{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:ZDS5LQIDEAFEAWKOVDA74PWY4P","short_pith_number":"pith:ZDS5LQID","canonical_record":{"source":{"id":"2501.13964","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-01-21T23:07:03Z","cross_cats_sorted":["cs.AI","cs.HC"],"title_canon_sha256":"19b318ff49c261d64406a935d63b3cd468cafc3de0ca89b9840ea8138528e94e","abstract_canon_sha256":"8ed48d087d53899f8211932275f16c80c14039fc1519ef779323dc2a613b5c1d"},"schema_version":"1.0"},"canonical_sha256":"c8e5d5c103200a40594ea8c1fe3ed8e3dc643694804a6e85abcfc8102178e97a","source":{"kind":"arxiv","id":"2501.13964","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.13964","created_at":"2026-07-05T10:08:28Z"},{"alias_kind":"arxiv_version","alias_value":"2501.13964v3","created_at":"2026-07-05T10:08:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.13964","created_at":"2026-07-05T10:08:28Z"},{"alias_kind":"pith_short_12","alias_value":"ZDS5LQIDEAFE","created_at":"2026-07-05T10:08:28Z"},{"alias_kind":"pith_short_16","alias_value":"ZDS5LQIDEAFEAWKO","created_at":"2026-07-05T10:08:28Z"},{"alias_kind":"pith_short_8","alias_value":"ZDS5LQID","created_at":"2026-07-05T10:08:28Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:ZDS5LQIDEAFEAWKOVDA74PWY4P","target":"record","payload":{"canonical_record":{"source":{"id":"2501.13964","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-01-21T23:07:03Z","cross_cats_sorted":["cs.AI","cs.HC"],"title_canon_sha256":"19b318ff49c261d64406a935d63b3cd468cafc3de0ca89b9840ea8138528e94e","abstract_canon_sha256":"8ed48d087d53899f8211932275f16c80c14039fc1519ef779323dc2a613b5c1d"},"schema_version":"1.0"},"canonical_sha256":"c8e5d5c103200a40594ea8c1fe3ed8e3dc643694804a6e85abcfc8102178e97a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:08:28.380107Z","signature_b64":"un5BuiSlvlDlQ2eKLap0OdgGCgycgDTzsL07ywOJSGOH/QT/5z+EuCOZBW7QSbDsGOClhd9qpiQn6ftXxz24Dg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c8e5d5c103200a40594ea8c1fe3ed8e3dc643694804a6e85abcfc8102178e97a","last_reissued_at":"2026-07-05T10:08:28.379599Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:08:28.379599Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2501.13964","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":"2026-07-05T10:08:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Zzoe4cKfhcM67DgmuEvgECAhHoCtRPr2qJ9Ns8Q0ZfGjhej4ubNVzHsJTLyu21p56hqcEst7u1VLmJE+uhS4AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T13:26:29.052548Z"},"content_sha256":"b9058c7ea0f07cf91a68ac844ea697965933bae1bfee7ca73bf1bf717009180e","schema_version":"1.0","event_id":"sha256:b9058c7ea0f07cf91a68ac844ea697965933bae1bfee7ca73bf1bf717009180e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:ZDS5LQIDEAFEAWKOVDA74PWY4P","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Advancing the Understanding and Evaluation of AR-Generated Scenes: When Vision-Language Models Shine and Stumble","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.HC"],"primary_cat":"cs.CV","authors_text":"Lin Duan, Maria Gorlatova, Yanming Xiu","submitted_at":"2025-01-21T23:07:03Z","abstract_excerpt":"Augmented Reality (AR) enhances the real world by integrating virtual content, yet ensuring the quality, usability, and safety of AR experiences presents significant challenges. Could Vision-Language Models (VLMs) offer a solution for the automated evaluation of AR-generated scenes? Could Vision-Language Models (VLMs) offer a solution for the automated evaluation of AR-generated scenes? In this study, we evaluate the capabilities of three state-of-the-art commercial VLMs -- GPT, Gemini, and Claude -- in identifying and describing AR scenes. For this purpose, we use DiverseAR, the first AR data"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.13964","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/2501.13964/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":"2026-07-05T10:08:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YHRJOPXM4XRgJYx4ooTBknQTc7h0oUdWoHRzp/QKrGThF0kkdTWNKeOEl+8HL9m95G2ssUUAKM5NW1D99tBjCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T13:26:29.052913Z"},"content_sha256":"38b47fae5a791cba19feb58df8af8cd8dee853d22e735dbf1de6841760157e32","schema_version":"1.0","event_id":"sha256:38b47fae5a791cba19feb58df8af8cd8dee853d22e735dbf1de6841760157e32"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZDS5LQIDEAFEAWKOVDA74PWY4P/bundle.json","state_url":"https://pith.science