{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:NLG444PLBHBNVD67Y2ZOOK4U7I","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":"243e796fc8152984b30f1f87c75358508118daa1f0bc0b4b12cfd770d7152e47","cross_cats_sorted":["cs.AR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-02-08T19:56:04Z","title_canon_sha256":"2677b98a755acec972ead37e3bf8cf29356d488941672a3f5f45acb8df6b1db4"},"schema_version":"1.0","source":{"id":"2102.04503","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2102.04503","created_at":"2026-07-05T02:14:14Z"},{"alias_kind":"arxiv_version","alias_value":"2102.04503v1","created_at":"2026-07-05T02:14:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2102.04503","created_at":"2026-07-05T02:14:14Z"},{"alias_kind":"pith_short_12","alias_value":"NLG444PLBHBN","created_at":"2026-07-05T02:14:14Z"},{"alias_kind":"pith_short_16","alias_value":"NLG444PLBHBNVD67","created_at":"2026-07-05T02:14:14Z"},{"alias_kind":"pith_short_8","alias_value":"NLG444PL","created_at":"2026-07-05T02:14:14Z"}],"graph_snapshots":[{"event_id":"sha256:dca09e5c8d295f29febb328cc6eed1873d7d91bdb4057567d58fa6f1dce99b59","target":"graph","created_at":"2026-07-05T02:14:14Z","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/2102.04503/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Quantization enables efficient acceleration of deep neural networks by reducing model memory footprint and exploiting low-cost integer math hardware units. Quantization maps floating-point weights and activations in a trained model to low-bitwidth integer values using scale factors. Excessive quantization, reducing precision too aggressively, results in accuracy degradation. When scale factors are shared at a coarse granularity across many dimensions of each tensor, effective precision of individual elements within the tensor are limited. To reduce quantization-related accuracy loss, we propos","authors_text":"Brian Zimmer, Brucek Khailany, Haoxing Ren, Rangharajan Venkatesan, Steve Dai, William J. Dally","cross_cats":["cs.AR"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-02-08T19:56:04Z","title":"VS-Quant: Per-vector Scaled Quantization for Accurate Low-Precision Neural Network Inference"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2102.04503","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":"sha256:542f74f4335d54253282f53a9a9c8330e579275b3aeff140d7873330a4dcee17","target":"record","created_at":"2026-07-05T02:14:14Z","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":"243e796fc8152984b30f1f87c75358508118daa1f0bc0b4b12cfd770d7152e47","cross_cats_sorted":["cs.AR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-02-08T19:56:04Z","title_canon_sha256":"2677b98a755acec972ead37e3bf8cf29356d488941672a3f5f45acb8df6b1db4"},"schema_version":"1.0","source":{"id":"2102.04503","kind":"arxiv","version":1}},"canonical_sha256":"6acdce71eb09c2da8fdfc6b2e72b94fa3f5afd5959da45eee816ff64feaf43e9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6acdce71eb09c2da8fdfc6b2e72b94fa3f5afd5959da45eee816ff64feaf43e9","first_computed_at":"2026-07-05T02:14:14.448699Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:14:14.448699Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"W0r0oThig/+zJ9N924macgE0mDywdd/LLJCA4ChLyfbdU0/HoD3SQZfMc5HOt+bkHb3L4WnNnCDiz/J8epUpCw==","signature_status":"signed_v1","signed_at":"2026-07-05T02:14:14.449092Z","signed_message":"canonical_sha256_bytes"},"source_id":"2102.04503","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:542f74f4335d54253282f53a9a9c8330e579275b3aeff140d7873330a4dcee17","sha256:dca09e5c8d295f29febb328cc6eed1873d7d91bdb4057567d58fa6f1dce99b59"],"state_sha256":"f307301fcd4f95358534eee9cb2fca484699228010ef2ea5e51a5ebf47c809f4"}