{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:AZXNRHS72PX6SGKIRS7WTSIZSO","short_pith_number":"pith:AZXNRHS7","canonical_record":{"source":{"id":"1912.05361","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-12-11T14:43:18Z","cross_cats_sorted":[],"title_canon_sha256":"a3f7fc48c182ad07082f7922184e2036b4476abaaaf926ecaecf43aa6d3e7ebd","abstract_canon_sha256":"29cd9a8208c847704a367fe5c16f42e0abd920b1daa1dfb9a4c73585765f87c3"},"schema_version":"1.0"},"canonical_sha256":"066ed89e5fd3efe919488cbf69c91993bd2d81b2a219ad003ae2e7907137fa1b","source":{"kind":"arxiv","id":"1912.05361","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1912.05361","created_at":"2026-07-05T00:25:34Z"},{"alias_kind":"arxiv_version","alias_value":"1912.05361v1","created_at":"2026-07-05T00:25:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1912.05361","created_at":"2026-07-05T00:25:34Z"},{"alias_kind":"pith_short_12","alias_value":"AZXNRHS72PX6","created_at":"2026-07-05T00:25:34Z"},{"alias_kind":"pith_short_16","alias_value":"AZXNRHS72PX6SGKI","created_at":"2026-07-05T00:25:34Z"},{"alias_kind":"pith_short_8","alias_value":"AZXNRHS7","created_at":"2026-07-05T00:25:34Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:AZXNRHS72PX6SGKIRS7WTSIZSO","target":"record","payload":{"canonical_record":{"source":{"id":"1912.05361","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-12-11T14:43:18Z","cross_cats_sorted":[],"title_canon_sha256":"a3f7fc48c182ad07082f7922184e2036b4476abaaaf926ecaecf43aa6d3e7ebd","abstract_canon_sha256":"29cd9a8208c847704a367fe5c16f42e0abd920b1daa1dfb9a4c73585765f87c3"},"schema_version":"1.0"},"canonical_sha256":"066ed89e5fd3efe919488cbf69c91993bd2d81b2a219ad003ae2e7907137fa1b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:25:34.925388Z","signature_b64":"slH/oOnE2OTLv39U45CvgELjxq/cGpeNjWNxMPG3mVESADJRNrKI7jleX30oMxZ30m+u6P7rZ6TWCFa5Rd3+DA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"066ed89e5fd3efe919488cbf69c91993bd2d81b2a219ad003ae2e7907137fa1b","last_reissued_at":"2026-07-05T00:25:34.924947Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:25:34.924947Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1912.05361","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":"2026-07-05T00:25:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hjedq4zZMcY+yeSz3rY7cgv5+r2lWZ86IR4MRKOSRdcwLUcyActHuEczSfqS3k854Ndw4cB/LVL6KBBI5Js0AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T10:34:09.106096Z"},"content_sha256":"291a85164dccf2b612d4764bb998687a1fefef8b480df00927aaaee11b52c165","schema_version":"1.0","event_id":"sha256:291a85164dccf2b612d4764bb998687a1fefef8b480df00927aaaee11b52c165"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:AZXNRHS72PX6SGKIRS7WTSIZSO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Parting with Illusions about Deep Active Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Maxim Tatarchenko, \\\"Ozg\\\"un \\c{C}i\\c{c}ek, Sudhanshu Mittal, Thomas Brox","submitted_at":"2019-12-11T14:43:18Z","abstract_excerpt":"Active learning aims to reduce the high labeling cost involved in training machine learning models on large datasets by efficiently labeling only the most informative samples. Recently, deep active learning has shown success on various tasks. However, the conventional evaluation scheme used for deep active learning is below par. Current methods disregard some apparent parallel work in the closely related fields. Active learning methods are quite sensitive w.r.t. changes in the training procedure like data augmentation. They improve by a large-margin when integrated with semi-supervised learnin"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1912.05361","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/1912.05361/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":"2026-07-05T00:25:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pYlTD5Il6VGFeSKQg2LdwGxkKCDSeFhR9HZR+XeoyK4dysKPRBJq9nhaO5riC4l6DPp+F5aYgeOiZzxnWSdtBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T10:34:09.106709Z"},"content_sha256":"48c602c55464630b770bfcd6db300bcf5189bd45d49db1019aaf40ac17fd11ea","schema_version":"1.0","event_id":"sha256:48c602c55464630b770bfcd6db300bcf5189bd45d49db1019aaf40ac17fd11ea"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/AZXNRHS72PX6SGKIRS7WTSIZSO/bundle.json","state_url":"https://pith.science/pith