{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:V3EG5OMXD3DOF4DKKVXZCHN6YM","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":"2f81d75714009cede1e8105018dee0b1d714f99a4c56c8ed139701ec1eb4d3c0","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-10-23T13:48:53Z","title_canon_sha256":"2dee7b8c6afd7f8b2ba215a0768e4aeacd7349272a7afe9aade4ec2d6d21f155"},"schema_version":"1.0","source":{"id":"1810.09854","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1810.09854","created_at":"2026-05-18T00:02:29Z"},{"alias_kind":"arxiv_version","alias_value":"1810.09854v1","created_at":"2026-05-18T00:02:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1810.09854","created_at":"2026-05-18T00:02:29Z"},{"alias_kind":"pith_short_12","alias_value":"V3EG5OMXD3DO","created_at":"2026-05-18T12:32:56Z"},{"alias_kind":"pith_short_16","alias_value":"V3EG5OMXD3DOF4DK","created_at":"2026-05-18T12:32:56Z"},{"alias_kind":"pith_short_8","alias_value":"V3EG5OMX","created_at":"2026-05-18T12:32:56Z"}],"graph_snapshots":[{"event_id":"sha256:2b8e87e8e8cb2636280fbe23648a2253f155ddd5af1cd742a4feac40c24645aa","target":"graph","created_at":"2026-05-18T00:02:29Z","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":"Deep neural networks (DNN) are powerful models for many pattern recognition tasks, yet their high computational complexity and memory requirement limit them to applications on high-performance computing platforms. In this paper, we propose a new method to evaluate DNNs trained with 32bit floating point (float32) accuracy using only low precision integer arithmetics in combination with binary shift and clipping operations. Because hardware implementation of these operations is much simpler than high precision floating point calculation, our method can be used for an efficient DNN inference on d","authors_text":"Bin Yang, Lukas Mauch","cross_cats":["cs.AI","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-10-23T13:48:53Z","title":"Deep Neural Network inference with reduced word length"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1810.09854","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":"sha256:00e1cdcdf010904f6f3c1969af0489d5d1d2162dbbaacaa1d72c96c403e2e5b3","target":"record","created_at":"2026-05-18T00:02:29Z","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":"2f81d75714009cede1e8105018dee0b1d714f99a4c56c8ed139701ec1eb4d3c0","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-10-23T13:48:53Z","title_canon_sha256":"2dee7b8c6afd7f8b2ba215a0768e4aeacd7349272a7afe9aade4ec2d6d21f155"},"schema_version":"1.0","source":{"id":"1810.09854","kind":"arxiv","version":1}},"canonical_sha256":"aec86eb9971ec6e2f06a556f911dbec301ba91d27d73dc2f6ccc040a85d0e165","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"aec86eb9971ec6e2f06a556f911dbec301ba91d27d73dc2f6ccc040a85d0e165","first_computed_at":"2026-05-18T00:02:29.121825Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:02:29.121825Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"vhLMFSdKv7yuG0obFQA37z1iU+nHo6OpXknwQGHX/cpF3KFwYlMwn9P64tUDfVMYodb9h49YsaqjqnXrBhMxAw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:02:29.122529Z","signed_message":"canonical_sha256_bytes"},"source_id":"1810.09854","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:00e1cdcdf010904f6f3c1969af0489d5d1d2162dbbaacaa1d72c96c403e2e5b3","sha256:2b8e87e8e8cb2636280fbe23648a2253f155ddd5af1cd742a4feac40c24645aa"],"state_sha256":"c06433f5966c3b02ae2bc03434fbdf1093b5a805de62917ab5579f01d67d258d"}