{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:6RCM7YHO3JRC7JLTQ2SU7WMJ3A","short_pith_number":"pith:6RCM7YHO","canonical_record":{"source":{"id":"2208.01813","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-08-03T02:18:09Z","cross_cats_sorted":[],"title_canon_sha256":"82b6021323e3827693cbd533eb5c6e24307c62b2a33c9e5c74c247bb74c65105","abstract_canon_sha256":"d621e53483098dc9c9dae7c69834ffe408f34d8562a86efebf26f6ef3abc82dc"},"schema_version":"1.0"},"canonical_sha256":"f444cfe0eeda622fa57386a54fd989d8093fd931cac3fec83275cf5e77db5c99","source":{"kind":"arxiv","id":"2208.01813","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2208.01813","created_at":"2026-07-05T05:04:30Z"},{"alias_kind":"arxiv_version","alias_value":"2208.01813v3","created_at":"2026-07-05T05:04:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2208.01813","created_at":"2026-07-05T05:04:30Z"},{"alias_kind":"pith_short_12","alias_value":"6RCM7YHO3JRC","created_at":"2026-07-05T05:04:30Z"},{"alias_kind":"pith_short_16","alias_value":"6RCM7YHO3JRC7JLT","created_at":"2026-07-05T05:04:30Z"},{"alias_kind":"pith_short_8","alias_value":"6RCM7YHO","created_at":"2026-07-05T05:04:30Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:6RCM7YHO3JRC7JLTQ2SU7WMJ3A","target":"record","payload":{"canonical_record":{"source":{"id":"2208.01813","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-08-03T02:18:09Z","cross_cats_sorted":[],"title_canon_sha256":"82b6021323e3827693cbd533eb5c6e24307c62b2a33c9e5c74c247bb74c65105","abstract_canon_sha256":"d621e53483098dc9c9dae7c69834ffe408f34d8562a86efebf26f6ef3abc82dc"},"schema_version":"1.0"},"canonical_sha256":"f444cfe0eeda622fa57386a54fd989d8093fd931cac3fec83275cf5e77db5c99","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:04:30.590764Z","signature_b64":"IVfnW+G38O0c5pRyZPIa/QoT/6FoMe9aLE6f6I0L9cEGO1rEfDmGb6i1yOrjNJlTamxJKeI/5VOQ4uH9CAQrDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f444cfe0eeda622fa57386a54fd989d8093fd931cac3fec83275cf5e77db5c99","last_reissued_at":"2026-07-05T05:04:30.590338Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:04:30.590338Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2208.01813","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":"2026-07-05T05:04:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DnBEsGRVt/FoERu65sAESselam2iEFrGtaQbk/OURAAGU4Mdp8Hc6WTjG1QoAUYphFikHnGZsfqEdrxgRxCGAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T15:32:45.205601Z"},"content_sha256":"18e4157417b388c1d559a8d4cf8c795f34cfe90bab2a7b2a772b3f69d9d6b276","schema_version":"1.0","event_id":"sha256:18e4157417b388c1d559a8d4cf8c795f34cfe90bab2a7b2a772b3f69d9d6b276"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:6RCM7YHO3JRC7JLTQ2SU7WMJ3A","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"TAG: Boosting Text-VQA via Text-aware Visual Question-answer Generation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chetan Ramaiah, Joseph F. JaJa, Jun Wang, Larry S. Davis, Mingfei Gao, Ramprasaath R. Selvaraju, Ran Xu, Yuqian Hu","submitted_at":"2022-08-03T02:18:09Z","abstract_excerpt":"Text-VQA aims at answering questions that require understanding the textual cues in an image. Despite the great progress of existing Text-VQA methods, their performance suffers from insufficient human-labeled question-answer (QA) pairs. However, we observe that, in general, the scene text is not fully exploited in the existing datasets -- only a small portion of the text in each image participates in the annotated QA activities. This results in a huge waste of useful information. To address this deficiency, we develop a new method to generate high-quality and diverse QA pairs by explicitly uti"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2208.01813","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/2208.01813/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":"2026-07-05T05:04:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9tZ62HyeT9/bgaALGasqfrAp51jJjbnRFyPJO8lvlofXbX9VNQiejVYcV7/u+I6LFQ5yl3CDI91ViA8owVxiDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T15:32:45.206113Z"},"content_sha256":"adbb23116c4836967e4423c5403757a20dccb70daccb23d318f1c41cdfc3a9dc","schema_version":"1.0","event_id":"sha256:adbb23116c4836967e4423c5403757a20dccb70daccb23d318f1c41cdfc3a9dc"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6RCM7YHO3JRC7JLTQ2SU7WMJ3A/bundle.json","state_url":"https://pith.science/pith