{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:Y22QYTDD4KRLZD3DOYNJNIN6SE","short_pith_number":"pith:Y22QYTDD","canonical_record":{"source":{"id":"2406.11070","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-06-16T20:55:19Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"e0c32488e76cbf74a8a61f00b92da84e621026071f2d78f9374ef3e5ff748cff","abstract_canon_sha256":"b5d33c4327d60965d267c68c1ef27334795f6872596597a8c1cbcfda551a1c7b"},"schema_version":"1.0"},"canonical_sha256":"c6b50c4c63e2a2bc8f63761a96a1be9130efa44ab736f67473e6e6962be27ff7","source":{"kind":"arxiv","id":"2406.11070","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.11070","created_at":"2026-07-05T08:32:48Z"},{"alias_kind":"arxiv_version","alias_value":"2406.11070v1","created_at":"2026-07-05T08:32:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.11070","created_at":"2026-07-05T08:32:48Z"},{"alias_kind":"pith_short_12","alias_value":"Y22QYTDD4KRL","created_at":"2026-07-05T08:32:48Z"},{"alias_kind":"pith_short_16","alias_value":"Y22QYTDD4KRLZD3D","created_at":"2026-07-05T08:32:48Z"},{"alias_kind":"pith_short_8","alias_value":"Y22QYTDD","created_at":"2026-07-05T08:32:48Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:Y22QYTDD4KRLZD3DOYNJNIN6SE","target":"record","payload":{"canonical_record":{"source":{"id":"2406.11070","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-06-16T20:55:19Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"e0c32488e76cbf74a8a61f00b92da84e621026071f2d78f9374ef3e5ff748cff","abstract_canon_sha256":"b5d33c4327d60965d267c68c1ef27334795f6872596597a8c1cbcfda551a1c7b"},"schema_version":"1.0"},"canonical_sha256":"c6b50c4c63e2a2bc8f63761a96a1be9130efa44ab736f67473e6e6962be27ff7","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:32:48.537885Z","signature_b64":"NXJZfm+PjIKou6dSM7Ofgq6H7NHvsQ2tzgn8DXsk1z9XJgR0eEIYFTaNySL/ukanhmzCXu0BthAI896SD9l8DA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c6b50c4c63e2a2bc8f63761a96a1be9130efa44ab736f67473e6e6962be27ff7","last_reissued_at":"2026-07-05T08:32:48.537376Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:32:48.537376Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2406.11070","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":"2026-07-05T08:32:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BnYAMtNTVzzVMm6oUHMf7AKsN9r9mBnt4DDTR4Oj7bqOZ8hmZiYEkAhmHHywfD7J8GHOPdyz2EAuISYQvmK4Cw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T08:12:59.590915Z"},"content_sha256":"10f29c9114b129137830b232cf811d08f7f2161b46c26d623b8cd624b8308c60","schema_version":"1.0","event_id":"sha256:10f29c9114b129137830b232cf811d08f7f2161b46c26d623b8cd624b8308c60"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:Y22QYTDD4KRLZD3DOYNJNIN6SE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Fine-grained Classes and How to Find Them","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.LG","authors_text":"Artyom Gadetsky, Maria Brbi\\'c, Matej Grci\\'c","submitted_at":"2024-06-16T20:55:19Z","abstract_excerpt":"In many practical applications, coarse-grained labels are readily available compared to fine-grained labels that reflect subtle differences between classes. However, existing methods cannot leverage coarse labels to infer fine-grained labels in an unsupervised manner. To bridge this gap, we propose FALCON, a method that discovers fine-grained classes from coarsely labeled data without any supervision at the fine-grained level. FALCON simultaneously infers unknown fine-grained classes and underlying relationships between coarse and fine-grained classes. Moreover, FALCON is a modular method that"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.11070","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/2406.11070/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":"2026-07-05T08:32:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3Ql0SWkc6Xkl8dFFm/Nyp8yxqIOXvdg+KbhPGJbSt8iyOwf6qx7RSf2NOlwhwDesyRJ8JH7K7H5Jy0qytM1sDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T08:12:59.591659Z"},"content_sha256":"f0001b3c679913d33cb9448c8af28d55a256e11149a9a6350e06a3a572a06042","schema_version":"1.0","event_id":"sha256:f0001b3c679913d33cb9448c8af28d55a256e11149a9a6350e06a3a572a06042"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/Y22QYTDD4KRLZD3DOYNJNIN6SE/bundle.json","state_url":"https://pith