{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:4VG42TAVLRTVVTYCU26S5G462M","short_pith_number":"pith:4VG42TAV","canonical_record":{"source":{"id":"2311.06242","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-11-10T18:59:08Z","cross_cats_sorted":[],"title_canon_sha256":"a3b56453f38b508c40e05afcea883b77dfe2d0731bf3a96effe70a1521c581d4","abstract_canon_sha256":"2ad3c57d421bb36d697d01017408ccdd23fef832452972f18c3300e80ecc3ee6"},"schema_version":"1.0"},"canonical_sha256":"e54dcd4c155c675acf02a6bd2e9b9ed333b4a3ddb00d53939dd3ec4d37371aef","source":{"kind":"arxiv","id":"2311.06242","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.06242","created_at":"2026-07-05T07:11:30Z"},{"alias_kind":"arxiv_version","alias_value":"2311.06242v1","created_at":"2026-07-05T07:11:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.06242","created_at":"2026-07-05T07:11:30Z"},{"alias_kind":"pith_short_12","alias_value":"4VG42TAVLRTV","created_at":"2026-07-05T07:11:30Z"},{"alias_kind":"pith_short_16","alias_value":"4VG42TAVLRTVVTYC","created_at":"2026-07-05T07:11:30Z"},{"alias_kind":"pith_short_8","alias_value":"4VG42TAV","created_at":"2026-07-05T07:11:30Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:4VG42TAVLRTVVTYCU26S5G462M","target":"record","payload":{"canonical_record":{"source":{"id":"2311.06242","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-11-10T18:59:08Z","cross_cats_sorted":[],"title_canon_sha256":"a3b56453f38b508c40e05afcea883b77dfe2d0731bf3a96effe70a1521c581d4","abstract_canon_sha256":"2ad3c57d421bb36d697d01017408ccdd23fef832452972f18c3300e80ecc3ee6"},"schema_version":"1.0"},"canonical_sha256":"e54dcd4c155c675acf02a6bd2e9b9ed333b4a3ddb00d53939dd3ec4d37371aef","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:11:30.251586Z","signature_b64":"gs+eg0Y4akxE1GYSbEQ8GPDqkQq+4zhhTMjYkBuxjK8qkY/zzDzPZ5CmvNhGygjAXdeEMAcYfVEU9rqcANRYDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e54dcd4c155c675acf02a6bd2e9b9ed333b4a3ddb00d53939dd3ec4d37371aef","last_reissued_at":"2026-07-05T07:11:30.251176Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:11:30.251176Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2311.06242","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":"2026-07-05T07:11:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bnuf2vk9ZAw/DRSsIBxKkVLLDJdx3ZJFL1syZZiyEl0keSdzR5fsnB3e6ZQmwcVWm5VvIh/Q5oRUz82LDzBTAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-16T11:39:47.293896Z"},"content_sha256":"940ad37d8bea6690d00ba285d090095aa4a7a83078015c62facfaff200711bfe","schema_version":"1.0","event_id":"sha256:940ad37d8bea6690d00ba285d090095aa4a7a83078015c62facfaff200711bfe"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:4VG42TAVLRTVVTYCU26S5G462M","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Florence-2: Advancing a Unified Representation for a Variety of Vision Tasks","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bin Xiao, Ce Liu, Haiping Wu, Houdong Hu, Lu Yuan, Michael Zeng, Weijian Xu, Xiyang Dai, Yumao Lu","submitted_at":"2023-11-10T18:59:08Z","abstract_excerpt":"We introduce Florence-2, a novel vision foundation model with a unified, prompt-based representation for a variety of computer vision and vision-language tasks. While existing large vision models excel in transfer learning, they struggle to perform a diversity of tasks with simple instructions, a capability that implies handling the complexity of various spatial hierarchy and semantic granularity. Florence-2 was designed to take text-prompt as task instructions and generate desirable results in text forms, whether it be captioning, object detection, grounding or segmentation. This multi-task l"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.06242","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/2311.06242/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":"2026-07-05T07:11:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tEcnuHHvI/iVj1BFADjZuUwHZrJbFojxoJVl3VTZt0Jdl9rMxIaFNDK+Qn0r1xQNquRZhoVg8AwrY6vrMsyGAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-16T11:39:47.294273Z"},"content_sha256":"5959a0284f6cb69799ed1a2564158a99db0da9d05a4af11466b3d43a39272727","schema_version":"1.0","event_id":"sha256:5959a0284f6cb69799ed1a2564158a99db0da9d05a4af11466b3d43a39272727"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4VG42TAVLRTVVTYCU26S5G462M/bundle.json","state_url":"https://pith.science