602.07360","citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:4f53946fb68299561ef299beea9f7fb1d33748d2180d93aefb2a98a61fab1b55","observation_id":"9b7faaa0-eaa3-4f9e-8993-e0b7e67913d5","resolution":{"observed_at":"2026-08-06T20:13:55.125054Z","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":"2026-08-06T20:13:55.190969Z","title":"Attention is all you need,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:55.190969Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:b6fd2539ac073af5c0b7bbe84b19730bc2dde8a74081faabcf12237f4c118bdf","observation_id":"8ef48d49-0e5a-4b63-b128-a703fe23df7f","resolution":{"observed_at":"2026-08-06T20:13:55.190969Z","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":"2026-08-06T20:13:55.272104Z","title":"Language mod- els are few-shot learners,","venue":null,"work_id":null,"year":1901},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:55.272104Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:c01afb3a8031fc60c433cf41a83e2399ff1717ea430b8542b3a064643cfe4004","observation_id":"0e589cfd-41c5-4f16-a66e-696d0c353074","resolution":{"observed_at":"2026-08-06T20:13:55.272104Z","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":"2026-08-06T20:14:03.948731Z","title":"Bert4rec: Sequential recommendation with bidirectional encoder representations from transformer,","venue":null,"work_id":"2c4db5ef-74d4-4e00-8745-fe61b9aa2283","year":2019},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:55.337011Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:d5b7a81aea673d641c67a2022208194233f0fd4e4107e23147f49d3dd8f07cfe","observation_id":"1c15801c-b925-4be5-be9a-653ddbf73218","resolution":{"observed_at":"2026-08-06T20:14:03.953042Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:14:03.927935Z","title":"Sse-pt: Sequential recommendation via personalized transformer,","venue":null,"work_id":"d8a8458f-8a88-4fcb-8d52-d48e5dc82183","year":2020},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:55.399361Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:150cc7a82d791bfbb54ba9a8c8c52fd7fe9ef84d8149cbbee5606015cc804168","observation_id":"255d492f-5011-4581-a990-4d23d8a0a761","resolution":{"observed_at":"2026-08-06T20:14:03.932762Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:14:03.912468Z","title":"The architectural implications of facebook’s dnn-based personalized recommendation,","venue":null,"work_id":"6625cdb4-ba45-4b41-b7c7-5bdf2f7a2e21","year":2020},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:55.460901Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:313947205dc56a4749751023616ef502e45d0c751696e17712ab0e52bccf74bd","observation_id":"a6846dd8-3f82-4ae6-97a7-8003f8d1c48c","resolution":{"observed_at":"2026-08-06T20:14:03.917188Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:14:03.897109Z","title":"An updated set of basic linear algebra subprograms (blas),","venue":null,"work_id":"345ef270-cf5e-41e3-a1c5-9d26424295a6","year":2002},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:55.536819Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:211897660747426fe018e21752bc53313f3d5996614295a6ea80afcd03811f9d","observation_id":"4639e2f2-d442-47df-98e7-7e87aaddd2c0","resolution":{"observed_at":"2026-08-06T20:14:03.901977Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:14:03.881055Z","title":"High performance zero-memory overhead direct convolutions,","venue":null,"work_id":"ccfcfe20-62e3-46c8-9398-a0bb25363e7e","year":2018},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:55.589345Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:48cadcac52ec66b8c5ccb7d2e607be1399b55f39378a6daf2a34f0785a31586a","observation_id":"ea8bc5f0-35f5-4562-b930-4f472d56b2c8","resolution":{"observed_at":"2026-08-06T20:14:03.886480Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/978-3-031-32041-5","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T00:03:56.115653Z","title":"Performance evaluation of a next-generation sx-aurora tsubasa vector supercomputer,","venue":"Lecture notes in computer science","work_id":"defeb603-9626-40d8-9e4e-cfc671e4b784","year":2023},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:55.671788Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:f61313133cf9a4ffffd870855908c66b4c97bd9f1c5a0a1d13b9e2fe11a94d18","observation_id":"f8ccbcd7-e40b-4c72-9029-99afbc4e286d","resolution":{"observed_at":"2026-08-06T20:13:58.536461Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:14:03.864041Z","title":"Vitruvius+: an area-efficient risc-v decoupled vector coprocessor for high performance computing