{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:3OCJUPGA46N6XV54G637PD622Q","short_pith_number":"pith:3OCJUPGA","canonical_record":{"source":{"id":"1810.12142","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-10-29T14:24:31Z","cross_cats_sorted":[],"title_canon_sha256":"05c93e5e171c495c35c730ae5a11c51b536f28fa1dbb6bcf5afe6022b0a1c76e","abstract_canon_sha256":"6e79b7e486d918c1188c3bff467af21c5e58174789c2889a08edc28b55cd99e6"},"schema_version":"1.0"},"canonical_sha256":"db849a3cc0e79bebd7bc37b7f78fdad429928793f165953dd012301bc9b92fc5","source":{"kind":"arxiv","id":"1810.12142","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1810.12142","created_at":"2026-05-17T23:57:56Z"},{"alias_kind":"arxiv_version","alias_value":"1810.12142v2","created_at":"2026-05-17T23:57:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1810.12142","created_at":"2026-05-17T23:57:56Z"},{"alias_kind":"pith_short_12","alias_value":"3OCJUPGA46N6","created_at":"2026-05-18T12:32:02Z"},{"alias_kind":"pith_short_16","alias_value":"3OCJUPGA46N6XV54","created_at":"2026-05-18T12:32:02Z"},{"alias_kind":"pith_short_8","alias_value":"3OCJUPGA","created_at":"2026-05-18T12:32:02Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:3OCJUPGA46N6XV54G637PD622Q","target":"record","payload":{"canonical_record":{"source":{"id":"1810.12142","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-10-29T14:24:31Z","cross_cats_sorted":[],"title_canon_sha256":"05c93e5e171c495c35c730ae5a11c51b536f28fa1dbb6bcf5afe6022b0a1c76e","abstract_canon_sha256":"6e79b7e486d918c1188c3bff467af21c5e58174789c2889a08edc28b55cd99e6"},"schema_version":"1.0"},"canonical_sha256":"db849a3cc0e79bebd7bc37b7f78fdad429928793f165953dd012301bc9b92fc5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:57:56.931277Z","signature_b64":"ZQCKwBWcsP3k4GvSGmtP762bTaKRyi6/Szai+3M7UwG2jXY93sOY4d8jju8NnFHlDW2Kn1E3nyswQYS4PAdgAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"db849a3cc0e79bebd7bc37b7f78fdad429928793f165953dd012301bc9b92fc5","last_reissued_at":"2026-05-17T23:57:56.930576Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:57:56.930576Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1810.12142","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":"2026-05-17T23:57:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rNx0lRpNHv3T098tKL8DWFIuMQjM/y4oXVvYWQjqQvGOCQHQSLnvlF+in+AAZxBh+6rrdSDx/nuZCOPNb8v6Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T03:02:02.174531Z"},"content_sha256":"cadb1bff1bd022a393b4f4c36234f2829c72f4bff317ff9354f8fd6ce152171e","schema_version":"1.0","event_id":"sha256:cadb1bff1bd022a393b4f4c36234f2829c72f4bff317ff9354f8fd6ce152171e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:3OCJUPGA46N6XV54G637PD622Q","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Unsupervised Data Selection for Supervised Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Andrea Leo, Daniele Della Latta, Dante Chiappino, Emiliano Ricciardi, Gabriele Valvano, Gianmarco Santini, Nicola Martini","submitted_at":"2018-10-29T14:24:31Z","abstract_excerpt":"Recent research put a big effort in the development of deep learning architectures and optimizers obtaining impressive results in areas ranging from vision to language processing. However little attention has been addressed to the need of a methodological process of data collection. In this work we hypothesize that high quality data for supervised learning can be selected in an unsupervised manner and that by doing so one can obtain models capable to generalize better than in the case of random training set construction. However, preliminary results are not robust and further studies on the su"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1810.12142","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":"2026-05-17T23:57:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4zzC/5ULsI/aDAhzRMhhZuBvj5+NpvaWvp0ShIats3wS37s10A1qr4AqKEUt+l66dz2UhIR66K7prOWW/twuCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T03:02:02.175374Z"},"content_sha256":"fdbab3882f2ec2360f50c037da1b71e03458d0a12bb82a2077e742a5b8667b37","schema_version":"1.0","event_id":"sha256:fdbab3882f2ec2360f50c037da1b71e03458d0a12bb82a2077e742a5b8667b37"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3OCJUPGA46N6XV54G637PD622Q/bundle.json","state_url":"https://pith.science/pith