{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:N2OKM6HO25GA66AM5BNUTILTCH","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":"adbde60006b2da9e0ef9531f7de899815c7bb67bef6f9b9b96abc0ea52a4e256","cross_cats_sorted":["cs.CV","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-02-18T22:28:34Z","title_canon_sha256":"546bb3cf96b28a0e3028eb86e66ae10e7c26001a9c982a794a18fa567334c4b0"},"schema_version":"1.0","source":{"id":"1902.06822","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1902.06822","created_at":"2026-05-17T23:50:33Z"},{"alias_kind":"arxiv_version","alias_value":"1902.06822v2","created_at":"2026-05-17T23:50:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1902.06822","created_at":"2026-05-17T23:50:33Z"},{"alias_kind":"pith_short_12","alias_value":"N2OKM6HO25GA","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_16","alias_value":"N2OKM6HO25GA66AM","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_8","alias_value":"N2OKM6HO","created_at":"2026-05-18T12:33:24Z"}],"graph_snapshots":[{"event_id":"sha256:000d0ed591bdf4cf035e30a1ca9b529138798e1c4c6fcccdefe056274d33eed1","target":"graph","created_at":"2026-05-17T23:50:33Z","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"},"paper":{"abstract_excerpt":"Recent machine learning methods use increasingly large deep neural networks to achieve state of the art results in various tasks. The gains in performance come at the cost of a substantial increase in computation and storage requirements. This makes real-time implementations on limited resources hardware a challenging task. One popular approach to address this challenge is to perform low-bit precision computations via neural network quantization. However, aggressive quantization generally entails a severe penalty in terms of accuracy, and often requires retraining of the network, or resorting ","authors_text":"Eli Kravchik, Fan Yang, Pavel Kisilev, Yoni Choukroun","cross_cats":["cs.CV","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-02-18T22:28:34Z","title":"Low-bit Quantization of Neural Networks for Efficient Inference"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1902.06822","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":"sha256:0ca4ad70dea625635bbd29b0549da614c31726f55ca6f12e857f0494827d1ec5","target":"record","created_at":"2026-05-17T23:50:33Z","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":"adbde60006b2da9e0ef9531f7de899815c7bb67bef6f9b9b96abc0ea52a4e256","cross_cats_sorted":["cs.CV","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-02-18T22:28:34Z","title_canon_sha256":"546bb3cf96b28a0e3028eb86e66ae10e7c26001a9c982a794a18fa567334c4b0"},"schema_version":"1.0","source":{"id":"1902.06822","kind":"arxiv","version":2}},"canonical_sha256":"6e9ca678eed74c0f780ce85b49a17311c25fbeb41acc33b86cb14cc92a9c4910","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6e9ca678eed74c0f780ce85b49a17311c25fbeb41acc33b86cb14cc92a9c4910","first_computed_at":"2026-05-17T23:50:33.253990Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:50:33.253990Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9464EElCjCkXxWcPrejdpaGno0ZzwzeRZOwLkAkZH/6CR0Bsl1rlEVKvyIk8hjFrufSdVHgB0sUOKJ1etO5YDA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:50:33.254556Z","signed_message":"canonical_sha256_bytes"},"source_id":"1902.06822","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0ca4ad70dea625635bbd29b0549da614c31726f55ca6f12e857f0494827d1ec5","sha256:000d0ed591bdf4cf035e30a1ca9b529138798e1c4c6fcccdefe056274d33eed1"],"state_sha256":"f11845babce4d90483c98ddba783a488b0a5f5cabbf4d84731414974589615ae"}