{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:4MDLVEJ2GFD4BUWASSMU24P7RI","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":"5aefc9205b50c2269756e78d07ef418802179ccba5eeab378841bc4886850a17","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-06-01T17:59:53Z","title_canon_sha256":"0c676e2247bece1c5f592eea042bc6335a810a319caae1e8d0fc171ab7ce968c"},"schema_version":"1.0","source":{"id":"2606.02580","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.02580","created_at":"2026-06-02T03:05:10Z"},{"alias_kind":"arxiv_version","alias_value":"2606.02580v1","created_at":"2026-06-02T03:05:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.02580","created_at":"2026-06-02T03:05:10Z"},{"alias_kind":"pith_short_12","alias_value":"4MDLVEJ2GFD4","created_at":"2026-06-02T03:05:10Z"},{"alias_kind":"pith_short_16","alias_value":"4MDLVEJ2GFD4BUWA","created_at":"2026-06-02T03:05:10Z"},{"alias_kind":"pith_short_8","alias_value":"4MDLVEJ2","created_at":"2026-06-02T03:05:10Z"}],"graph_snapshots":[{"event_id":"sha256:82e17aeba4d41db05755f41d59798c9a9435e32503698bcb0ebf942260e1909b","target":"graph","created_at":"2026-06-02T03:05:10Z","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/2606.02580/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Inverse graphics is a longstanding and highly underconstrained problem that seeks to reconstruct images as editable 3D scenes which can be rendered, relit, and manipulated. In this work, we investigate whether pretrained vision-language models (VLMs) can perform executable inverse graphics directly from a single image by reconstructing a scene as an editable Blender program, without relying on specialized 2D or 3D foundation models, differentiable rendering, or multi-view supervision. We introduce Staged Executable Inverse Graphics (SEIG), an agentic framework that reconstructs a 3D scene from","authors_text":"Guangzhao He, Hadar Averbuch-Elor, Rundong Luo, Wei-Chiu Ma","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-06-01T17:59:53Z","title":"Thinking in Blender: Staged Executable Inverse Graphics with Vision-Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.02580","kind":"arxiv","version":1},"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:be7e4194a3169eff602c6d9a5d2253dcebf10f4001cd1fbdd66b9e9345d98af6","target":"record","created_at":"2026-06-02T03:05:10Z","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":"5aefc9205b50c2269756e78d07ef418802179ccba5eeab378841bc4886850a17","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-06-01T17:59:53Z","title_canon_sha256":"0c676e2247bece1c5f592eea042bc6335a810a319caae1e8d0fc171ab7ce968c"},"schema_version":"1.0","source":{"id":"2606.02580","kind":"arxiv","version":1}},"canonical_sha256":"e306ba913a3147c0d2c094994d71ff8a0cfc7efc89dc8191fbb51a541705e7f5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e306ba913a3147c0d2c094994d71ff8a0cfc7efc89dc8191fbb51a541705e7f5","first_computed_at":"2026-06-02T03:05:10.726872Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-02T03:05:10.726872Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"0HvzfeHV0Us+ckclqesqMlsMLlUMRLHae0bORAvwLYoqe2zpKhCgsihCgfqgBemPWM6TYnfVTmPErXKMEAHLDQ==","signature_status":"signed_v1","signed_at":"2026-06-02T03:05:10.727292Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.02580","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:be7e4194a3169eff602c6d9a5d2253dcebf10f4001cd1fbdd66b9e9345d98af6","sha256:82e17aeba4d41db05755f41d59798c9a9435e32503698bcb0ebf942260e1909b"],"state_sha256":"c66f6931065f58332a80e43c07e1435f4fd7127a3ef239ab8bc8715279f36c28"}