{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:M5CWVXJKQ534Y2FESW7SBBSCYC","short_pith_number":"pith:M5CWVXJK","canonical_record":{"source":{"id":"1904.02365","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-04T06:06:32Z","cross_cats_sorted":[],"title_canon_sha256":"376119af8b80014854888ed55aded153a924de5baf551fca807088b1ac3e317e","abstract_canon_sha256":"f59e371ff2042b203f204ff0daa08b71a839dfcd2472aa8b131a198f047bd63f"},"schema_version":"1.0"},"canonical_sha256":"67456add2a8777cc68a495bf208642c0a3e5e3216e21f8f1cc3ca8c64f0cdc37","source":{"kind":"arxiv","id":"1904.02365","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.02365","created_at":"2026-07-05T01:04:59Z"},{"alias_kind":"arxiv_version","alias_value":"1904.02365v2","created_at":"2026-07-05T01:04:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.02365","created_at":"2026-07-05T01:04:59Z"},{"alias_kind":"pith_short_12","alias_value":"M5CWVXJKQ534","created_at":"2026-07-05T01:04:59Z"},{"alias_kind":"pith_short_16","alias_value":"M5CWVXJKQ534Y2FE","created_at":"2026-07-05T01:04:59Z"},{"alias_kind":"pith_short_8","alias_value":"M5CWVXJK","created_at":"2026-07-05T01:04:59Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:M5CWVXJKQ534Y2FESW7SBBSCYC","target":"record","payload":{"canonical_record":{"source":{"id":"1904.02365","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-04T06:06:32Z","cross_cats_sorted":[],"title_canon_sha256":"376119af8b80014854888ed55aded153a924de5baf551fca807088b1ac3e317e","abstract_canon_sha256":"f59e371ff2042b203f204ff0daa08b71a839dfcd2472aa8b131a198f047bd63f"},"schema_version":"1.0"},"canonical_sha256":"67456add2a8777cc68a495bf208642c0a3e5e3216e21f8f1cc3ca8c64f0cdc37","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:04:59.068720Z","signature_b64":"BFHiLNmDYdK0huQgEw0A53uAOEc2Uj2UJVem151uNxHVI/UeZzYcLqy2YRG1hLfAOC2MYk2PxW5jWda8d/ATAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"67456add2a8777cc68a495bf208642c0a3e5e3216e21f8f1cc3ca8c64f0cdc37","last_reissued_at":"2026-07-05T01:04:59.068209Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:04:59.068209Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1904.02365","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":"2026-07-05T01:04:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5OxYQVM9TAYLmXnhgUrEv2QQxikqdVoDapdolFgEQLnrzEvcsAZDbVjLopVfLmpoGBJhJQkrMa1hO70rIETBCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T12:46:33.961639Z"},"content_sha256":"82dcfc2da84304df9ad0f74eaf7c055e8fe70c940bd8fc16e872c00eeea32fe1","schema_version":"1.0","event_id":"sha256:82dcfc2da84304df9ad0f74eaf7c055e8fe70c940bd8fc16e872c00eeea32fe1"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:M5CWVXJKQ534Y2FESW7SBBSCYC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Template-Based Automatic Search of Compact Semantic Segmentation Architectures","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chunhua Shen, Ian Reid, Vladimir Nekrasov","submitted_at":"2019-04-04T06:06:32Z","abstract_excerpt":"Automatic search of neural architectures for various vision and natural language tasks is becoming a prominent tool as it allows to discover high-performing structures on any dataset of interest. Nevertheless, on more difficult domains, such as dense per-pixel classification, current automatic approaches are limited in their scope - due to their strong reliance on existing image classifiers they tend to search only for a handful of additional layers with discovered architectures still containing a large number of parameters. In contrast, in this work we propose a novel solution able to find li"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.02365","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/1904.02365/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2026-07-05T01:04:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"51rTxN1Udpzm61QegSdN8Xb5vC0KApyoGRJ2si53OaedPbLDZKSdf1dFuojQItZRMjgaSaWAxW+X4MXdcOHsBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T12:46:33.962152Z"},"content_sha256":"064b454e535966893472a6e8ca547a34392ff89e6a5e70b5039f5ae730f5fdbe","schema_version":"1.0","event_id":"sha256:064b454e535966893472a6e8ca547a34392ff89e6a5e70b5039f5ae730f5fdbe"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/M5CWVXJKQ534Y2FESW7SBBSCYC/bundle.json","state_url":"https://pith.science/pith