{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:TS3HO6W7QLDHEO7UE325BIQNLE","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":"b47d03ae9b59db324d11f0d2d10f25efb20410d7d42e4cd1cf65fe2dab9a88bf","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-08-24T14:33:35Z","title_canon_sha256":"17bfc410a4ed8df0b0188ab06e5724d0b968c747440e226879e8ef8bbd0f53ad"},"schema_version":"1.0","source":{"id":"2208.11580","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2208.11580","created_at":"2026-07-05T05:31:16Z"},{"alias_kind":"arxiv_version","alias_value":"2208.11580v2","created_at":"2026-07-05T05:31:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2208.11580","created_at":"2026-07-05T05:31:16Z"},{"alias_kind":"pith_short_12","alias_value":"TS3HO6W7QLDH","created_at":"2026-07-05T05:31:16Z"},{"alias_kind":"pith_short_16","alias_value":"TS3HO6W7QLDHEO7U","created_at":"2026-07-05T05:31:16Z"},{"alias_kind":"pith_short_8","alias_value":"TS3HO6W7","created_at":"2026-07-05T05:31:16Z"}],"graph_snapshots":[{"event_id":"sha256:38ebf6a06756a5589a75e05ebfab115004b72d8adcde6cb4dcc39feb8fb40cab","target":"graph","created_at":"2026-07-05T05:31:16Z","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/2208.11580/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We consider the problem of model compression for deep neural networks (DNNs) in the challenging one-shot/post-training setting, in which we are given an accurate trained model, and must compress it without any retraining, based only on a small amount of calibration input data. This problem has become popular in view of the emerging software and hardware support for executing models compressed via pruning and/or quantization with speedup, and well-performing solutions have been proposed independently for both compression approaches. In this paper, we introduce a new compression framework which ","authors_text":"Dan Alistarh, Elias Frantar, Sidak Pal Singh","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-08-24T14:33:35Z","title":"Optimal Brain Compression: A Framework for Accurate Post-Training Quantization and Pruning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2208.11580","kind":"arxiv","version":2},"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":"sha256:36dc69bdaf6a0115767727147a80bb382b93344293b5bb207dc6dd19058a7323","target":"record","created_at":"2026-07-05T05:31:16Z","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":"b47d03ae9b59db324d11f0d2d10f25efb20410d7d42e4cd1cf65fe2dab9a88bf","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-08-24T14:33:35Z","title_canon_sha256":"17bfc410a4ed8df0b0188ab06e5724d0b968c747440e226879e8ef8bbd0f53ad"},"schema_version":"1.0","source":{"id":"2208.11580","kind":"arxiv","version":2}},"canonical_sha256":"9cb6777adf82c6723bf426f5d0a20d5914f88badc73231742eceadc273120f8d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9cb6777adf82c6723bf426f5d0a20d5914f88badc73231742eceadc273120f8d","first_computed_at":"2026-07-05T05:31:16.518772Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:31:16.518772Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"KAdrrSIc3fCOYxb4LFx2p4HbIR11bOIlsgeZhYOfCTGOyMuDw0iCMmjeMqNNd3oaO1pguUz0baO5HBoQ/GqRBg==","signature_status":"signed_v1","signed_at":"2026-07-05T05:31:16.519243Z","signed_message":"canonical_sha256_bytes"},"source_id":"2208.11580","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:36dc69bdaf6a0115767727147a80bb382b93344293b5bb207dc6dd19058a7323","sha256:38ebf6a06756a5589a75e05ebfab115004b72d8adcde6cb4dcc39feb8fb40cab"],"state_sha256":"282359744a10311ba8eeed28d7867b313ecb2e4910c0ff6de75cbd8d62d40574"}