{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:EYC7AMD4PVEIL5QB4AJMNVGJ4O","short_pith_number":"pith:EYC7AMD4","canonical_record":{"source":{"id":"1908.06066","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-08-16T17:26:56Z","cross_cats_sorted":[],"title_canon_sha256":"0232eaea9da9bc971f612f41d7693105b1ec4cb9bd4380c8deed0494e4b16c65","abstract_canon_sha256":"8b75898ee178dcc32e8c0e4cd975c3bce15b501f126493bcedcdf5be7b6ad372"},"schema_version":"1.0"},"canonical_sha256":"2605f0307c7d4885f601e012c6d4c9e3981902e402c25584b0509f24a8992ad1","source":{"kind":"arxiv","id":"1908.06066","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1908.06066","created_at":"2026-07-05T00:23:23Z"},{"alias_kind":"arxiv_version","alias_value":"1908.06066v3","created_at":"2026-07-05T00:23:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1908.06066","created_at":"2026-07-05T00:23:23Z"},{"alias_kind":"pith_short_12","alias_value":"EYC7AMD4PVEI","created_at":"2026-07-05T00:23:23Z"},{"alias_kind":"pith_short_16","alias_value":"EYC7AMD4PVEIL5QB","created_at":"2026-07-05T00:23:23Z"},{"alias_kind":"pith_short_8","alias_value":"EYC7AMD4","created_at":"2026-07-05T00:23:23Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:EYC7AMD4PVEIL5QB4AJMNVGJ4O","target":"record","payload":{"canonical_record":{"source":{"id":"1908.06066","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-08-16T17:26:56Z","cross_cats_sorted":[],"title_canon_sha256":"0232eaea9da9bc971f612f41d7693105b1ec4cb9bd4380c8deed0494e4b16c65","abstract_canon_sha256":"8b75898ee178dcc32e8c0e4cd975c3bce15b501f126493bcedcdf5be7b6ad372"},"schema_version":"1.0"},"canonical_sha256":"2605f0307c7d4885f601e012c6d4c9e3981902e402c25584b0509f24a8992ad1","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:23:23.656290Z","signature_b64":"DWSlAIKJMHudGE1D0ExmK4nzzKWubLfuhCG/vKtAzBFgUeqzm0ywsMO5zEPR55d+bUjGgWVkZkUN+ijSnkEZDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2605f0307c7d4885f601e012c6d4c9e3981902e402c25584b0509f24a8992ad1","last_reissued_at":"2026-07-05T00:23:23.655665Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:23:23.655665Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1908.06066","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T00:23:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"857tlzLiNicF+zPzULdDWsMtJHFG9bzdV3S0dUUnLlX9Ubwdg2VE5XxK2/Fce3PXFlL2hsuSF5YpHZYX83aECw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-22T16:52:50.493424Z"},"content_sha256":"2d5d857f44b0b2ae28eb25f7c29a566bf48532b0b04a4d5bb911873f791b054c","schema_version":"1.0","event_id":"sha256:2d5d857f44b0b2ae28eb25f7c29a566bf48532b0b04a4d5bb911873f791b054c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:EYC7AMD4PVEIL5QB4AJMNVGJ4O","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Unicoder-VL: A Universal Encoder for Vision and Language by Cross-modal Pre-training","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Daxin Jiang, Gen Li, Ming Gong, Ming Zhou, Nan Duan, Yuejian Fang","submitted_at":"2019-08-16T17:26:56Z","abstract_excerpt":"We propose Unicoder-VL, a universal encoder that aims to learn joint representations of vision and language in a pre-training manner. Borrow ideas from cross-lingual pre-trained models, such as XLM and Unicoder, both visual and linguistic contents are fed into a multi-layer Transformer for the cross-modal pre-training, where three pre-trained tasks are employed, including Masked Language Modeling (MLM), Masked Object Classification (MOC) and Visual-linguistic Matching (VLM). The first two tasks learn context-aware representations for input tokens based on linguistic and visual contents jointly"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1908.06066","kind":"arxiv","version":3},"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/1908.06066/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":"2026-07-05T00:23:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ndk5WflmC0eFIVN2tUwZUnGmF+NebgxJiRn6sFc7V1uB+ZEEkuBoO2RMXqDyPJlJ2U021j8gU6WXQSHs9dU0Cw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-22T16:52:50.493807Z"},"content_sha256":"24e01b9805bb95bc80d794b22cd047a5731a7803970f3b06f539e0925e48daab","schema_version":"1.0","event_id":"sha256:24e01b9805bb95bc80d794b22cd047a5731a7803970f3b06f539e0925e48daab"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/EYC7AMD4PVEIL5QB4AJMNVGJ4O/bundle.json","state_url":"https://pith.science/pith/EYC7AMD