{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:UCZEAOGWIEGBYZ6WGRU5UFJ3EU","short_pith_number":"pith:UCZEAOGW","canonical_record":{"source":{"id":"1707.04610","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.PF","submitted_at":"2017-07-14T19:05:50Z","cross_cats_sorted":["cs.CV","cs.LG"],"title_canon_sha256":"97c021f555608a479c67d02713dedbf0b0f164a22d53b3b35ab42302e045c16c","abstract_canon_sha256":"03280c2425ee4e88045863141cec3c928290726c06eeaadfc450b48b135bd4bf"},"schema_version":"1.0"},"canonical_sha256":"a0b24038d6410c1c67d63469da153b2529397676b6286831d2f1ef8542b91e0f","source":{"kind":"arxiv","id":"1707.04610","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1707.04610","created_at":"2026-05-17T23:52:30Z"},{"alias_kind":"arxiv_version","alias_value":"1707.04610v2","created_at":"2026-05-17T23:52:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1707.04610","created_at":"2026-05-17T23:52:30Z"},{"alias_kind":"pith_short_12","alias_value":"UCZEAOGWIEGB","created_at":"2026-05-18T12:31:46Z"},{"alias_kind":"pith_short_16","alias_value":"UCZEAOGWIEGBYZ6W","created_at":"2026-05-18T12:31:46Z"},{"alias_kind":"pith_short_8","alias_value":"UCZEAOGW","created_at":"2026-05-18T12:31:46Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:UCZEAOGWIEGBYZ6WGRU5UFJ3EU","target":"record","payload":{"canonical_record":{"source":{"id":"1707.04610","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.PF","submitted_at":"2017-07-14T19:05:50Z","cross_cats_sorted":["cs.CV","cs.LG"],"title_canon_sha256":"97c021f555608a479c67d02713dedbf0b0f164a22d53b3b35ab42302e045c16c","abstract_canon_sha256":"03280c2425ee4e88045863141cec3c928290726c06eeaadfc450b48b135bd4bf"},"schema_version":"1.0"},"canonical_sha256":"a0b24038d6410c1c67d63469da153b2529397676b6286831d2f1ef8542b91e0f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:52:30.178623Z","signature_b64":"nWjk4KVsprq5u3OeV+y9o4UuLwZ2Cf/B6hbA/7GP4Y6Uifu7CUq01B5tf3Pn5TKcTudy6Xt7VRDZVcodg0RKBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a0b24038d6410c1c67d63469da153b2529397676b6286831d2f1ef8542b91e0f","last_reissued_at":"2026-05-17T23:52:30.178088Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:52:30.178088Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1707.04610","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:52:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xaP/F91NldsrSNmZoolVMUwS5mzR+tkFs8cu4HsT7bPVlKPQSyTgnh2ELIMcVL8sKGT4NCw+F8uGX3WyMraSBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-01T23:04:58.093209Z"},"content_sha256":"f6c899b35a9c7676a8a83704ce541355eecc435a763b736f5bcc7bbaed367016","schema_version":"1.0","event_id":"sha256:f6c899b35a9c7676a8a83704ce541355eecc435a763b736f5bcc7bbaed367016"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:UCZEAOGWIEGBYZ6WGRU5UFJ3EU","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Cloud-based or On-device: An Empirical Study of Mobile Deep Inference","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV","cs.LG"],"primary_cat":"cs.PF","authors_text":"Tian Guo","submitted_at":"2017-07-14T19:05:50Z","abstract_excerpt":"Modern mobile applications are benefiting significantly from the advancement in deep learning, e.g., implementing real-time image recognition and conversational system. Given a trained deep learning model, applications usually need to perform a series of matrix operations based on the input data, in order to infer possible output values. Because of computational complexity and size constraints, these trained models are often hosted in the cloud. To utilize these cloud-based models, mobile apps will have to send input data over the network. While cloud-based deep learning can provide reasonable"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1707.04610","kind":"arxiv","version":2},"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":"2026-05-17T23:52:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mIZqpgAcFCzNHdShnQIkmoxd1fRoHrwMGSrQWJH92KJRJkPfhJMjpeo5b4I7dy2Qq0DJ5WVx57MqnJE56oOhBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-01T23:04:58.093825Z"},"content_sha256":"5a2fba6922707aafeadc370681193276b4689e34d9e8e0725979b1ae01f94cd1","schema_version":"1.0","event_id":"sha256:5a2fba6922707aafeadc370681193276b4689e34d9e8e0725979b1ae01f94cd1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UCZEAOGWIEGBYZ6WGRU5UFJ3EU/bundle.json","state