/pith/4VG42TAVLRTVVTYCU26S5G462M/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4VG42TAVLRTVVTYCU26S5G462M/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":"2026-07-16T11:39:47Z","links":{"resolver":"https://pith.science/pith/4VG42TAVLRTVVTYCU26S5G462M","bundle":"https://pith.science/pith/4VG42TAVLRTVVTYCU26S5G462M/bundle.json","state":"https://pith.science/pith/4VG42TAVLRTVVTYCU26S5G462M/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4VG42TAVLRTVVTYCU26S5G462M/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:4VG42TAVLRTVVTYCU26S5G462M","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":"2ad3c57d421bb36d697d01017408ccdd23fef832452972f18c3300e80ecc3ee6","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-11-10T18:59:08Z","title_canon_sha256":"a3b56453f38b508c40e05afcea883b77dfe2d0731bf3a96effe70a1521c581d4"},"schema_version":"1.0","source":{"id":"2311.06242","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.06242","created_at":"2026-07-05T07:11:30Z"},{"alias_kind":"arxiv_version","alias_value":"2311.06242v1","created_at":"2026-07-05T07:11:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.06242","created_at":"2026-07-05T07:11:30Z"},{"alias_kind":"pith_short_12","alias_value":"4VG42TAVLRTV","created_at":"2026-07-05T07:11:30Z"},{"alias_kind":"pith_short_16","alias_value":"4VG42TAVLRTVVTYC","created_at":"2026-07-05T07:11:30Z"},{"alias_kind":"pith_short_8","alias_value":"4VG42TAV","created_at":"2026-07-05T07:11:30Z"}],"graph_snapshots":[{"event_id":"sha256:5959a0284f6cb69799ed1a2564158a99db0da9d05a4af11466b3d43a39272727","target":"graph","created_at":"2026-07-05T07:11:30Z","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/2311.06242/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We introduce Florence-2, a novel vision foundation model with a unified, prompt-based representation for a variety of computer vision and vision-language tasks. While existing large vision models excel in transfer learning, they struggle to perform a diversity of tasks with simple instructions, a capability that implies handling the complexity of various spatial hierarchy and semantic granularity. Florence-2 was designed to take text-prompt as task instructions and generate desirable results in text forms, whether it be captioning, object detection, grounding or segmentation. This multi-task l","authors_text":"Bin Xiao, Ce Liu, Haiping Wu, Houdong Hu, Lu Yuan, Michael Zeng, Weijian Xu, Xiyang Dai, Yumao Lu","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-11-10T18:59:08Z","title":"Florence-2: Advancing a Unified Representation for a Variety of Vision Tasks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.06242","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":"sha256:940ad37d8bea6690d00ba285d090095aa4a7a83078015c62facfaff200711bfe","target":"record","created_at":"2026-07-05T07:11:30Z","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":"2ad3c57d421bb36d697d01017408ccdd23fef832452972f18c3300e80ecc3ee6","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-11-10T18:59:08Z","title_canon_sha256":"a3b56453f38b508c40e05afcea883b77dfe2d0731bf3a96effe70a1521c581d4"},"schema_version":"1.0","source":{"id":"2311.06242","kind":"arxiv","version":1}},"canonical_sha256":"e54dcd4c155c675acf02a6bd2e9b9ed333b4a3ddb00d53939dd3ec4d37371aef","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e54dcd4c155c675acf02a6bd2e9b9ed333b4a3ddb00d53939dd3ec4d37371aef","first_computed_at":"2026-07-05T07:11:30.251176Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:11:30.251176Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"gs+eg0Y4akxE1GYSbEQ8GPDqkQq+4zhhTMjYkBuxjK8qkY/zzDzPZ5CmvNhGygjAXdeEMAcYfVEU9rqcANRYDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T07:11:30.251586Z","signed_message":"canonical_sha256_bytes"},"source_id":"2311.06242","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:940ad37d8bea6690d00ba285d090095aa4a7a83078015c62facfaff200711bfe","sha256:5959a0284f6cb69799ed1a2564158a99db0da9d05a4af11466b3d43a39272727"],"state_sha256":"e565e2712cfdbe5c7cc88e3566be273f6146add260412fdd565a594635e757b2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nvIn1NV8PfgaMPeAWkxr62O1SroOG6BaCflvaQzk2MlOdPjItC5g8ifvkbDzBenNDZdhmLytjwdek+lFRZsKBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-16T11:39:47.296866Z","bundle_sha256":"0634053e99277645cb3b0a39f23120fcd73f19c26a10cc6dbb56ea774f1174f3"}}