/6RCM7YHO3JRC7JLTQ2SU7WMJ3A/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6RCM7YHO3JRC7JLTQ2SU7WMJ3A/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":"2026-08-03T15:32:45Z","links":{"resolver":"https://pith.science/pith/6RCM7YHO3JRC7JLTQ2SU7WMJ3A","bundle":"https://pith.science/pith/6RCM7YHO3JRC7JLTQ2SU7WMJ3A/bundle.json","state":"https://pith.science/pith/6RCM7YHO3JRC7JLTQ2SU7WMJ3A/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6RCM7YHO3JRC7JLTQ2SU7WMJ3A/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:6RCM7YHO3JRC7JLTQ2SU7WMJ3A","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":"d621e53483098dc9c9dae7c69834ffe408f34d8562a86efebf26f6ef3abc82dc","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-08-03T02:18:09Z","title_canon_sha256":"82b6021323e3827693cbd533eb5c6e24307c62b2a33c9e5c74c247bb74c65105"},"schema_version":"1.0","source":{"id":"2208.01813","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2208.01813","created_at":"2026-07-05T05:04:30Z"},{"alias_kind":"arxiv_version","alias_value":"2208.01813v3","created_at":"2026-07-05T05:04:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2208.01813","created_at":"2026-07-05T05:04:30Z"},{"alias_kind":"pith_short_12","alias_value":"6RCM7YHO3JRC","created_at":"2026-07-05T05:04:30Z"},{"alias_kind":"pith_short_16","alias_value":"6RCM7YHO3JRC7JLT","created_at":"2026-07-05T05:04:30Z"},{"alias_kind":"pith_short_8","alias_value":"6RCM7YHO","created_at":"2026-07-05T05:04:30Z"}],"graph_snapshots":[{"event_id":"sha256:adbb23116c4836967e4423c5403757a20dccb70daccb23d318f1c41cdfc3a9dc","target":"graph","created_at":"2026-07-05T05:04:30Z","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/2208.01813/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Text-VQA aims at answering questions that require understanding the textual cues in an image. Despite the great progress of existing Text-VQA methods, their performance suffers from insufficient human-labeled question-answer (QA) pairs. However, we observe that, in general, the scene text is not fully exploited in the existing datasets -- only a small portion of the text in each image participates in the annotated QA activities. This results in a huge waste of useful information. To address this deficiency, we develop a new method to generate high-quality and diverse QA pairs by explicitly uti","authors_text":"Chetan Ramaiah, Joseph F. JaJa, Jun Wang, Larry S. Davis, Mingfei Gao, Ramprasaath R. Selvaraju, Ran Xu, Yuqian Hu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-08-03T02:18:09Z","title":"TAG: Boosting Text-VQA via Text-aware Visual Question-answer Generation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2208.01813","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":"sha256:18e4157417b388c1d559a8d4cf8c795f34cfe90bab2a7b2a772b3f69d9d6b276","target":"record","created_at":"2026-07-05T05:04:30Z","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":"d621e53483098dc9c9dae7c69834ffe408f34d8562a86efebf26f6ef3abc82dc","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-08-03T02:18:09Z","title_canon_sha256":"82b6021323e3827693cbd533eb5c6e24307c62b2a33c9e5c74c247bb74c65105"},"schema_version":"1.0","source":{"id":"2208.01813","kind":"arxiv","version":3}},"canonical_sha256":"f444cfe0eeda622fa57386a54fd989d8093fd931cac3fec83275cf5e77db5c99","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f444cfe0eeda622fa57386a54fd989d8093fd931cac3fec83275cf5e77db5c99","first_computed_at":"2026-07-05T05:04:30.590338Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:04:30.590338Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"IVfnW+G38O0c5pRyZPIa/QoT/6FoMe9aLE6f6I0L9cEGO1rEfDmGb6i1yOrjNJlTamxJKeI/5VOQ4uH9CAQrDg==","signature_status":"signed_v1","signed_at":"2026-07-05T05:04:30.590764Z","signed_message":"canonical_sha256_bytes"},"source_id":"2208.01813","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:18e4157417b388c1d559a8d4cf8c795f34cfe90bab2a7b2a772b3f69d9d6b276","sha256:adbb23116c4836967e4423c5403757a20dccb70daccb23d318f1c41cdfc3a9dc"],"state_sha256":"8ed955e7b374f010c7739bb76e0e4c477d556cbd916594aa4ae6e5c2c6933566"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"htvYjV3ZKVtfYTrB95yY0IVPW1Q3wfBGYe1n3a0aM1w5AEx+0vJ7dMQUyr0jSthXjVbhFpwv8c75t6sXRkRRDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-03T15:32:45.210080Z","bundle_sha256":"b90cc90289f8365fc472769c4e89f6e2e555a0f1f5ff5183a5f756e7eeabaad2"}}