{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:2OOX2BFHL7GS6UDO4IK7LESOMP","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":"d2b41706e8fef06d20534658e54c4ed85fa242028684927cd72696beb2531676","cross_cats_sorted":["cs.AI","cs.CV","cs.NE","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-07-03T20:27:51Z","title_canon_sha256":"bc43b3343e78741e1e1ba1ea9fcea2c345ef8ba98bef1f1ad4f2bc62a519da5c"},"schema_version":"1.0","source":{"id":"1907.02124","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.02124","created_at":"2026-07-05T00:32:12Z"},{"alias_kind":"arxiv_version","alias_value":"1907.02124v2","created_at":"2026-07-05T00:32:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.02124","created_at":"2026-07-05T00:32:12Z"},{"alias_kind":"pith_short_12","alias_value":"2OOX2BFHL7GS","created_at":"2026-07-05T00:32:12Z"},{"alias_kind":"pith_short_16","alias_value":"2OOX2BFHL7GS6UDO","created_at":"2026-07-05T00:32:12Z"},{"alias_kind":"pith_short_8","alias_value":"2OOX2BFH","created_at":"2026-07-05T00:32:12Z"}],"graph_snapshots":[{"event_id":"sha256:cad42ff37eef3ad2942f1efe2d8150365a004c4c06599ad603bb35c7c3330421","target":"graph","created_at":"2026-07-05T00:32:12Z","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/1907.02124/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large deep neural network (DNN) models pose the key challenge to energy efficiency due to the significantly higher energy consumption of off-chip DRAM accesses than arithmetic or SRAM operations. It motivates the intensive research on model compression with two main approaches. Weight pruning leverages the redundancy in the number of weights and can be performed in a non-structured, which has higher flexibility and pruning rate but incurs index accesses due to irregular weights, or structured manner, which preserves the full matrix structure with lower pruning rate. Weight quantization leverag","authors_text":"Deliang Fan, Geng Yuan, Kaisheng Ma, Linfeng Zhang, Shaokai Ye, Sheng Lin, Sia Huat Tan, Xiaolong Ma, Xuehai Qian, Xue Lin, Yanzhi Wang, Zhengang Li, Zhezhi He","cross_cats":["cs.AI","cs.CV","cs.NE","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-07-03T20:27:51Z","title":"Non-Structured DNN Weight Pruning -- Is It Beneficial in Any Platform?"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.02124","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":"sha256:68e09e8204147c1fc77c054474f063ce3f7c82f90a32fce3456942c7a6c13ffe","target":"record","created_at":"2026-07-05T00:32:12Z","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":"d2b41706e8fef06d20534658e54c4ed85fa242028684927cd72696beb2531676","cross_cats_sorted":["cs.AI","cs.CV","cs.NE","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-07-03T20:27:51Z","title_canon_sha256":"bc43b3343e78741e1e1ba1ea9fcea2c345ef8ba98bef1f1ad4f2bc62a519da5c"},"schema_version":"1.0","source":{"id":"1907.02124","kind":"arxiv","version":2}},"canonical_sha256":"d39d7d04a75fcd2f506ee215f5924e63cd4614c1dabb67277b9930460fcb8d9e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d39d7d04a75fcd2f506ee215f5924e63cd4614c1dabb67277b9930460fcb8d9e","first_computed_at":"2026-07-05T00:32:12.993561Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:32:12.993561Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"BTM/IBvSTrJzVo0ufCXmH2cvJbRqdnUXoGwK0LSHtaZy4/DDO9ZbGoHORgX/k2wGT9H+1TFNXXytoB2HHoEvCA==","signature_status":"signed_v1","signed_at":"2026-07-05T00:32:12.994050Z","signed_message":"canonical_sha256_bytes"},"source_id":"1907.02124","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:68e09e8204147c1fc77c054474f063ce3f7c82f90a32fce3456942c7a6c13ffe","sha256:cad42ff37eef3ad2942f1efe2d8150365a004c4c06599ad603bb35c7c3330421"],"state_sha256":"090ccb83132498d1a1f78d7cd790813b33325050195b86711eba07c8a09005f6"}