_url":"https://pith.science/pith/UCZEAOGWIEGBYZ6WGRU5UFJ3EU/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UCZEAOGWIEGBYZ6WGRU5UFJ3EU/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":"2026-07-01T23:04:58Z","links":{"resolver":"https://pith.science/pith/UCZEAOGWIEGBYZ6WGRU5UFJ3EU","bundle":"https://pith.science/pith/UCZEAOGWIEGBYZ6WGRU5UFJ3EU/bundle.json","state":"https://pith.science/pith/UCZEAOGWIEGBYZ6WGRU5UFJ3EU/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UCZEAOGWIEGBYZ6WGRU5UFJ3EU/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:UCZEAOGWIEGBYZ6WGRU5UFJ3EU","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":"03280c2425ee4e88045863141cec3c928290726c06eeaadfc450b48b135bd4bf","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.PF","submitted_at":"2017-07-14T19:05:50Z","title_canon_sha256":"97c021f555608a479c67d02713dedbf0b0f164a22d53b3b35ab42302e045c16c"},"schema_version":"1.0","source":{"id":"1707.04610","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1707.04610","created_at":"2026-05-17T23:52:30Z"},{"alias_kind":"arxiv_version","alias_value":"1707.04610v2","created_at":"2026-05-17T23:52:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1707.04610","created_at":"2026-05-17T23:52:30Z"},{"alias_kind":"pith_short_12","alias_value":"UCZEAOGWIEGB","created_at":"2026-05-18T12:31:46Z"},{"alias_kind":"pith_short_16","alias_value":"UCZEAOGWIEGBYZ6W","created_at":"2026-05-18T12:31:46Z"},{"alias_kind":"pith_short_8","alias_value":"UCZEAOGW","created_at":"2026-05-18T12:31:46Z"}],"graph_snapshots":[{"event_id":"sha256:5a2fba6922707aafeadc370681193276b4689e34d9e8e0725979b1ae01f94cd1","target":"graph","created_at":"2026-05-17T23:52:30Z","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":"Modern mobile applications are benefiting significantly from the advancement in deep learning, e.g., implementing real-time image recognition and conversational system. Given a trained deep learning model, applications usually need to perform a series of matrix operations based on the input data, in order to infer possible output values. Because of computational complexity and size constraints, these trained models are often hosted in the cloud. To utilize these cloud-based models, mobile apps will have to send input data over the network. While cloud-based deep learning can provide reasonable","authors_text":"Tian Guo","cross_cats":["cs.CV","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.PF","submitted_at":"2017-07-14T19:05:50Z","title":"Cloud-based or On-device: An Empirical Study of Mobile Deep Inference"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1707.04610","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:f6c899b35a9c7676a8a83704ce541355eecc435a763b736f5bcc7bbaed367016","target":"record","created_at":"2026-05-17T23:52:30Z","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":"03280c2425ee4e88045863141cec3c928290726c06eeaadfc450b48b135bd4bf","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.PF","submitted_at":"2017-07-14T19:05:50Z","title_canon_sha256":"97c021f555608a479c67d02713dedbf0b0f164a22d53b3b35ab42302e045c16c"},"schema_version":"1.0","source":{"id":"1707.04610","kind":"arxiv","version":2}},"canonical_sha256":"a0b24038d6410c1c67d63469da153b2529397676b6286831d2f1ef8542b91e0f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a0b24038d6410c1c67d63469da153b2529397676b6286831d2f1ef8542b91e0f","first_computed_at":"2026-05-17T23:52:30.178088Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:52:30.178088Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nWjk4KVsprq5u3OeV+y9o4UuLwZ2Cf/B6hbA/7GP4Y6Uifu7CUq01B5tf3Pn5TKcTudy6Xt7VRDZVcodg0RKBw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:52:30.178623Z","signed_message":"canonical_sha256_bytes"},"source_id":"1707.04610","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f6c899b35a9c7676a8a83704ce541355eecc435a763b736f5bcc7bbaed367016","sha256:5a2fba6922707aafeadc370681193276b4689e34d9e8e0725979b1ae01f94cd1"],"state_sha256":"61587b2003f91c0d311151cebd4998ad6eb19df17a74c126496a1f9f5ff5c756"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"w/HIMR7MjPili+mSg3lRnUxDOLRGb5y5R5Xxdjap6vWirBy++7F78+nlddaFQo69HuLwby8FVqL11mzgd/0NAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-01T23:04:58.097236Z","bundle_sha256":"58a4723872a0da92d4c8b28c4bc93f096fb9bfe8f476a1807a12843d3801c9bd"}}