{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:T3ECIM4XSYAL2HOQRCYRFH3JQU","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":"bed41d9f1f92cbd770da211a4acba99656a6b43e92314366a05453ec3fdfedd1","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-08-30T10:06:26Z","title_canon_sha256":"0e56997263b3006bdaac797ac37273ac2f33f9a63af477c3f3a328a8f3001603"},"schema_version":"1.0","source":{"id":"2408.17163","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.17163","created_at":"2026-07-05T09:01:11Z"},{"alias_kind":"arxiv_version","alias_value":"2408.17163v1","created_at":"2026-07-05T09:01:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.17163","created_at":"2026-07-05T09:01:11Z"},{"alias_kind":"pith_short_12","alias_value":"T3ECIM4XSYAL","created_at":"2026-07-05T09:01:11Z"},{"alias_kind":"pith_short_16","alias_value":"T3ECIM4XSYAL2HOQ","created_at":"2026-07-05T09:01:11Z"},{"alias_kind":"pith_short_8","alias_value":"T3ECIM4X","created_at":"2026-07-05T09:01:11Z"}],"graph_snapshots":[{"event_id":"sha256:02ff566f1b95b079e1e10215b341c6d56362a7c1b11510c9766b5989bb312e56","target":"graph","created_at":"2026-07-05T09:01:11Z","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/2408.17163/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The rising footprint of machine learning has led to a focus on imposing \\emph{model sparsity} as a means of reducing computational and memory costs. For deep neural networks (DNNs), the state-of-the-art accuracy-vs-sparsity is achieved by heuristics inspired by the classical Optimal Brain Surgeon (OBS) framework~\\citep{lecun90brain, hassibi1992second, hassibi1993optimal}, which leverages loss curvature information to make better pruning decisions. Yet, these results still lack a solid theoretical understanding, and it is unclear whether they can be improved by leveraging connections to the wea","authors_text":"Dan Alistarh, Denis Kuznedelev, Diyuan Wu, Ionut-Vlad Modoranu, Mher Safaryan","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-08-30T10:06:26Z","title":"The Iterative Optimal Brain Surgeon: Faster Sparse Recovery by Leveraging Second-Order Information"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.17163","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":"sha256:042af4528f1e95774783d6045262f9fb5a68a640d2b677da9f84159e83c69ef1","target":"record","created_at":"2026-07-05T09:01:11Z","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":"bed41d9f1f92cbd770da211a4acba99656a6b43e92314366a05453ec3fdfedd1","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-08-30T10:06:26Z","title_canon_sha256":"0e56997263b3006bdaac797ac37273ac2f33f9a63af477c3f3a328a8f3001603"},"schema_version":"1.0","source":{"id":"2408.17163","kind":"arxiv","version":1}},"canonical_sha256":"9ec82433979600bd1dd088b1129f6985079a06a9eded2040444bb234ec92611b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9ec82433979600bd1dd088b1129f6985079a06a9eded2040444bb234ec92611b","first_computed_at":"2026-07-05T09:01:11.657815Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:01:11.657815Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"h3i3oamzvPat9MdkOsng9ts58aFJeyZtkLi0FSB0w2EscBeyD1IziHwUcBr8O2vfhWFN+dBNSXvbE1WYGMPjAw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:01:11.658216Z","signed_message":"canonical_sha256_bytes"},"source_id":"2408.17163","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:042af4528f1e95774783d6045262f9fb5a68a640d2b677da9f84159e83c69ef1","sha256:02ff566f1b95b079e1e10215b341c6d56362a7c1b11510c9766b5989bb312e56"],"state_sha256":"87d5f687ecb58995a5dcb84f7db4182eb6f32f05bdfe91289c2df3bea9162a3d"}