.science/pith/Y22QYTDD4KRLZD3DOYNJNIN6SE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/Y22QYTDD4KRLZD3DOYNJNIN6SE/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":"2026-08-04T08:12:59Z","links":{"resolver":"https://pith.science/pith/Y22QYTDD4KRLZD3DOYNJNIN6SE","bundle":"https://pith.science/pith/Y22QYTDD4KRLZD3DOYNJNIN6SE/bundle.json","state":"https://pith.science/pith/Y22QYTDD4KRLZD3DOYNJNIN6SE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/Y22QYTDD4KRLZD3DOYNJNIN6SE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:Y22QYTDD4KRLZD3DOYNJNIN6SE","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":"b5d33c4327d60965d267c68c1ef27334795f6872596597a8c1cbcfda551a1c7b","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-06-16T20:55:19Z","title_canon_sha256":"e0c32488e76cbf74a8a61f00b92da84e621026071f2d78f9374ef3e5ff748cff"},"schema_version":"1.0","source":{"id":"2406.11070","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.11070","created_at":"2026-07-05T08:32:48Z"},{"alias_kind":"arxiv_version","alias_value":"2406.11070v1","created_at":"2026-07-05T08:32:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.11070","created_at":"2026-07-05T08:32:48Z"},{"alias_kind":"pith_short_12","alias_value":"Y22QYTDD4KRL","created_at":"2026-07-05T08:32:48Z"},{"alias_kind":"pith_short_16","alias_value":"Y22QYTDD4KRLZD3D","created_at":"2026-07-05T08:32:48Z"},{"alias_kind":"pith_short_8","alias_value":"Y22QYTDD","created_at":"2026-07-05T08:32:48Z"}],"graph_snapshots":[{"event_id":"sha256:f0001b3c679913d33cb9448c8af28d55a256e11149a9a6350e06a3a572a06042","target":"graph","created_at":"2026-07-05T08:32:48Z","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/2406.11070/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In many practical applications, coarse-grained labels are readily available compared to fine-grained labels that reflect subtle differences between classes. However, existing methods cannot leverage coarse labels to infer fine-grained labels in an unsupervised manner. To bridge this gap, we propose FALCON, a method that discovers fine-grained classes from coarsely labeled data without any supervision at the fine-grained level. FALCON simultaneously infers unknown fine-grained classes and underlying relationships between coarse and fine-grained classes. Moreover, FALCON is a modular method that","authors_text":"Artyom Gadetsky, Maria Brbi\\'c, Matej Grci\\'c","cross_cats":["cs.CV"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-06-16T20:55:19Z","title":"Fine-grained Classes and How to Find Them"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.11070","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":"sha256:10f29c9114b129137830b232cf811d08f7f2161b46c26d623b8cd624b8308c60","target":"record","created_at":"2026-07-05T08:32:48Z","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":"b5d33c4327d60965d267c68c1ef27334795f6872596597a8c1cbcfda551a1c7b","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-06-16T20:55:19Z","title_canon_sha256":"e0c32488e76cbf74a8a61f00b92da84e621026071f2d78f9374ef3e5ff748cff"},"schema_version":"1.0","source":{"id":"2406.11070","kind":"arxiv","version":1}},"canonical_sha256":"c6b50c4c63e2a2bc8f63761a96a1be9130efa44ab736f67473e6e6962be27ff7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c6b50c4c63e2a2bc8f63761a96a1be9130efa44ab736f67473e6e6962be27ff7","first_computed_at":"2026-07-05T08:32:48.537376Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:32:48.537376Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"NXJZfm+PjIKou6dSM7Ofgq6H7NHvsQ2tzgn8DXsk1z9XJgR0eEIYFTaNySL/ukanhmzCXu0BthAI896SD9l8DA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:32:48.537885Z","signed_message":"canonical_sha256_bytes"},"source_id":"2406.11070","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:10f29c9114b129137830b232cf811d08f7f2161b46c26d623b8cd624b8308c60","sha256:f0001b3c679913d33cb9448c8af28d55a256e11149a9a6350e06a3a572a06042"],"state_sha256":"d440443ca0f1bb0839f5693308bfe8272cb14d31acdc64fe00ad288578506895"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZOBifzVFE2C8GS7w0EhHnr72cT3pJQO2WAgh5EU82vz1jOPn4KcDZGqdqGgwtk4OL9dVWV+HrrC7GXaL0N7eAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T08:12:59.597395Z","bundle_sha256":"b69f038d3d9d01cfbcac2abe18b0e93955fadb449c378b7f995ca80dc412e098"}}