{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:LR72SRQYTMTMPZOT6GPT3Q4LOV","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"c3c412ac457b9eee93cbd1eeb54de9e3f38cddc0c751269882be942c4e90a4d0","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.ET","submitted_at":"2020-01-31T11:22:09Z","title_canon_sha256":"c28ca2979f9cf1c5cb745facd2b5ff65cb572494c5a46f0def23b8f7ed5eec9e"},"schema_version":"1.0","source":{"id":"2001.11773","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2001.11773","created_at":"2026-07-05T01:02:09Z"},{"alias_kind":"arxiv_version","alias_value":"2001.11773v1","created_at":"2026-07-05T01:02:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2001.11773","created_at":"2026-07-05T01:02:09Z"},{"alias_kind":"pith_short_12","alias_value":"LR72SRQYTMTM","created_at":"2026-07-05T01:02:09Z"},{"alias_kind":"pith_short_16","alias_value":"LR72SRQYTMTMPZOT","created_at":"2026-07-05T01:02:09Z"},{"alias_kind":"pith_short_8","alias_value":"LR72SRQY","created_at":"2026-07-05T01:02:09Z"}],"graph_snapshots":[{"event_id":"sha256:785579cb4bad4a8dc8589763b2e3fc13e39db9ec50568c9b3d0062362650ab20","target":"graph","created_at":"2026-07-05T01:02:09Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2001.11773/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep neural networks (DNNs) have revolutionized the field of artificial intelligence and have achieved unprecedented success in cognitive tasks such as image and speech recognition. Training of large DNNs, however, is computationally intensive and this has motivated the search for novel computing architectures targeting this application. A computational memory unit with nanoscale resistive memory devices organized in crossbar arrays could store the synaptic weights in their conductance states and perform the expensive weighted summations in place in a non-von Neumann manner. However, updating ","authors_text":"Abu Sebastian, Anastasios Petropoulos, Bipin Rajendran, Christophe Piveteau, Evangelos Eleftheriou, Geethan Karunaratne, Giovanni Mariani, Irem Boybat, Manuel Le Gallo, Riduan Khaddam-Aljameh, S. R. Nandakumar, Theodore Antonakopoulos, Urs Egger, Vinay Joshi","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.ET","submitted_at":"2020-01-31T11:22:09Z","title":"Mixed-precision deep learning based on computational memory"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2001.11773","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:7dc6a7b42c1f135e0f91a6055f47bab2f40aec02492b3e96cfea711a1603d40b","target":"record","created_at":"2026-07-05T01:02:09Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"c3c412ac457b9eee93cbd1eeb54de9e3f38cddc0c751269882be942c4e90a4d0","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.ET","submitted_at":"2020-01-31T11:22:09Z","title_canon_sha256":"c28ca2979f9cf1c5cb745facd2b5ff65cb572494c5a46f0def23b8f7ed5eec9e"},"schema_version":"1.0","source":{"id":"2001.11773","kind":"arxiv","version":1}},"canonical_sha256":"5c7fa946189b26c7e5d3f19f3dc38b75520ea5f5501b9a8a40ef78665debbf60","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5c7fa946189b26c7e5d3f19f3dc38b75520ea5f5501b9a8a40ef78665debbf60","first_computed_at":"2026-07-05T01:02:09.525564Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:02:09.525564Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nGOU/7g+ichrWPGfnHrE5p5IbvqJrrWz/Fiah5D9jZ+53WxrgXMZsGDgZ6cZ2YN62HjkqPe0Cpwz3efQqBTaCA==","signature_status":"signed_v1","signed_at":"2026-07-05T01:02:09.525973Z","signed_message":"canonical_sha256_bytes"},"source_id":"2001.11773","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7dc6a7b42c1f135e0f91a6055f47bab2f40aec02492b3e96cfea711a1603d40b","sha256:785579cb4bad4a8dc8589763b2e3fc13e39db9ec50568c9b3d0062362650ab20"],"state_sha256":"cfdea3eeac54d7d8b647bc3ce35ccba0c3c337df4dc98f44dbf921053de716d1"}