4PVEIL5QB4AJMNVGJ4O/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/EYC7AMD4PVEIL5QB4AJMNVGJ4O/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":"2026-07-22T16:52:50Z","links":{"resolver":"https://pith.science/pith/EYC7AMD4PVEIL5QB4AJMNVGJ4O","bundle":"https://pith.science/pith/EYC7AMD4PVEIL5QB4AJMNVGJ4O/bundle.json","state":"https://pith.science/pith/EYC7AMD4PVEIL5QB4AJMNVGJ4O/state.json","well_known_bundle":"https://pith.science/.well-known/pith/EYC7AMD4PVEIL5QB4AJMNVGJ4O/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:EYC7AMD4PVEIL5QB4AJMNVGJ4O","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":"8b75898ee178dcc32e8c0e4cd975c3bce15b501f126493bcedcdf5be7b6ad372","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-08-16T17:26:56Z","title_canon_sha256":"0232eaea9da9bc971f612f41d7693105b1ec4cb9bd4380c8deed0494e4b16c65"},"schema_version":"1.0","source":{"id":"1908.06066","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1908.06066","created_at":"2026-07-05T00:23:23Z"},{"alias_kind":"arxiv_version","alias_value":"1908.06066v3","created_at":"2026-07-05T00:23:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1908.06066","created_at":"2026-07-05T00:23:23Z"},{"alias_kind":"pith_short_12","alias_value":"EYC7AMD4PVEI","created_at":"2026-07-05T00:23:23Z"},{"alias_kind":"pith_short_16","alias_value":"EYC7AMD4PVEIL5QB","created_at":"2026-07-05T00:23:23Z"},{"alias_kind":"pith_short_8","alias_value":"EYC7AMD4","created_at":"2026-07-05T00:23:23Z"}],"graph_snapshots":[{"event_id":"sha256:24e01b9805bb95bc80d794b22cd047a5731a7803970f3b06f539e0925e48daab","target":"graph","created_at":"2026-07-05T00:23:23Z","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/1908.06066/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We propose Unicoder-VL, a universal encoder that aims to learn joint representations of vision and language in a pre-training manner. Borrow ideas from cross-lingual pre-trained models, such as XLM and Unicoder, both visual and linguistic contents are fed into a multi-layer Transformer for the cross-modal pre-training, where three pre-trained tasks are employed, including Masked Language Modeling (MLM), Masked Object Classification (MOC) and Visual-linguistic Matching (VLM). The first two tasks learn context-aware representations for input tokens based on linguistic and visual contents jointly","authors_text":"Daxin Jiang, Gen Li, Ming Gong, Ming Zhou, Nan Duan, Yuejian Fang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-08-16T17:26:56Z","title":"Unicoder-VL: A Universal Encoder for Vision and Language by Cross-modal Pre-training"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1908.06066","kind":"arxiv","version":3},"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":"sha256:2d5d857f44b0b2ae28eb25f7c29a566bf48532b0b04a4d5bb911873f791b054c","target":"record","created_at":"2026-07-05T00:23:23Z","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":"8b75898ee178dcc32e8c0e4cd975c3bce15b501f126493bcedcdf5be7b6ad372","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-08-16T17:26:56Z","title_canon_sha256":"0232eaea9da9bc971f612f41d7693105b1ec4cb9bd4380c8deed0494e4b16c65"},"schema_version":"1.0","source":{"id":"1908.06066","kind":"arxiv","version":3}},"canonical_sha256":"2605f0307c7d4885f601e012c6d4c9e3981902e402c25584b0509f24a8992ad1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2605f0307c7d4885f601e012c6d4c9e3981902e402c25584b0509f24a8992ad1","first_computed_at":"2026-07-05T00:23:23.655665Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:23:23.655665Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"DWSlAIKJMHudGE1D0ExmK4nzzKWubLfuhCG/vKtAzBFgUeqzm0ywsMO5zEPR55d+bUjGgWVkZkUN+ijSnkEZDw==","signature_status":"signed_v1","signed_at":"2026-07-05T00:23:23.656290Z","signed_message":"canonical_sha256_bytes"},"source_id":"1908.06066","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2d5d857f44b0b2ae28eb25f7c29a566bf48532b0b04a4d5bb911873f791b054c","sha256:24e01b9805bb95bc80d794b22cd047a5731a7803970f3b06f539e0925e48daab"],"state_sha256":"6403c52ad2a694704ce94755f1a7478fb9471dba8b6ed1d0a179a171dfb46874"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"l9aEcdDM1X3ao3LszdF/6sg9rnlNzL8TwEiocanP20UbziBqiA8JB7LkI+4fNF8VGvrAWe9t/RXPfDUd0YrKBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-22T16:52:50.497358Z","bundle_sha256":"023ce0d568c2793ca3648b1a7136cf6b3cfd184239903fb9e537ebe7770d681a"}}