{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:2NWLR56UEMYD3536TW6RLW73VV","short_pith_number":"pith:2NWLR56U","canonical_record":{"source":{"id":"1905.00571","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-05-02T04:37:27Z","cross_cats_sorted":["cs.CV","stat.ML"],"title_canon_sha256":"249fe208be915ca9077d085f8a097422ea52220883994779e004d5a4ccd14d38","abstract_canon_sha256":"516bf1378ab233bd134c9844faab6fd48b219676b57f9978b81498f32142191b"},"schema_version":"1.0"},"canonical_sha256":"d36cb8f7d423303df77e9dbd15dbfbad50dbaa19ab3d910654b0d7227dd83ca9","source":{"kind":"arxiv","id":"1905.00571","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1905.00571","created_at":"2026-05-17T23:47:11Z"},{"alias_kind":"arxiv_version","alias_value":"1905.00571v1","created_at":"2026-05-17T23:47:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1905.00571","created_at":"2026-05-17T23:47:11Z"},{"alias_kind":"pith_short_12","alias_value":"2NWLR56UEMYD","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_16","alias_value":"2NWLR56UEMYD3536","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_8","alias_value":"2NWLR56U","created_at":"2026-05-18T12:33:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:2NWLR56UEMYD3536TW6RLW73VV","target":"record","payload":{"canonical_record":{"source":{"id":"1905.00571","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-05-02T04:37:27Z","cross_cats_sorted":["cs.CV","stat.ML"],"title_canon_sha256":"249fe208be915ca9077d085f8a097422ea52220883994779e004d5a4ccd14d38","abstract_canon_sha256":"516bf1378ab233bd134c9844faab6fd48b219676b57f9978b81498f32142191b"},"schema_version":"1.0"},"canonical_sha256":"d36cb8f7d423303df77e9dbd15dbfbad50dbaa19ab3d910654b0d7227dd83ca9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:47:11.527905Z","signature_b64":"f0RbUXL8BIzVS3+iy/6CezQnIbph6HO2aymTVVqjDn4HFTJGCDJ139Utg1dgyO5BZLRzXNfGm9bLTgcMeRz3Dw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d36cb8f7d423303df77e9dbd15dbfbad50dbaa19ab3d910654b0d7227dd83ca9","last_reissued_at":"2026-05-17T23:47:11.527514Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:47:11.527514Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1905.00571","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:47:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/FalNUDBk78fBFmCQVPiFOoBR6HC8UKh5VrpPL/5aTwiqG5WckMC3eqkWgO4xs167v6TLAZFgurEUfiinzIKBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T02:39:31.649702Z"},"content_sha256":"956a85963200c3036ddf482439d5063b75289743a3c223082617a8234ff44438","schema_version":"1.0","event_id":"sha256:956a85963200c3036ddf482439d5063b75289743a3c223082617a8234ff44438"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:2NWLR56UEMYD3536TW6RLW73VV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"26ms Inference Time for ResNet-50: Towards Real-Time Execution of all DNNs on Smartphone","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV","stat.ML"],"primary_cat":"cs.LG","authors_text":"Bin Ren, Wei Niu, Xiaolong Ma, Yanzhi Wang","submitted_at":"2019-05-02T04:37:27Z","abstract_excerpt":"With the rapid emergence of a spectrum of high-end mobile devices, many applications that required desktop-level computation capability formerly can now run on these devices without any problem. However, without a careful optimization, executing Deep Neural Networks (a key building block of the real-time video stream processing that is the foundation of many popular applications) is still challenging, specifically, if an extremely low latency or high accuracy inference is needed. This work presents CADNN, a programming framework to efficiently execute DNN on mobile devices with the help of adv"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1905.00571","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:47:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KygQP1C9HV5pphgk8gYSj10p1bdASZL+WCy/kfWcAmfyp+UIzcCAwsvRrQgEiy8e5YjMhrT26oA2V/x7GyuRBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T02:39:31.650203Z"},"content_sha256":"269dd7d55c87d29ddd0b8abe10eec899e6e03d11a9ec550b352185b7e080f1fb","schema_version":"1.0","event_id":"sha256:269dd7d55c87d29ddd0b8abe10eec899e6e03d11a9ec550b352185b7e080f1fb"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2NWLR56UEMYD3536TW6RLW73VV/bundle.json","state_url":"https://pith.science/pith/2NWLR