{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:EAGHO7UV7FZQOKKPSATJAQHRM2","short_pith_number":"pith:EAGHO7UV","canonical_record":{"source":{"id":"1804.04606","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-04-10T07:43:16Z","cross_cats_sorted":[],"title_canon_sha256":"594751501b5348ce2b5c396f71f89492a85df5f35e565a246c92868006524136","abstract_canon_sha256":"275eee435806e0ab0f6e5480b88235ed15ab12faef6627c0140397ccd503a9ff"},"schema_version":"1.0"},"canonical_sha256":"200c777e95f97307294f90269040f16687aa18093e6f9fc918db9025a7154fcf","source":{"kind":"arxiv","id":"1804.04606","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1804.04606","created_at":"2026-05-18T00:18:36Z"},{"alias_kind":"arxiv_version","alias_value":"1804.04606v1","created_at":"2026-05-18T00:18:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1804.04606","created_at":"2026-05-18T00:18:36Z"},{"alias_kind":"pith_short_12","alias_value":"EAGHO7UV7FZQ","created_at":"2026-05-18T12:32:22Z"},{"alias_kind":"pith_short_16","alias_value":"EAGHO7UV7FZQOKKP","created_at":"2026-05-18T12:32:22Z"},{"alias_kind":"pith_short_8","alias_value":"EAGHO7UV","created_at":"2026-05-18T12:32:22Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:EAGHO7UV7FZQOKKPSATJAQHRM2","target":"record","payload":{"canonical_record":{"source":{"id":"1804.04606","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-04-10T07:43:16Z","cross_cats_sorted":[],"title_canon_sha256":"594751501b5348ce2b5c396f71f89492a85df5f35e565a246c92868006524136","abstract_canon_sha256":"275eee435806e0ab0f6e5480b88235ed15ab12faef6627c0140397ccd503a9ff"},"schema_version":"1.0"},"canonical_sha256":"200c777e95f97307294f90269040f16687aa18093e6f9fc918db9025a7154fcf","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:18:36.803705Z","signature_b64":"hBvFw4QhtvUoUxKoukEHr3+bZXxEahewaJyblzFGAAxQkQziw4MdXLGgtTpFnw1vWSLiBOPrhIbkF2/fyVIRAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"200c777e95f97307294f90269040f16687aa18093e6f9fc918db9025a7154fcf","last_reissued_at":"2026-05-18T00:18:36.803138Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:18:36.803138Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1804.04606","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":"2026-05-18T00:18:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WRhFhoGuAYNigAZkZ0xnx+sYss9IlpKEEaQ+o9m3qVA9DuVMDlUUSrpBDMzAkXFlA8e2tD/MZyjZ8SjBAWa1BA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T11:12:05.497346Z"},"content_sha256":"beace729fa9a8a695ee9338258b7028aca4f32e40d27be6e1fc0a73f4c91e734","schema_version":"1.0","event_id":"sha256:beace729fa9a8a695ee9338258b7028aca4f32e40d27be6e1fc0a73f4c91e734"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:EAGHO7UV7FZQOKKPSATJAQHRM2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Loss Rank Mining: A General Hard Example Mining Method for Real-time Detectors","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Dongsheng Li, Hao Wu, Hao Yu, Jun Zhao, Xicheng Lu, Zhaoning Zhang, Zheng Qin","submitted_at":"2018-04-10T07:43:16Z","abstract_excerpt":"Modern object detectors usually suffer from low accuracy issues, as foregrounds always drown in tons of backgrounds and become hard examples during training. Compared with those proposal-based ones, real-time detectors are in far more serious trouble since they renounce the use of region-proposing stage which is used to filter a majority of backgrounds for achieving real-time rates. Though foregrounds as hard examples are in urgent need of being mined from tons of backgrounds, a considerable number of state-of-the-art real-time detectors, like YOLO series, have yet to profit from existing hard"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1804.04606","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":"2026-05-18T00:18:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"osSvheyE3gZTLzeICe+gZN1AxT9GbjmLIPNVRYNEEQwJVSxNEZCp1zlCSzgSw9dQVd6efw4gR1Tv0nGwgLd/Aw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T11:12:05.497777Z"},"content_sha256":"8851d622aeca2ba44f93734ff24f9d33f891f069b5a933d07fb1344cfe979308","schema_version":"1.0","event_id":"sha256:8851d622aeca2ba44f93734ff24f9d33f891f069b5a933d07fb1344cfe979308"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/EAGHO7UV7FZQOKKPSATJAQHRM2/bundle.json","state_url":"https://pith