/pith/ZDS5LQIDEAFEAWKOVDA74PWY4P/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZDS5LQIDEAFEAWKOVDA74PWY4P/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":"2026-07-07T13:26:29Z","links":{"resolver":"https://pith.science/pith/ZDS5LQIDEAFEAWKOVDA74PWY4P","bundle":"https://pith.science/pith/ZDS5LQIDEAFEAWKOVDA74PWY4P/bundle.json","state":"https://pith.science/pith/ZDS5LQIDEAFEAWKOVDA74PWY4P/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZDS5LQIDEAFEAWKOVDA74PWY4P/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:ZDS5LQIDEAFEAWKOVDA74PWY4P","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":"8ed48d087d53899f8211932275f16c80c14039fc1519ef779323dc2a613b5c1d","cross_cats_sorted":["cs.AI","cs.HC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-01-21T23:07:03Z","title_canon_sha256":"19b318ff49c261d64406a935d63b3cd468cafc3de0ca89b9840ea8138528e94e"},"schema_version":"1.0","source":{"id":"2501.13964","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.13964","created_at":"2026-07-05T10:08:28Z"},{"alias_kind":"arxiv_version","alias_value":"2501.13964v3","created_at":"2026-07-05T10:08:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.13964","created_at":"2026-07-05T10:08:28Z"},{"alias_kind":"pith_short_12","alias_value":"ZDS5LQIDEAFE","created_at":"2026-07-05T10:08:28Z"},{"alias_kind":"pith_short_16","alias_value":"ZDS5LQIDEAFEAWKO","created_at":"2026-07-05T10:08:28Z"},{"alias_kind":"pith_short_8","alias_value":"ZDS5LQID","created_at":"2026-07-05T10:08:28Z"}],"graph_snapshots":[{"event_id":"sha256:38b47fae5a791cba19feb58df8af8cd8dee853d22e735dbf1de6841760157e32","target":"graph","created_at":"2026-07-05T10:08:28Z","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/2501.13964/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Augmented Reality (AR) enhances the real world by integrating virtual content, yet ensuring the quality, usability, and safety of AR experiences presents significant challenges. Could Vision-Language Models (VLMs) offer a solution for the automated evaluation of AR-generated scenes? Could Vision-Language Models (VLMs) offer a solution for the automated evaluation of AR-generated scenes? In this study, we evaluate the capabilities of three state-of-the-art commercial VLMs -- GPT, Gemini, and Claude -- in identifying and describing AR scenes. For this purpose, we use DiverseAR, the first AR data","authors_text":"Lin Duan, Maria Gorlatova, Yanming Xiu","cross_cats":["cs.AI","cs.HC"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-01-21T23:07:03Z","title":"Advancing the Understanding and Evaluation of AR-Generated Scenes: When Vision-Language Models Shine and Stumble"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.13964","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:b9058c7ea0f07cf91a68ac844ea697965933bae1bfee7ca73bf1bf717009180e","target":"record","created_at":"2026-07-05T10:08:28Z","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":"8ed48d087d53899f8211932275f16c80c14039fc1519ef779323dc2a613b5c1d","cross_cats_sorted":["cs.AI","cs.HC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-01-21T23:07:03Z","title_canon_sha256":"19b318ff49c261d64406a935d63b3cd468cafc3de0ca89b9840ea8138528e94e"},"schema_version":"1.0","source":{"id":"2501.13964","kind":"arxiv","version":3}},"canonical_sha256":"c8e5d5c103200a40594ea8c1fe3ed8e3dc643694804a6e85abcfc8102178e97a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c8e5d5c103200a40594ea8c1fe3ed8e3dc643694804a6e85abcfc8102178e97a","first_computed_at":"2026-07-05T10:08:28.379599Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:08:28.379599Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"un5BuiSlvlDlQ2eKLap0OdgGCgycgDTzsL07ywOJSGOH/QT/5z+EuCOZBW7QSbDsGOClhd9qpiQn6ftXxz24Dg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:08:28.380107Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.13964","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b9058c7ea0f07cf91a68ac844ea697965933bae1bfee7ca73bf1bf717009180e","sha256:38b47fae5a791cba19feb58df8af8cd8dee853d22e735dbf1de6841760157e32"],"state_sha256":"b736fdd4bba70a9d913777de695b4d06051744f8605dee1f5fa81d9daa537056"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"c6tYNUcXe5to17vk+x9EHCV4HN2zx8FTpZFSWCYImUKepCvR05w25NEXk3Jp9PT6GeatvYhAZC4UDXzbfoybCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T13:26:29.054819Z","bundle_sha256":"934834a1c20ed08c2e21930de2b0067028b4c1abe74aa78622d3ea273ec23404"}}