applications,","venue":null,"work_id":"b3f190e9-20a6-4e3a-aa4d-57b15a839969","year":2023},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:55.742471Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:0a9ad5c7efc9403942ef36bec23c7d4f6cf185087bbc2ff443d21101becedf58","observation_id":"bfc6eeaf-a3cd-4523-8c59-626fe110e08d","resolution":{"observed_at":"2026-08-06T20:14:03.868923Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:14:03.847543Z","title":"Vsa: A hybrid vector- systolic architecture,","venue":null,"work_id":"80a8dfba-a7a5-4f21-8ea0-bb14975b4395","year":2022},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:55.780220Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:caa01338907ec6253be8720f3c69f33fff36f9b10c6a3e5705c26de1b030ca7f","observation_id":"6aa4665f-8416-43c1-b8c7-cde9f823f259","resolution":{"observed_at":"2026-08-06T20:14:03.853117Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:14:03.828296Z","title":"Stencil codes on a vector length agnostic architecture,","venue":null,"work_id":"6af5ae33-2ee0-4b1e-9af2-2b04cd8cf7e4","year":2018},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:55.858993Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:89656b19bbf6e4bfcdc6abf98c846afa12094d2bc329504d2802d3a38b18a68a","observation_id":"10c59ad3-9824-49e0-81a9-10b8dc7f0986","resolution":{"observed_at":"2026-08-06T20:14:03.833913Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:14:03.809509Z","title":"Efficiently running spmv on long vector architectures,","venue":null,"work_id":"162c69c4-d7ff-4a54-9662-9ae5fc73508b","year":2021},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:55.963359Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:e460973e0a6cd95a6d9c22579bd893799a9d88c94bd7df3c83f0b0d9f6556b9a","observation_id":"c1039acf-dca2-44a7-8f62-f5f700aab4e6","resolution":{"observed_at":"2026-08-06T20:14:03.816428Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:14:03.791071Z","title":"Challenges and oppor- tunities in the co-design of convolutions and risc-v vector processors,","venue":null,"work_id":"5a80f60d-9314-464b-8fba-3bba29f9ed66","year":2023},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:56.067070Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:452522f0fbeb7ecd28e50c0e78619aadfb3ce8407a645266602b7e912f74bb21","observation_id":"0916fce2-b009-4661-8e60-74aa6313b18c","resolution":{"observed_at":"2026-08-06T20:14:03.795611Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:14:03.774034Z","title":null,"venue":null,"work_id":"4245751d-0730-4ade-b271-462ac6b71331","year":2020},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:56.163745Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:ec6a57f54a8fd2ba1e561a47fcb0846c628f56aa2b9b59d414c7a2abf11df61f","observation_id":"34560842-ed1a-4452-b3b6-f101f238f4d6","resolution":{"observed_at":"2026-08-06T20:14:03.779118Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:14:03.756875Z","title":null,"venue":null,"work_id":"af8e1891-cdb1-4f1c-88cf-df96be66fc56","year":2023},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:56.231176Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:f6bd913b49041907aa139f4008519904559a49f188419d62db55c641d57f3503","observation_id":"cb7582d7-e55d-46da-a1d7-38ad59e6baf0","resolution":{"observed_at":"2026-08-06T20:14:03.762123Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:14:03.736831Z","title":null,"venue":null,"work_id":"460407e6-9400-4eac-aa38-f85e103d77ed","year":2024},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:56.323032Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:54b39b0ae81107372dbbb5e864e15234d48a949a363d157e014b379e383f18f0","observation_id":"8c6baf63-f5a9-4813-afed-26d5242b691a","resolution":{"observed_at":"2026-08-06T20:14:03.743580Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:14:03.713376Z","title":null,"venue":null,"work_id":"7d8c8e38-4a5b-4cb6-8f00-71ff272232fe","year":2022},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:56.407230Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:43708f4aeda4cf2d669c19debe8d8820831de4ea553b16b004d725d101fdac37","observation_id":"2d03e0bb-39ab-4c0f-b7de-baaa9473d326","resolution":{"observed_at":"2026-08-06T20:14:03.719036Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2007.06674","last_updated":"2020-07-13T20:33:46Z","snapshot_observed_at":"2026-08-13T22:08:35.469780Z","submitted_at":"2020-07-13T20:33:46Z","title":"A Survey of Numerical Methods Utilizing Mixed Precision Arithmetic","version":1},"cited_work":{"arxiv_id":"2007.06674","doi":null,"metadata_source":"pith","pith_arxiv_id":"2007.06674","snapshot_observed_at":"2026-08-06T20:13:59.081203Z","title":"A Survey of Numerical Methods Utilizing Mixed Precision Arithmetic","venue":"cs.MS","work_id":"5aef0fe0-339d-4fc1-880a-d11e60dbabf8","year":2020},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:56.478683Z"},"links":{"cited_paper":"/paper/2007.06674","citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:14cdd75644a47afbec2341bb1143ae715dcad65a9f0cf8a3043c32d532415143","observation_id":"d4d98a82-2ef4-4486-8b5f-bc4c28fcad7b","resolution":{"observed_at":"2026-08-06T20:13:59.162540Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:14:03.691387Z","title":"Nvidia