.science/pith/EAGHO7UV7FZQOKKPSATJAQHRM2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/EAGHO7UV7FZQOKKPSATJAQHRM2/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":"2026-05-25T11:12:05Z","links":{"resolver":"https://pith.science/pith/EAGHO7UV7FZQOKKPSATJAQHRM2","bundle":"https://pith.science/pith/EAGHO7UV7FZQOKKPSATJAQHRM2/bundle.json","state":"https://pith.science/pith/EAGHO7UV7FZQOKKPSATJAQHRM2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/EAGHO7UV7FZQOKKPSATJAQHRM2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:EAGHO7UV7FZQOKKPSATJAQHRM2","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":"275eee435806e0ab0f6e5480b88235ed15ab12faef6627c0140397ccd503a9ff","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-04-10T07:43:16Z","title_canon_sha256":"594751501b5348ce2b5c396f71f89492a85df5f35e565a246c92868006524136"},"schema_version":"1.0","source":{"id":"1804.04606","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1804.04606","created_at":"2026-05-18T00:18:36Z"},{"alias_kind":"arxiv_version","alias_value":"1804.04606v1","created_at":"2026-05-18T00:18:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1804.04606","created_at":"2026-05-18T00:18:36Z"},{"alias_kind":"pith_short_12","alias_value":"EAGHO7UV7FZQ","created_at":"2026-05-18T12:32:22Z"},{"alias_kind":"pith_short_16","alias_value":"EAGHO7UV7FZQOKKP","created_at":"2026-05-18T12:32:22Z"},{"alias_kind":"pith_short_8","alias_value":"EAGHO7UV","created_at":"2026-05-18T12:32:22Z"}],"graph_snapshots":[{"event_id":"sha256:8851d622aeca2ba44f93734ff24f9d33f891f069b5a933d07fb1344cfe979308","target":"graph","created_at":"2026-05-18T00:18:36Z","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 object detectors usually suffer from low accuracy issues, as foregrounds always drown in tons of backgrounds and become hard examples during training. Compared with those proposal-based ones, real-time detectors are in far more serious trouble since they renounce the use of region-proposing stage which is used to filter a majority of backgrounds for achieving real-time rates. Though foregrounds as hard examples are in urgent need of being mined from tons of backgrounds, a considerable number of state-of-the-art real-time detectors, like YOLO series, have yet to profit from existing hard","authors_text":"Dongsheng Li, Hao Wu, Hao Yu, Jun Zhao, Xicheng Lu, Zhaoning Zhang, Zheng Qin","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-04-10T07:43:16Z","title":"Loss Rank Mining: A General Hard Example Mining Method for Real-time Detectors"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1804.04606","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:beace729fa9a8a695ee9338258b7028aca4f32e40d27be6e1fc0a73f4c91e734","target":"record","created_at":"2026-05-18T00:18:36Z","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":"275eee435806e0ab0f6e5480b88235ed15ab12faef6627c0140397ccd503a9ff","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-04-10T07:43:16Z","title_canon_sha256":"594751501b5348ce2b5c396f71f89492a85df5f35e565a246c92868006524136"},"schema_version":"1.0","source":{"id":"1804.04606","kind":"arxiv","version":1}},"canonical_sha256":"200c777e95f97307294f90269040f16687aa18093e6f9fc918db9025a7154fcf","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"200c777e95f97307294f90269040f16687aa18093e6f9fc918db9025a7154fcf","first_computed_at":"2026-05-18T00:18:36.803138Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:18:36.803138Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"hBvFw4QhtvUoUxKoukEHr3+bZXxEahewaJyblzFGAAxQkQziw4MdXLGgtTpFnw1vWSLiBOPrhIbkF2/fyVIRAQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:18:36.803705Z","signed_message":"canonical_sha256_bytes"},"source_id":"1804.04606","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:beace729fa9a8a695ee9338258b7028aca4f32e40d27be6e1fc0a73f4c91e734","sha256:8851d622aeca2ba44f93734ff24f9d33f891f069b5a933d07fb1344cfe979308"],"state_sha256":"b5da8853be8f0fcea29635ba19f31d63842b9753452b87a69381d5840300461b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ezRMEqKRcrKzg36n7/oPERQk4fMXx5YQmjjArX/nUJHjf/MQu7FWIyFSZfptia7nM6Am7l2mff9PFMN8PR6cCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-25T11:12:05.500638Z","bundle_sha256":"88e231d7d36f50572712f7fd1b78ea7e2103a1e7120725e1b2eb4eb0b2cf75db"}}