{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:MW2RHVGSBO3FNA737M3ZTASYC6","short_pith_number":"pith:MW2RHVGS","canonical_record":{"source":{"id":"2205.11169","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-05-23T10:17:53Z","cross_cats_sorted":["cs.AI","cs.CL"],"title_canon_sha256":"8eb69de7c86b36bce9bd08ce4fd59f40af8ef1335fac2cc4a1d96d04eb98e2b2","abstract_canon_sha256":"f9204c705cc304a37332b3a36003cce92954be84d53a455bb81df566a36e3cd6"},"schema_version":"1.0"},"canonical_sha256":"65b513d4d20bb65683fbfb379982581787001c5b335b737b4018e1dac4719a64","source":{"kind":"arxiv","id":"2205.11169","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.11169","created_at":"2026-07-05T05:18:03Z"},{"alias_kind":"arxiv_version","alias_value":"2205.11169v2","created_at":"2026-07-05T05:18:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.11169","created_at":"2026-07-05T05:18:03Z"},{"alias_kind":"pith_short_12","alias_value":"MW2RHVGSBO3F","created_at":"2026-07-05T05:18:03Z"},{"alias_kind":"pith_short_16","alias_value":"MW2RHVGSBO3FNA73","created_at":"2026-07-05T05:18:03Z"},{"alias_kind":"pith_short_8","alias_value":"MW2RHVGS","created_at":"2026-07-05T05:18:03Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:MW2RHVGSBO3FNA737M3ZTASYC6","target":"record","payload":{"canonical_record":{"source":{"id":"2205.11169","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-05-23T10:17:53Z","cross_cats_sorted":["cs.AI","cs.CL"],"title_canon_sha256":"8eb69de7c86b36bce9bd08ce4fd59f40af8ef1335fac2cc4a1d96d04eb98e2b2","abstract_canon_sha256":"f9204c705cc304a37332b3a36003cce92954be84d53a455bb81df566a36e3cd6"},"schema_version":"1.0"},"canonical_sha256":"65b513d4d20bb65683fbfb379982581787001c5b335b737b4018e1dac4719a64","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:18:03.784372Z","signature_b64":"Mtc7Sw4JYoeUifXdlfuJOEfG3tqyVKZ/GOfjwXX2preERyolQv4DvdmOlQlPt01k97diA/KMwWauGIgWj0iLAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"65b513d4d20bb65683fbfb379982581787001c5b335b737b4018e1dac4719a64","last_reissued_at":"2026-07-05T05:18:03.783937Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:18:03.783937Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2205.11169","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":"2026-07-05T05:18:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KHxOq72HJJTRIS9UmKAUnifZUoUbVdkIYDLbONiW99c6EYZvgbBsf94dn0n04fw1bwsZ+nq6BJuidfujW0IlBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T04:19:12.408233Z"},"content_sha256":"3178bdc92495065959243937c40be2866bbf6a606cd51d244b7552e4b3471643","schema_version":"1.0","event_id":"sha256:3178bdc92495065959243937c40be2866bbf6a606cd51d244b7552e4b3471643"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:MW2RHVGSBO3FNA737M3ZTASYC6","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"PEVL: Position-enhanced Pre-training and Prompt Tuning for Vision-language Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.CL"],"primary_cat":"cs.CV","authors_text":"Ao Zhang, Maosong Sun, Qianyu Chen, Tat-Seng Chua, Wei Ji, Yuan Yao, Zhiyuan Liu","submitted_at":"2022-05-23T10:17:53Z","abstract_excerpt":"Vision-language pre-training (VLP) has shown impressive performance on a wide range of cross-modal tasks, where VLP models without reliance on object detectors are becoming the mainstream due to their superior computation efficiency and competitive performance. However, the removal of object detectors also deprives the capability of VLP models in explicit object modeling, which is essential to various position-sensitive vision-language (VL) tasks, such as referring expression comprehension and visual commonsense reasoning. To address the challenge, we introduce PEVL that enhances the pre-train"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.11169","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2205.11169/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":"2026-07-05T05:18:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CULpYm08fvZGBkrCoN1eQZL+mM5+9Zil+wIHPcyObsbX9i7mePgp+Iha7EPbNSm/8ocYIRI2pBYSejIjQrPHBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T04:19:12.408771Z"},"content_sha256":"0d0e0aa05321fc85b825244ed4f1b83433b3f9a8f66f588ed252baeff71e68ee","schema_version":"1.0","event_id":"sha256:0d0e0aa05321fc85b825244ed4f1b83433b3f9a8f66f588ed252baeff71e68ee"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MW2RHVGSBO3FNA737M3ZTASYC6/bundle.json","state_url":"https://pith.science/pith/MW2RHVGSBO3FNA737M3ZTASYC6/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MW2RHVGSBO3FNA737M3ZTASYC6/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":"2026-08-11T04:19:12Z","links":{"resolver":"https://pith.science/pith/MW2RHVGSBO3FNA737M3ZTASYC6","bundle":"https://pith.science/pith/MW2RHVGSBO3FNA737M3ZTASYC6/bundle.json","state":"https://pith.science/pith/MW2RHVGSBO3FNA737M3ZTASYC6/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MW2RHVGSBO3FNA737M3ZTASYC6/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:MW2RHVGSBO3FNA737M3ZTASYC6","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":"f9204c705cc304a37332b3a36003cce92954be84d53a455bb81df566a36e3cd6","cross_cats_sorted":["cs.AI","cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-05-23T10:17:53Z","title_canon_sha256":"8eb69de7c86b36bce9bd08ce4fd59f40af8ef1335fac2cc4a1d96d04eb98e2b2"},"schema_version":"1.0","source":{"id":"2205.11169","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.11169","created_at":"2026-07-05T05:18:03Z"},{"alias_kind":"arxiv_version","alias_value":"2205.11169v2","created_at":"2026-07-05T05:18:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.11169","created_at":"2026-07-05T05:18:03Z"},{"alias_kind":"pith_short_12","alias_value":"MW2RHVGSBO3F","created_at":"2026-07-05T05:18:03Z"},{"alias_kind":"pith_short_16","alias_value":"MW2RHVGSBO3FNA73","created_at":"2026-07-05T05:18:03Z"},{"alias_kind":"pith_short_8","alias_value":"MW2RHVGS","created_at":"2026-07-05T05:18:03Z"}],"graph_snapshots":[{"event_id":"sha256:0d0e0aa05321fc85b825244ed4f1b83433b3f9a8f66f588ed252baeff71e68ee","target":"graph","created_at":"2026-07-05T05:18:03Z","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/2205.11169/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Vision-language pre-training (VLP) has shown impressive performance on a wide range of cross-modal tasks, where VLP models without reliance on object detectors are becoming the mainstream due to their superior computation efficiency and competitive performance. However, the removal of object detectors also deprives the capability of VLP models in explicit object modeling, which is essential to various position-sensitive vision-language (VL) tasks, such as referring expression comprehension and visual commonsense reasoning. To address the challenge, we introduce PEVL that enhances the pre-train","authors_text":"Ao Zhang, Maosong Sun, Qianyu Chen, Tat-Seng Chua, Wei Ji, Yuan Yao, Zhiyuan Liu","cross_cats":["cs.AI","cs.CL"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-05-23T10:17:53Z","title":"PEVL: Position-enhanced Pre-training and Prompt Tuning for Vision-language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.11169","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":"sha256:3178bdc92495065959243937c40be2866bbf6a606cd51d244b7552e4b3471643","target":"record","created_at":"2026-07-05T05:18:03Z","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":"f9204c705cc304a37332b3a36003cce92954be84d53a455bb81df566a36e3cd6","cross_cats_sorted":["cs.AI","cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-05-23T10:17:53Z","title_canon_sha256":"8eb69de7c86b36bce9bd08ce4fd59f40af8ef1335fac2cc4a1d96d04eb98e2b2"},"schema_version":"1.0","source":{"id":"2205.11169","kind":"arxiv","version":2}},"canonical_sha256":"65b513d4d20bb65683fbfb379982581787001c5b335b737b4018e1dac4719a64","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"65b513d4d20bb65683fbfb379982581787001c5b335b737b4018e1dac4719a64","first_computed_at":"2026-07-05T05:18:03.783937Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:18:03.783937Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Mtc7Sw4JYoeUifXdlfuJOEfG3tqyVKZ/GOfjwXX2preERyolQv4DvdmOlQlPt01k97diA/KMwWauGIgWj0iLAg==","signature_status":"signed_v1","signed_at":"2026-07-05T05:18:03.784372Z","signed_message":"canonical_sha256_bytes"},"source_id":"2205.11169","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3178bdc92495065959243937c40be2866bbf6a606cd51d244b7552e4b3471643","sha256:0d0e0aa05321fc85b825244ed4f1b83433b3f9a8f66f588ed252baeff71e68ee"],"state_sha256":"9e0201870e6e86223c699336f355ed5660448d67cd60e0ba7d8b27ad480c522c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"z029VyvyheHDBxliUV0cOdYn/ahTTcju607keLy1lCRz9aFR4L2eRKkymktwPuw0i8nXIpC8UmG6Mb5hIi0BBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-11T04:19:12.412967Z","bundle_sha256":"d76a8d4f014ef1ed2f4c10fc037e5b129276ee7efa40359a5cdc0401925f4724"}}