hopper h100 gpu: Scaling performance,","venue":null,"work_id":"24dec3f8-859e-4e6c-af57-5444d9840889","year":2023},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:56.574837Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:f419789277b8a3e86c5f3838b2b6afad3f17b40b54a1da1a327c2d738efeab5b","observation_id":"167b023d-67e6-44c3-9e54-08589b54140a","resolution":{"observed_at":"2026-08-06T20:14:03.697114Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:14:03.671925Z","title":"Ten lessons from three generations shaped google’s tpuv4i: Industrial product,","venue":null,"work_id":"41dc66ce-725e-4fd2-8e5b-29c06b7e2e74","year":2021},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:56.658665Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:bd204d05494c5a371b374c2e0f6571993239fec249bd4f641b322be151177b40","observation_id":"665d28fc-7e0a-4b91-9bea-819a8a9b8999","resolution":{"observed_at":"2026-08-06T20:14:03.679343Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:14:03.650857Z","title":"Reducing power by optimizing the necessary precision/range of floating-point arithmetic,","venue":null,"work_id":"2e5a5a1e-3ba9-49b7-bbb1-d2f14bbea177","year":2000},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:56.728307Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:b5bcd9ec07ab4de95d43dc8a68d0ff75d4c197a16a50cff7cc8402a5730f103e","observation_id":"49d1861b-d043-4542-9b10-f059926bffa3","resolution":{"observed_at":"2026-08-06T20:14:03.656742Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:14:03.633704Z","title":"Training deep neural networks with 8-bit floating point numbers,","venue":null,"work_id":"9c97dc94-7bd4-4e99-bb4d-db5651af42c0","year":2018},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:56.806956Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:8ca91c7cfabf134fcdff6a26f7d9d35c3d7e28a3c673e67f165d66402fd3480c","observation_id":"46158820-11cd-45e7-bf58-83bf890c8ef7","resolution":{"observed_at":"2026-08-06T20:14:03.639396Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:14:03.613071Z","title":null,"venue":null,"work_id":"dcac2908-ac27-4a10-a903-c43346261359","year":1979},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:56.881060Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:9aabac8768b9df2ddea6b5b56a1cd4a832c7df812153ce77e229b18393b91910","observation_id":"2e69ea98-8fd4-4f55-82f4-22d5fa90e133","resolution":{"observed_at":"2026-08-06T20:14:03.618821Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"biblio/1113870","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:13:58.851201Z","title":"Hpcg benchmark technical specification,","venue":null,"work_id":"1d7db446-f2c1-42dc-ab8d-9bb824cc93c1","year":2013},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:56.962454Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:706f0fc767207efa79283208b2726a4f191e2e6182067cb69442ce8858755ef0","observation_id":"d6a58172-d03a-4f34-8cd1-cb064d95ff2c","resolution":{"observed_at":"2026-08-06T20:13:58.971694Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:14:03.586159Z","title":"Vector engine processor of NEC’s brand- new supercomputer SX-Aurora TSUBASA,","venue":null,"work_id":"e0d3b303-326d-4c62-b3f7-105b138dfd71","year":2018},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:57.025556Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:96813522aed44bed4e1adc618e19be04ce40bbe5969d5ef8c51232034ba53f10","observation_id":"8f3eff95-97a4-43f2-860c-22021a3f1e63","resolution":{"observed_at":"2026-08-06T20:14:03.594649Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:14:03.563105Z","title":"Oneapi deep neural network library,","venue":null,"work_id":"66b4761e-7441-492d-a2ce-9d3a16858fb8","year":2024},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:57.118276Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:48181375bec492b61de2956d88eba72e9d26e87a4123ca652cdad0db872ca01d","observation_id":"a26580aa-2f25-4600-8063-1f1426336dba","resolution":{"observed_at":"2026-08-06T20:14:03.569856Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:14:03.543696Z","title":"Pytorch: An imperative style, high-performance deep learning library,","venue":null,"work_id":"d0c1e1b8-14a0-4b64-ac6a-9c9ec3a08ca5","year":2019},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:57.192621Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:8581358924c22b4f09d61252e3bd1f8735068c711bb9784eca944d74d1352b69","observation_id":"a3bb544a-f0fd-48bc-bc14-e76061df2b88","resolution":{"observed_at":"2026-08-06T20:14:03.549461Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:14:03.292989Z","title":"Tensorflow: A system for large-scale machine learning,","venue":null,"work_id":"6c46052d-82b4-40b7-8b17-c5c06ba0f9aa","year":2016},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:57.293634Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:7e04e7049c2b16fc26a558066f1df1146741938a752839e5fec060a6c6fde94b","observation_id":"8885ef7d-3f96-4a35-a2ca-8437d1bb26c2","resolution":{"observed_at":"2026-08-06T20:14:03.454840Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:14:02.877939Z","title":"Xbyak, a c++ jit assembler for x86 (ia32), x64 (amd64, x86-64),","venue":null,"work_id":"44c49057-6f67-443e-aa2a-f1531f0b9aba","year":2024},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:57.408601Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:2145c5405409efa3129730fbe45fe7ea4222a337344c852840a8cae7cfe005c8","observation_id":"6420fd88-7d5d-4916-a6f9-005b5115e1fa","resolution":{"observed_at":"2026-08-06T20:14:03.066918Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:14:02.605768Z","title":"A binary translator to accelerate development of deep learning pro- cessing library for aarch64 cpu,","venue":null,"work_id":"1effe057-0bf8-40d0-96e7-532cc18d250f","year":2022},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:57.469464Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:f0972584797381d220d0e9da022bb4355ac54d286d5222eefc68c9bba697aafe","observation_id":"830761ff-dfde-4f1a-9b12-8776184c6b63","resolution":{"observed_at":"2026-08-06T20:14:02.753458Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:14:02.330165Z","title":"Advancing direct convolution using convo- lution slicing optimization and isa extensions,","venue":null,"work_id":"0181aab7-fdf4-4e74-a1af-e20bc25b73b8","year":2023},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:57.522956Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:56a4aea5eb0f9575074a8129eec38e81c76a2ae7c12c43684e11ec097329e106","observation_id":"d4dfdcd0-7e37-48b1-bf53-c6bac75b32a1","resolution":{"observed_at":"2026-08-06T20:14:02.475322Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:14:02.028790Z","title":"Torchvision the machine-vision package of torch,","venue":null,"work_id":"4415a879-1784-4599-a02b-5272fadddc21","year":2010},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:57.588871Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:a7b75d8d09e75ccda286513ad7350feaee54938a7d6f16ebbace557ffa0447a4","observation_id":"fc8155d7-b4d4-4379-bf10-700a5d10df04","resolution":{"observed_at":"2026-08-06T20:14:02.166197Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:14:01.736511Z","title":"Benchdnn github repository,","venue":null,"work_id":"0604a05e-5027-4b3d-b143-a2af82038173","year":2024},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:57.642353Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:4986d5f2d3b2b6c0731731aae0f80b906f9c11d32353ca030dbe89a8b1ee9d4c","observation_id":"c2f98611-acef-4e11-b898-1070a5bcbe3e","resolution":{"observed_at":"2026-08-06T20:14:01.898244Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:14:01.398375Z","title":"McPAT: An Integrated Power, Area, and Timing Modeling Framework for Multicore and Manycore Architectures,","venue":null,"work_id":"0f8fb746-79ac-41f6-aec5-f0dbdecd7daa","year":2009},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:57.730561Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:ae8928c430a977f5970146bf4d32a12eaa253ced9458dadd6b044a660257c8d0","observation_id":"957d980f-4208-4543-a74a-fd5f08508519","resolution":{"observed_at":"2026-08-06T20:14:01.564694Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:14:01.198751Z","title":"[Online]","venue":null,"work_id":"57324174-d10f-4dd5-84ea-75df9e69d32b","year":2025},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:57.775683Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:f5589f236d128c6275efaf7cea459b07ad1bc136410f522b1ebc57477605193c","observation_id":"346f2f0d-762e-49c9-88c0-0de365647191","resolution":{"observed_at":"2026-08-06T20:14:01.310276Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:14:00.971199Z","title":"Fincacti: Architectural analysis and modeling of caches with deeply-scaled finfet devices,","venue":null,"work_id":"ce9d1c06-e37b-40b4-82c7-38ba8ddcb08d","year":2014},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:57.837144Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:d5450d96a0cd225a26a119d79dbf8ee83b9ccc308a5774d7b6f14491ed7d2e7b","observation_id":"3249fcfa-45bf-4b8c-94c7-95d67395b641","resolution":{"observed_at":"2026-08-06T20:14:01.077181Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1109/isvlsi.2014.101","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"5nm finfet standard cell library optimization and circuit synthesis in near-and super-threshold voltage