56UEMYD3536TW6RLW73VV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2NWLR56UEMYD3536TW6RLW73VV/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-05-27T02:39:31Z","links":{"resolver":"https://pith.science/pith/2NWLR56UEMYD3536TW6RLW73VV","bundle":"https://pith.science/pith/2NWLR56UEMYD3536TW6RLW73VV/bundle.json","state":"https://pith.science/pith/2NWLR56UEMYD3536TW6RLW73VV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2NWLR56UEMYD3536TW6RLW73VV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:2NWLR56UEMYD3536TW6RLW73VV","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":"516bf1378ab233bd134c9844faab6fd48b219676b57f9978b81498f32142191b","cross_cats_sorted":["cs.CV","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-05-02T04:37:27Z","title_canon_sha256":"249fe208be915ca9077d085f8a097422ea52220883994779e004d5a4ccd14d38"},"schema_version":"1.0","source":{"id":"1905.00571","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1905.00571","created_at":"2026-05-17T23:47:11Z"},{"alias_kind":"arxiv_version","alias_value":"1905.00571v1","created_at":"2026-05-17T23:47:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1905.00571","created_at":"2026-05-17T23:47:11Z"},{"alias_kind":"pith_short_12","alias_value":"2NWLR56UEMYD","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_16","alias_value":"2NWLR56UEMYD3536","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_8","alias_value":"2NWLR56U","created_at":"2026-05-18T12:33:07Z"}],"graph_snapshots":[{"event_id":"sha256:269dd7d55c87d29ddd0b8abe10eec899e6e03d11a9ec550b352185b7e080f1fb","target":"graph","created_at":"2026-05-17T23:47:11Z","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":"With the rapid emergence of a spectrum of high-end mobile devices, many applications that required desktop-level computation capability formerly can now run on these devices without any problem. However, without a careful optimization, executing Deep Neural Networks (a key building block of the real-time video stream processing that is the foundation of many popular applications) is still challenging, specifically, if an extremely low latency or high accuracy inference is needed. This work presents CADNN, a programming framework to efficiently execute DNN on mobile devices with the help of adv","authors_text":"Bin Ren, Wei Niu, Xiaolong Ma, Yanzhi Wang","cross_cats":["cs.CV","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-05-02T04:37:27Z","title":"26ms Inference Time for ResNet-50: Towards Real-Time Execution of all DNNs on Smartphone"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1905.00571","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":"sha256:956a85963200c3036ddf482439d5063b75289743a3c223082617a8234ff44438","target":"record","created_at":"2026-05-17T23:47:11Z","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":"516bf1378ab233bd134c9844faab6fd48b219676b57f9978b81498f32142191b","cross_cats_sorted":["cs.CV","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-05-02T04:37:27Z","title_canon_sha256":"249fe208be915ca9077d085f8a097422ea52220883994779e004d5a4ccd14d38"},"schema_version":"1.0","source":{"id":"1905.00571","kind":"arxiv","version":1}},"canonical_sha256":"d36cb8f7d423303df77e9dbd15dbfbad50dbaa19ab3d910654b0d7227dd83ca9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d36cb8f7d423303df77e9dbd15dbfbad50dbaa19ab3d910654b0d7227dd83ca9","first_computed_at":"2026-05-17T23:47:11.527514Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:47:11.527514Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"f0RbUXL8BIzVS3+iy/6CezQnIbph6HO2aymTVVqjDn4HFTJGCDJ139Utg1dgyO5BZLRzXNfGm9bLTgcMeRz3Dw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:47:11.527905Z","signed_message":"canonical_sha256_bytes"},"source_id":"1905.00571","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:956a85963200c3036ddf482439d5063b75289743a3c223082617a8234ff44438","sha256:269dd7d55c87d29ddd0b8abe10eec899e6e03d11a9ec550b352185b7e080f1fb"],"state_sha256":"2485c88b062c81a147aade317bbf717ef449f51cbc2ca3d0de5867479b72d85b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"X3G4Uwj7txGsY8yRgoyjmwkVVq6RgyqybWxmPGrTCwm5qbpaPhSKb17DuMAqGvK9AjfNPoZ0Bbe3WT/K0aF1BQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-27T02:39:31.653280Z","bundle_sha256":"49e53f6cc4d818c8cd57513f9b4caf14525e053cd4c546e65730a2d6ba000a6f"}}