/M5CWVXJKQ534Y2FESW7SBBSCYC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/M5CWVXJKQ534Y2FESW7SBBSCYC/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":"2026-08-06T12:46:33Z","links":{"resolver":"https://pith.science/pith/M5CWVXJKQ534Y2FESW7SBBSCYC","bundle":"https://pith.science/pith/M5CWVXJKQ534Y2FESW7SBBSCYC/bundle.json","state":"https://pith.science/pith/M5CWVXJKQ534Y2FESW7SBBSCYC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/M5CWVXJKQ534Y2FESW7SBBSCYC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:M5CWVXJKQ534Y2FESW7SBBSCYC","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":"f59e371ff2042b203f204ff0daa08b71a839dfcd2472aa8b131a198f047bd63f","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-04T06:06:32Z","title_canon_sha256":"376119af8b80014854888ed55aded153a924de5baf551fca807088b1ac3e317e"},"schema_version":"1.0","source":{"id":"1904.02365","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.02365","created_at":"2026-07-05T01:04:59Z"},{"alias_kind":"arxiv_version","alias_value":"1904.02365v2","created_at":"2026-07-05T01:04:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.02365","created_at":"2026-07-05T01:04:59Z"},{"alias_kind":"pith_short_12","alias_value":"M5CWVXJKQ534","created_at":"2026-07-05T01:04:59Z"},{"alias_kind":"pith_short_16","alias_value":"M5CWVXJKQ534Y2FE","created_at":"2026-07-05T01:04:59Z"},{"alias_kind":"pith_short_8","alias_value":"M5CWVXJK","created_at":"2026-07-05T01:04:59Z"}],"graph_snapshots":[{"event_id":"sha256:064b454e535966893472a6e8ca547a34392ff89e6a5e70b5039f5ae730f5fdbe","target":"graph","created_at":"2026-07-05T01:04:59Z","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/1904.02365/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Automatic search of neural architectures for various vision and natural language tasks is becoming a prominent tool as it allows to discover high-performing structures on any dataset of interest. Nevertheless, on more difficult domains, such as dense per-pixel classification, current automatic approaches are limited in their scope - due to their strong reliance on existing image classifiers they tend to search only for a handful of additional layers with discovered architectures still containing a large number of parameters. In contrast, in this work we propose a novel solution able to find li","authors_text":"Chunhua Shen, Ian Reid, Vladimir Nekrasov","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-04T06:06:32Z","title":"Template-Based Automatic Search of Compact Semantic Segmentation Architectures"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.02365","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":"sha256:82dcfc2da84304df9ad0f74eaf7c055e8fe70c940bd8fc16e872c00eeea32fe1","target":"record","created_at":"2026-07-05T01:04:59Z","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":"f59e371ff2042b203f204ff0daa08b71a839dfcd2472aa8b131a198f047bd63f","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-04T06:06:32Z","title_canon_sha256":"376119af8b80014854888ed55aded153a924de5baf551fca807088b1ac3e317e"},"schema_version":"1.0","source":{"id":"1904.02365","kind":"arxiv","version":2}},"canonical_sha256":"67456add2a8777cc68a495bf208642c0a3e5e3216e21f8f1cc3ca8c64f0cdc37","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"67456add2a8777cc68a495bf208642c0a3e5e3216e21f8f1cc3ca8c64f0cdc37","first_computed_at":"2026-07-05T01:04:59.068209Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:04:59.068209Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"BFHiLNmDYdK0huQgEw0A53uAOEc2Uj2UJVem151uNxHVI/UeZzYcLqy2YRG1hLfAOC2MYk2PxW5jWda8d/ATAg==","signature_status":"signed_v1","signed_at":"2026-07-05T01:04:59.068720Z","signed_message":"canonical_sha256_bytes"},"source_id":"1904.02365","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:82dcfc2da84304df9ad0f74eaf7c055e8fe70c940bd8fc16e872c00eeea32fe1","sha256:064b454e535966893472a6e8ca547a34392ff89e6a5e70b5039f5ae730f5fdbe"],"state_sha256":"325628d612f6399bf63ed3631ad1615418a225598661b85c6c654a665b94a9ac"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"P5OzQJeeyUwQ4MTbPageF1FKruTpSLOrcu5LM6Vs3GEzIYcW079MaEaUXiBcEuK0lngem5+hjvgZ/Vt2fv2XDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T12:46:33.965471Z","bundle_sha256":"ff7bee7097410d59b063bed3531203d98931fb37e7d50d6c3ff20c2bbc13a96a"}}