/3OCJUPGA46N6XV54G637PD622Q/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3OCJUPGA46N6XV54G637PD622Q/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":"2026-08-16T03:02:02Z","links":{"resolver":"https://pith.science/pith/3OCJUPGA46N6XV54G637PD622Q","bundle":"https://pith.science/pith/3OCJUPGA46N6XV54G637PD622Q/bundle.json","state":"https://pith.science/pith/3OCJUPGA46N6XV54G637PD622Q/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3OCJUPGA46N6XV54G637PD622Q/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:3OCJUPGA46N6XV54G637PD622Q","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":"6e79b7e486d918c1188c3bff467af21c5e58174789c2889a08edc28b55cd99e6","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-10-29T14:24:31Z","title_canon_sha256":"05c93e5e171c495c35c730ae5a11c51b536f28fa1dbb6bcf5afe6022b0a1c76e"},"schema_version":"1.0","source":{"id":"1810.12142","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1810.12142","created_at":"2026-05-17T23:57:56Z"},{"alias_kind":"arxiv_version","alias_value":"1810.12142v2","created_at":"2026-05-17T23:57:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1810.12142","created_at":"2026-05-17T23:57:56Z"},{"alias_kind":"pith_short_12","alias_value":"3OCJUPGA46N6","created_at":"2026-05-18T12:32:02Z"},{"alias_kind":"pith_short_16","alias_value":"3OCJUPGA46N6XV54","created_at":"2026-05-18T12:32:02Z"},{"alias_kind":"pith_short_8","alias_value":"3OCJUPGA","created_at":"2026-05-18T12:32:02Z"}],"graph_snapshots":[{"event_id":"sha256:fdbab3882f2ec2360f50c037da1b71e03458d0a12bb82a2077e742a5b8667b37","target":"graph","created_at":"2026-05-17T23:57:56Z","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":"Recent research put a big effort in the development of deep learning architectures and optimizers obtaining impressive results in areas ranging from vision to language processing. However little attention has been addressed to the need of a methodological process of data collection. In this work we hypothesize that high quality data for supervised learning can be selected in an unsupervised manner and that by doing so one can obtain models capable to generalize better than in the case of random training set construction. However, preliminary results are not robust and further studies on the su","authors_text":"Andrea Leo, Daniele Della Latta, Dante Chiappino, Emiliano Ricciardi, Gabriele Valvano, Gianmarco Santini, Nicola Martini","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-10-29T14:24:31Z","title":"Unsupervised Data Selection for Supervised Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1810.12142","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:cadb1bff1bd022a393b4f4c36234f2829c72f4bff317ff9354f8fd6ce152171e","target":"record","created_at":"2026-05-17T23:57:56Z","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":"6e79b7e486d918c1188c3bff467af21c5e58174789c2889a08edc28b55cd99e6","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-10-29T14:24:31Z","title_canon_sha256":"05c93e5e171c495c35c730ae5a11c51b536f28fa1dbb6bcf5afe6022b0a1c76e"},"schema_version":"1.0","source":{"id":"1810.12142","kind":"arxiv","version":2}},"canonical_sha256":"db849a3cc0e79bebd7bc37b7f78fdad429928793f165953dd012301bc9b92fc5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"db849a3cc0e79bebd7bc37b7f78fdad429928793f165953dd012301bc9b92fc5","first_computed_at":"2026-05-17T23:57:56.930576Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:57:56.930576Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ZQCKwBWcsP3k4GvSGmtP762bTaKRyi6/Szai+3M7UwG2jXY93sOY4d8jju8NnFHlDW2Kn1E3nyswQYS4PAdgAg==","signature_status":"signed_v1","signed_at":"2026-05-17T23:57:56.931277Z","signed_message":"canonical_sha256_bytes"},"source_id":"1810.12142","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:cadb1bff1bd022a393b4f4c36234f2829c72f4bff317ff9354f8fd6ce152171e","sha256:fdbab3882f2ec2360f50c037da1b71e03458d0a12bb82a2077e742a5b8667b37"],"state_sha256":"580f1fc1f7108df843c2ef032b4276dcae7cff87a73001c2e1d5e1e9916bee3e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NwoGuYGLl6GTJAJF0rd1Z+XdKHtmrFQ0nUhHFnstSwKn0Z3hcwJ3GCsvrw8eejJFq3OUpfiBTsHzYLzuqnL3Bg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-16T03:02:02.182629Z","bundle_sha256":"2a3b3e83588c82cff31581b94b45052aef46e377079cce2cc692d2ed67aa1274"}}