{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:XOFUYOZLRAYQ3BDYQEFNUH2HTO","short_pith_number":"pith:XOFUYOZL","schema_version":"1.0","canonical_sha256":"bb8b4c3b2b88310d8478810ada1f479baee0714ce936a98e71b4d863ec0a783e","source":{"kind":"arxiv","id":"2606.26029","version":1},"attestation_state":"computed","paper":{"title":"TriViewBench: Controlled Complexity Scaling for Multi-View Structural Reasoning in MLLMs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Lan-Zhe Guo, Yu-Yang Chen","submitted_at":"2026-06-24T17:00:05Z","abstract_excerpt":"Multimodal Large Language Models (MLLMs) demonstrate strong performance on standard visual question answering benchmarks, yet their scalability under controlled structural complexity remains poorly understood. We introduce TriViewBench, a controlled three-view visual reasoning benchmark constructed from synthetic 3D scenes with explicitly parameterized object count and occlusion. The benchmark contains 1,923 scenes and over 14K Question-Answer (QA) pairs organized into four complexity levels and three reasoning categories: Local Decision, Object Counting, and Global Recovery. We evaluate 18 op"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2606.26029","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-06-24T17:00:05Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"2f89ee4a4184c96bc2600836ac001ec057a681dae26e2217a95481cb081d307b","abstract_canon_sha256":"b47ed2e431e813d5d9b9914bf0adbea8b3e7912e37762a8b2ed6529a217cf022"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-25T01:18:46.300494Z","signature_b64":"B2o3ZONs9cIe37fX1CjwCUAEzUK0Ki6N+lAavrreLi4SaEPZzMsDyupSMDaWsNCC4t/kob8XZ88dB0I/uFqaDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bb8b4c3b2b88310d8478810ada1f479baee0714ce936a98e71b4d863ec0a783e","last_reissued_at":"2026-06-25T01:18:46.300127Z","signature_status":"signed_v1","first_computed_at":"2026-06-25T01:18:46.300127Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"TriViewBench: Controlled Complexity Scaling for Multi-View Structural Reasoning in MLLMs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Lan-Zhe Guo, Yu-Yang Chen","submitted_at":"2026-06-24T17:00:05Z","abstract_excerpt":"Multimodal Large Language Models (MLLMs) demonstrate strong performance on standard visual question answering benchmarks, yet their scalability under controlled structural complexity remains poorly understood. We introduce TriViewBench, a controlled three-view visual reasoning benchmark constructed from synthetic 3D scenes with explicitly parameterized object count and occlusion. The benchmark contains 1,923 scenes and over 14K Question-Answer (QA) pairs organized into four complexity levels and three reasoning categories: Local Decision, Object Counting, and Global Recovery. We evaluate 18 op"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.26029","kind":"arxiv","version":1},"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/2606.26029/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2606.26029","created_at":"2026-06-25T01:18:46.300189+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.26029v1","created_at":"2026-06-25T01:18:46.300189+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.26029","created_at":"2026-06-25T01:18:46.300189+00:00"},{"alias_kind":"pith_short_12","alias_value":"XOFUYOZLRAYQ","created_at":"2026-06-25T01:18:46.300189+00:00"},{"alias_kind":"pith_short_16","alias_value":"XOFUYOZLRAYQ3BDY","created_at":"2026-06-25T01:18:46.300189+00:00"},{"alias_kind":"pith_short_8","alias_value":"XOFUYOZL","created_at":"2026-06-25T01:18:46.300189+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/XOFUYOZLRAYQ3BDYQEFNUH2HTO","json":"https://pith.science/pith/XOFUYOZLRAYQ3BDYQEFNUH2HTO.json","graph_json":"https://pith.science/api/pith-number/XOFUYOZLRAYQ3BDYQEFNUH2HTO/graph.json","events_json":"https://pith.science/api/pith-number/XOFUYOZLRAYQ3BDYQEFNUH2HTO/events.json","paper":"https://pith.science/paper/XOFUYOZL"},"agent_actions":{"view_html":"https://pith.science/pith/XOFUYOZLRAYQ3BDYQEFNUH2HTO","download_json":"https://pith.science/pith/XOFUYOZLRAYQ3BDYQEFNUH2HTO.json","view_paper":"https://pith.science/paper/XOFUYOZL","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.26029&json=true","fetch_graph":"https://pith.science/api/pith-number/XOFUYOZLRAYQ3BDYQEFNUH2HTO/graph.json","fetch_events":"https://pith.science/api/pith-number/XOFUYOZLRAYQ3BDYQEFNUH2HTO/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/XOFUYOZLRAYQ3BDYQEFNUH2HTO/action/timestamp_anchor","attest_storage":"https://pith.science/pith/XOFUYOZLRAYQ3BDYQEFNUH2HTO/action/storage_attestation","attest_author":"https://pith.science/pith/XOFUYOZLRAYQ3BDYQEFNUH2HTO/action/author_attestation","sign_citation":"https://pith.science/pith/XOFUYOZLRAYQ3BDYQEFNUH2HTO/action/citation_signature","submit_replication":"https://pith.science/pith/XOFUYOZLRAYQ3BDYQEFNUH2HTO/action/replication_record"}},"created_at":"2026-06-25T01:18:46.300189+00:00","updated_at":"2026-06-25T01:18:46.300189+00:00"}