/AZXNRHS72PX6SGKIRS7WTSIZSO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/AZXNRHS72PX6SGKIRS7WTSIZSO/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":"2026-08-09T10:34:09Z","links":{"resolver":"https://pith.science/pith/AZXNRHS72PX6SGKIRS7WTSIZSO","bundle":"https://pith.science/pith/AZXNRHS72PX6SGKIRS7WTSIZSO/bundle.json","state":"https://pith.science/pith/AZXNRHS72PX6SGKIRS7WTSIZSO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/AZXNRHS72PX6SGKIRS7WTSIZSO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:AZXNRHS72PX6SGKIRS7WTSIZSO","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":"29cd9a8208c847704a367fe5c16f42e0abd920b1daa1dfb9a4c73585765f87c3","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-12-11T14:43:18Z","title_canon_sha256":"a3f7fc48c182ad07082f7922184e2036b4476abaaaf926ecaecf43aa6d3e7ebd"},"schema_version":"1.0","source":{"id":"1912.05361","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1912.05361","created_at":"2026-07-05T00:25:34Z"},{"alias_kind":"arxiv_version","alias_value":"1912.05361v1","created_at":"2026-07-05T00:25:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1912.05361","created_at":"2026-07-05T00:25:34Z"},{"alias_kind":"pith_short_12","alias_value":"AZXNRHS72PX6","created_at":"2026-07-05T00:25:34Z"},{"alias_kind":"pith_short_16","alias_value":"AZXNRHS72PX6SGKI","created_at":"2026-07-05T00:25:34Z"},{"alias_kind":"pith_short_8","alias_value":"AZXNRHS7","created_at":"2026-07-05T00:25:34Z"}],"graph_snapshots":[{"event_id":"sha256:48c602c55464630b770bfcd6db300bcf5189bd45d49db1019aaf40ac17fd11ea","target":"graph","created_at":"2026-07-05T00:25:34Z","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/1912.05361/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Active learning aims to reduce the high labeling cost involved in training machine learning models on large datasets by efficiently labeling only the most informative samples. Recently, deep active learning has shown success on various tasks. However, the conventional evaluation scheme used for deep active learning is below par. Current methods disregard some apparent parallel work in the closely related fields. Active learning methods are quite sensitive w.r.t. changes in the training procedure like data augmentation. They improve by a large-margin when integrated with semi-supervised learnin","authors_text":"Maxim Tatarchenko, \\\"Ozg\\\"un \\c{C}i\\c{c}ek, Sudhanshu Mittal, Thomas Brox","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-12-11T14:43:18Z","title":"Parting with Illusions about Deep Active Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1912.05361","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":"sha256:291a85164dccf2b612d4764bb998687a1fefef8b480df00927aaaee11b52c165","target":"record","created_at":"2026-07-05T00:25:34Z","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":"29cd9a8208c847704a367fe5c16f42e0abd920b1daa1dfb9a4c73585765f87c3","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-12-11T14:43:18Z","title_canon_sha256":"a3f7fc48c182ad07082f7922184e2036b4476abaaaf926ecaecf43aa6d3e7ebd"},"schema_version":"1.0","source":{"id":"1912.05361","kind":"arxiv","version":1}},"canonical_sha256":"066ed89e5fd3efe919488cbf69c91993bd2d81b2a219ad003ae2e7907137fa1b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"066ed89e5fd3efe919488cbf69c91993bd2d81b2a219ad003ae2e7907137fa1b","first_computed_at":"2026-07-05T00:25:34.924947Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:25:34.924947Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"slH/oOnE2OTLv39U45CvgELjxq/cGpeNjWNxMPG3mVESADJRNrKI7jleX30oMxZ30m+u6P7rZ6TWCFa5Rd3+DA==","signature_status":"signed_v1","signed_at":"2026-07-05T00:25:34.925388Z","signed_message":"canonical_sha256_bytes"},"source_id":"1912.05361","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:291a85164dccf2b612d4764bb998687a1fefef8b480df00927aaaee11b52c165","sha256:48c602c55464630b770bfcd6db300bcf5189bd45d49db1019aaf40ac17fd11ea"],"state_sha256":"ad30a24811a5be799c922fb54aee559a6ef9cff45aa16cbc5f05858e341a7385"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Jj3RNTZHNHEdGXArR97CWA09wTXn3048z1t3pZX66zQ58uo/9S7CFep8ngngkHi2phgPgvvjYTZsFNl48i3CBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T10:34:09.110389Z","bundle_sha256":"b6a151da753b12aaa8770f548072892e501d23b9c8a1696bc453e641038af1f9"}}