{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:234ZUZQERVEMFMZTNQKLVRRTIA","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":"0861d7f0136e42ecf4d9f9d74c1e8d507ad9f884b2f443cabd83621611061f82","cross_cats_sorted":["cs.CV","cs.NE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-12-29T11:06:39Z","title_canon_sha256":"c15d142280913cddc79055a57a746a2733e89cce78322eeb3c83535543e0a893"},"schema_version":"1.0","source":{"id":"1812.11337","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1812.11337","created_at":"2026-05-17T23:57:12Z"},{"alias_kind":"arxiv_version","alias_value":"1812.11337v1","created_at":"2026-05-17T23:57:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1812.11337","created_at":"2026-05-17T23:57:12Z"},{"alias_kind":"pith_short_12","alias_value":"234ZUZQERVEM","created_at":"2026-05-18T12:31:59Z"},{"alias_kind":"pith_short_16","alias_value":"234ZUZQERVEMFMZT","created_at":"2026-05-18T12:31:59Z"},{"alias_kind":"pith_short_8","alias_value":"234ZUZQE","created_at":"2026-05-18T12:31:59Z"}],"graph_snapshots":[{"event_id":"sha256:0b6fcab0689878aef9a9d136c45c0b926e9f3771e9bcdcdfdb6dc3ee78ffbdb4","target":"graph","created_at":"2026-05-17T23:57:12Z","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"},"paper":{"abstract_excerpt":"Convolutional Neural Networks (CNNs) are state-of-the-art in numerous computer vision tasks such as object classification and detection. However, the large amount of parameters they contain leads to a high computational complexity and strongly limits their usability in budget-constrained devices such as embedded devices. In this paper, we propose a combination of a new pruning technique and a quantization scheme that effectively reduce the complexity and memory usage of convolutional layers of CNNs, and replace the complex convolutional operation by a low-cost multiplexer. We perform experimen","authors_text":"Ghouthi Boukli Hacene (ELEC), Matthieu Arzel (ELEC), Nicolas Farrugia (ELEC), Vincent Gripon, Yoshua Bengio (DIRO)","cross_cats":["cs.CV","cs.NE"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-12-29T11:06:39Z","title":"Quantized Guided Pruning for Efficient Hardware Implementations of Convolutional Neural Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1812.11337","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":"sha256:69fd75b0f6c3b652ffa664a8abc37db23c4126b7e29b193f6c3e8bc6babd702a","target":"record","created_at":"2026-05-17T23:57:12Z","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":"0861d7f0136e42ecf4d9f9d74c1e8d507ad9f884b2f443cabd83621611061f82","cross_cats_sorted":["cs.CV","cs.NE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-12-29T11:06:39Z","title_canon_sha256":"c15d142280913cddc79055a57a746a2733e89cce78322eeb3c83535543e0a893"},"schema_version":"1.0","source":{"id":"1812.11337","kind":"arxiv","version":1}},"canonical_sha256":"d6f99a66048d48c2b3336c14bac633400d61eb10dec0271f231722572e5306f9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d6f99a66048d48c2b3336c14bac633400d61eb10dec0271f231722572e5306f9","first_computed_at":"2026-05-17T23:57:12.207447Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:57:12.207447Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Z2iwx/r0hw99MXqpjV7GapSe0Y1YQFv3fLm5EQnjuE8RwRzwygIlqUpZNqFChioINEMEI+LUbQnX5ECcZHpvBw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:57:12.207811Z","signed_message":"canonical_sha256_bytes"},"source_id":"1812.11337","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:69fd75b0f6c3b652ffa664a8abc37db23c4126b7e29b193f6c3e8bc6babd702a","sha256:0b6fcab0689878aef9a9d136c45c0b926e9f3771e9bcdcdfdb6dc3ee78ffbdb4"],"state_sha256":"dc541219740f19d7d0267bbd299bf9f560ae815799e753a4a836db82b6ba2e00"}