regimes,","venue":null,"work_id":"0b56e64a-b7b6-47d0-aa5f-1cbf18cb970d","year":2014},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:57.903775Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:9f27aa2558e31ae4705770c95ab1529e49f9436fe193f345e5ed5ff98dfbc517","observation_id":"363f0449-6288-45a8-b0dc-7efd15e19f84","resolution":{"observed_at":"2026-08-06T20:13:58.436877Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:14:00.758874Z","title":"Quantifying sources of error in McPAT and potential impacts on architectural studies,","venue":null,"work_id":"559b25d7-9648-4412-a08a-051488d8c9fd","year":2015},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:57.967039Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:3d5140b0237f9685f93264316e56cfb363ac2b547a6854437ebb24cea4e640f5","observation_id":"c4e37083-782c-438f-8a9e-d892be2f8a4d","resolution":{"observed_at":"2026-08-06T20:14:00.856326Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:14:00.510162Z","title":"intel.com/content/www/us/en/developer/articles/technical/ a-simple-example-to-measure-the-performance-of-an-intel-mkl-function","venue":null,"work_id":"c9d81d9e-ad57-4b9d-b28b-70e127e89b3f","year":2024},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:58.017203Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:e351806b968b4b94540c07dd925b2d42c33b10dc971bfb6fce806665a3304f48","observation_id":"e7c027bb-d935-49f8-badb-84b2d93d350e","resolution":{"observed_at":"2026-08-06T20:14:00.613375Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:14:00.265903Z","title":"Torchvision: Pytorch’s computer vision library,","venue":null,"work_id":"79b4cbb4-3951-47d5-b685-b0ec8b5058b7","year":2016},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:58.068488Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:12d55df7b75242c9853d3876405fe7567ec42228209ae8181c41b59bbb11e94f","observation_id":"bcca1356-1c4d-43e5-98e4-1a024e54f1ef","resolution":{"observed_at":"2026-08-06T20:14:00.366043Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:13:59.966480Z","title":"Transformers: State-of- the-art natural language processing,","venue":null,"work_id":"844553dd-16e0-4803-9397-aa8edadd9456","year":2020},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:58.149755Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:ace4c8a6361c8671708fd09c6872e8c7456fa357cb3380e2a3f4fada85b29a8e","observation_id":"5f744799-67c2-4d88-a107-f735171945bc","resolution":{"observed_at":"2026-08-06T20:14:00.124398Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:13:59.697417Z","title":"Calculation of cross-correlation function accelerated by tensorfloat-32 tensor core operations on nvidia’s ampere and hopper gpus,","venue":null,"work_id":"55d7f454-76dd-4341-a7ad-6cf2f57ea6ed","year":2023},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:58.209584Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:beedfd17ff09a73003100ea82efaba1bb136db3833e0cb4de433ca427a4d2f95","observation_id":"9f6731a7-2636-403d-b9ff-f83aba8f07e7","resolution":{"observed_at":"2026-08-06T20:13:59.849510Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:13:59.468359Z","title":"Optimizing winograd-based convolution with tensor cores,","venue":null,"work_id":"946d2cd4-3b5a-4490-a24c-30ce5c61a30b","year":2021},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:58.276067Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:a6dd01b4d119fc751dfafd0fa13cee5f09f81aa5b3a58f822d8722a6022016d7","observation_id":"036e0955-7dd9-4db4-9e54-4a6b403d3281","resolution":{"observed_at":"2026-08-06T20:13:59.550761Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-06T20:13:59.317537Z","title":"Performance evaluation of cudnn convolution algorithms on nvidia volta gpus,","venue":null,"work_id":"b92846e2-9f68-4fe3-b7c6-94c8ca85a975","year":2019},"citing_paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:58.317969Z"},"links":{"citing_paper":"/paper/2507.03522"},"observation_digest":"sha256:2e3b73b7320e2f491f7ef7c6b527ae35f1ccbb13824458c80419ee55d54b7e32","observation_id":"64f44b99-6015-418e-8c52-72cd1ecac132","resolution":{"observed_at":"2026-08-06T20:13:59.346411Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2507.03522","last_updated":"2025-07-04T12:17:00Z","latest_version":1,"primary_category":"cs.AR","snapshot_observed_at":"2026-08-13T18:52:13.061337Z","submitted_at":"2025-07-04T12:17:00Z","title":"A Flexible Instruction Set Architecture for Efficient GEMMs"},"reference_resolution":{"displayed":63,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":14,"verified_exact":5,"verified_fuzzy":44},"total_outbound_references":63},"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":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 63 of 63 outbound references and 0 inbound Pith citation observations for arXiv:2507.03522."}