{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:NH2LNOSZ7SK7HRZ6YAMOKGPNAT","short_pith_number":"pith:NH2LNOSZ","canonical_record":{"source":{"id":"2407.10920","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-07-15T17:21:41Z","cross_cats_sorted":["cs.AI","cs.CL"],"title_canon_sha256":"cdfa02880346011ae4c25ac59b85be7ea699f8b1d09cf95b869c5ea78c702040","abstract_canon_sha256":"89cba74872ef0fc039faa1b29328dc6b5c0b8fac1b567271ca5678812b4d7bf2"},"schema_version":"1.0"},"canonical_sha256":"69f4b6ba59fc95f3c73ec018e519ed04ed3055d617dc3b9af36f90b3d1e885fc","source":{"kind":"arxiv","id":"2407.10920","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.10920","created_at":"2026-07-05T09:20:01Z"},{"alias_kind":"arxiv_version","alias_value":"2407.10920v3","created_at":"2026-07-05T09:20:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.10920","created_at":"2026-07-05T09:20:01Z"},{"alias_kind":"pith_short_12","alias_value":"NH2LNOSZ7SK7","created_at":"2026-07-05T09:20:01Z"},{"alias_kind":"pith_short_16","alias_value":"NH2LNOSZ7SK7HRZ6","created_at":"2026-07-05T09:20:01Z"},{"alias_kind":"pith_short_8","alias_value":"NH2LNOSZ","created_at":"2026-07-05T09:20:01Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:NH2LNOSZ7SK7HRZ6YAMOKGPNAT","target":"record","payload":{"canonical_record":{"source":{"id":"2407.10920","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-07-15T17:21:41Z","cross_cats_sorted":["cs.AI","cs.CL"],"title_canon_sha256":"cdfa02880346011ae4c25ac59b85be7ea699f8b1d09cf95b869c5ea78c702040","abstract_canon_sha256":"89cba74872ef0fc039faa1b29328dc6b5c0b8fac1b567271ca5678812b4d7bf2"},"schema_version":"1.0"},"canonical_sha256":"69f4b6ba59fc95f3c73ec018e519ed04ed3055d617dc3b9af36f90b3d1e885fc","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:20:01.131600Z","signature_b64":"lXV6M2vLuh4SLx7E5n0e4gQgkqIro4LREpOmwWiMZF9pPNYd/701b6wZCY326E7N6o05nA2EvRX58W5nrs8rBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"69f4b6ba59fc95f3c73ec018e519ed04ed3055d617dc3b9af36f90b3d1e885fc","last_reissued_at":"2026-07-05T09:20:01.131162Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:20:01.131162Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2407.10920","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":"2026-07-05T09:20:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cGmQHIrQohUTNqMo04NHEfcvqaoyJGo8x9yjszVPInOhKNRg2JJI/kSVxJI2+dAwSFqFumqVVclRCRwBEO8AAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T15:25:42.990250Z"},"content_sha256":"1e764351031072571c1ac09f1a19c24193c294db72cf54e02aa62facd87bab00","schema_version":"1.0","event_id":"sha256:1e764351031072571c1ac09f1a19c24193c294db72cf54e02aa62facd87bab00"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:NH2LNOSZ7SK7HRZ6YAMOKGPNAT","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Benchmarking Vision Language Models for Cultural Understanding","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.CL"],"primary_cat":"cs.CV","authors_text":"Aishwarya Agrawal, Kanishk Jain, Karolina Sta\\'nczak, Lisa Anne Hendricks, Rabiul Awal, Shravan Nayak, Siva Reddy, Sjoerd van Steenkiste","submitted_at":"2024-07-15T17:21:41Z","abstract_excerpt":"Foundation models and vision-language pre-training have notably advanced Vision Language Models (VLMs), enabling multimodal processing of visual and linguistic data. However, their performance has been typically assessed on general scene understanding - recognizing objects, attributes, and actions - rather than cultural comprehension. This study introduces CulturalVQA, a visual question-answering benchmark aimed at assessing VLM's geo-diverse cultural understanding. We curate a collection of 2,378 image-question pairs with 1-5 answers per question representing cultures from 11 countries across"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.10920","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/2407.10920/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":"2026-07-05T09:20:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1PemKEe+lypYYRJ5t2lNLdq8fP+jrVct1LYi2DgFTOkczOBTlVjNsEHAjfq4zdVGKxwKHEFCZ+dY10vzwCAmAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T15:25:42.990938Z"},"content_sha256":"cf20d35a41f600e3f3d27d54c2863311111d0b6085825f01a1f7970441d3d4d4","schema_version":"1.0","event_id":"sha256:cf20d35a41f600e3f3d27d54c2863311111d0b6085825f01a1f7970441d3d4d4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/NH2LNOSZ7SK7HRZ6YAMOKGPNAT/bundle.json","state_url":"https://pith.science/pith/NH2LNOSZ7SK7HRZ6YAMOKGPNAT/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/NH2LNOSZ7SK7HRZ6YAMOKGPNAT/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":"2026-08-08T15:25:42Z","links":{"resolver":"https://pith.science/pith/NH2LNOSZ7SK7HRZ6YAMOKGPNAT","bundle":"https://pith.science/pith/NH2LNOSZ7SK7HRZ6YAMOKGPNAT/bundle.json","state":"https://pith.science/pith/NH2LNOSZ7SK7HRZ6YAMOKGPNAT/state.json","well_known_bundle":"https://pith.science/.well-known/pith/NH2LNOSZ7SK7HRZ6YAMOKGPNAT/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:NH2LNOSZ7SK7HRZ6YAMOKGPNAT","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":"89cba74872ef0fc039faa1b29328dc6b5c0b8fac1b567271ca5678812b4d7bf2","cross_cats_sorted":["cs.AI","cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-07-15T17:21:41Z","title_canon_sha256":"cdfa02880346011ae4c25ac59b85be7ea699f8b1d09cf95b869c5ea78c702040"},"schema_version":"1.0","source":{"id":"2407.10920","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.10920","created_at":"2026-07-05T09:20:01Z"},{"alias_kind":"arxiv_version","alias_value":"2407.10920v3","created_at":"2026-07-05T09:20:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.10920","created_at":"2026-07-05T09:20:01Z"},{"alias_kind":"pith_short_12","alias_value":"NH2LNOSZ7SK7","created_at":"2026-07-05T09:20:01Z"},{"alias_kind":"pith_short_16","alias_value":"NH2LNOSZ7SK7HRZ6","created_at":"2026-07-05T09:20:01Z"},{"alias_kind":"pith_short_8","alias_value":"NH2LNOSZ","created_at":"2026-07-05T09:20:01Z"}],"graph_snapshots":[{"event_id":"sha256:cf20d35a41f600e3f3d27d54c2863311111d0b6085825f01a1f7970441d3d4d4","target":"graph","created_at":"2026-07-05T09:20:01Z","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/2407.10920/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Foundation models and vision-language pre-training have notably advanced Vision Language Models (VLMs), enabling multimodal processing of visual and linguistic data. However, their performance has been typically assessed on general scene understanding - recognizing objects, attributes, and actions - rather than cultural comprehension. This study introduces CulturalVQA, a visual question-answering benchmark aimed at assessing VLM's geo-diverse cultural understanding. We curate a collection of 2,378 image-question pairs with 1-5 answers per question representing cultures from 11 countries across","authors_text":"Aishwarya Agrawal, Kanishk Jain, Karolina Sta\\'nczak, Lisa Anne Hendricks, Rabiul Awal, Shravan Nayak, Siva Reddy, Sjoerd van Steenkiste","cross_cats":["cs.AI","cs.CL"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-07-15T17:21:41Z","title":"Benchmarking Vision Language Models for Cultural Understanding"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.10920","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":"sha256:1e764351031072571c1ac09f1a19c24193c294db72cf54e02aa62facd87bab00","target":"record","created_at":"2026-07-05T09:20:01Z","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":"89cba74872ef0fc039faa1b29328dc6b5c0b8fac1b567271ca5678812b4d7bf2","cross_cats_sorted":["cs.AI","cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-07-15T17:21:41Z","title_canon_sha256":"cdfa02880346011ae4c25ac59b85be7ea699f8b1d09cf95b869c5ea78c702040"},"schema_version":"1.0","source":{"id":"2407.10920","kind":"arxiv","version":3}},"canonical_sha256":"69f4b6ba59fc95f3c73ec018e519ed04ed3055d617dc3b9af36f90b3d1e885fc","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"69f4b6ba59fc95f3c73ec018e519ed04ed3055d617dc3b9af36f90b3d1e885fc","first_computed_at":"2026-07-05T09:20:01.131162Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:20:01.131162Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"lXV6M2vLuh4SLx7E5n0e4gQgkqIro4LREpOmwWiMZF9pPNYd/701b6wZCY326E7N6o05nA2EvRX58W5nrs8rBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T09:20:01.131600Z","signed_message":"canonical_sha256_bytes"},"source_id":"2407.10920","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1e764351031072571c1ac09f1a19c24193c294db72cf54e02aa62facd87bab00","sha256:cf20d35a41f600e3f3d27d54c2863311111d0b6085825f01a1f7970441d3d4d4"],"state_sha256":"2b2bd17e7a0bd86a499c04bcf9f754ba2115ed50d74266c9d4b45bddbfce12c8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CaHucKTckj7f2Nf3DU41ZmrwZWe5t7cMjKwAp63ZVtZc1D33cX+bBtXduMmR41gXt/lVtDA4HFXTxJuPOWH0CQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T15:25:42.997937Z","bundle_sha256":"89bca09f9ad7618f287a30b06f87133ebbd78b05a8e2e8a17853b8670388c9e2"}}