{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:4P7VIORNZTBEBMHMX5UWJZAZ4A","short_pith_number":"pith:4P7VIORN","canonical_record":{"source":{"id":"2606.22702","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-06-21T22:38:35Z","cross_cats_sorted":[],"title_canon_sha256":"6aaa07eabfd92386d64590919888f5f1832bef03453d7a406d287cb4cf965a01","abstract_canon_sha256":"50128127e7c9ebcb016c183b13b5269ad3741312ad88292e708ae6f127797d65"},"schema_version":"1.0"},"canonical_sha256":"e3ff543a2dccc240b0ecbf6964e419e0135fae42c3614215ffef07e5a8df9d40","source":{"kind":"arxiv","id":"2606.22702","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.22702","created_at":"2026-06-23T02:13:45Z"},{"alias_kind":"arxiv_version","alias_value":"2606.22702v1","created_at":"2026-06-23T02:13:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.22702","created_at":"2026-06-23T02:13:45Z"},{"alias_kind":"pith_short_12","alias_value":"4P7VIORNZTBE","created_at":"2026-06-23T02:13:45Z"},{"alias_kind":"pith_short_16","alias_value":"4P7VIORNZTBEBMHM","created_at":"2026-06-23T02:13:45Z"},{"alias_kind":"pith_short_8","alias_value":"4P7VIORN","created_at":"2026-06-23T02:13:45Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:4P7VIORNZTBEBMHMX5UWJZAZ4A","target":"record","payload":{"canonical_record":{"source":{"id":"2606.22702","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-06-21T22:38:35Z","cross_cats_sorted":[],"title_canon_sha256":"6aaa07eabfd92386d64590919888f5f1832bef03453d7a406d287cb4cf965a01","abstract_canon_sha256":"50128127e7c9ebcb016c183b13b5269ad3741312ad88292e708ae6f127797d65"},"schema_version":"1.0"},"canonical_sha256":"e3ff543a2dccc240b0ecbf6964e419e0135fae42c3614215ffef07e5a8df9d40","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-23T02:13:45.229134Z","signature_b64":"2VMTFSGdJnfcNUrJavWYbY1rFdamIfCjuAm0RsbktCSMLySxTtAX3CoSpZyVFsvslj9+TQRvgk9rCmfkInJpCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e3ff543a2dccc240b0ecbf6964e419e0135fae42c3614215ffef07e5a8df9d40","last_reissued_at":"2026-06-23T02:13:45.228714Z","signature_status":"signed_v1","first_computed_at":"2026-06-23T02:13:45.228714Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2606.22702","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-06-23T02:13:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yfCd1VeAHFU76CEWsC3wxb32PEDC/EsTwWsLZCCEYkLLzKIs4wIg+1Uver6eiJRxCv1dTr2+cR3d1Nm1HhJWCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-29T03:16:50.952667Z"},"content_sha256":"37aebb4530c1b23264e4db2d9050918088a778d63b3eab074411721d065f7994","schema_version":"1.0","event_id":"sha256:37aebb4530c1b23264e4db2d9050918088a778d63b3eab074411721d065f7994"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:4P7VIORNZTBEBMHMX5UWJZAZ4A","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Modular Diffusion Models for Structured Visual Recognition","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bj\\\"orn Ommer, Leonid Sigal, Siddhesh Khandelwal","submitted_at":"2026-06-21T22:38:35Z","abstract_excerpt":"Traditional supervised methods for structured visual recognition tasks -- such as object detection, segmentation, and scene graph generation -- often produce deterministic, fixed outputs, limiting their ability to capture the inherent uncertainty in complex visual scenes. As a consequence, such point estimates are unable to capture the prediction uncertainty (or multi modality) intrinsic to these problems, often arising from natural ambiguities (e.g., ambiguity in size of partially occluded objects, local ambiguity of exact segmentation boundary, etc.) as well as noise and sparsity of training"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.22702","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/2606.22702/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":"2026-06-23T02:13:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1Ab/4ZVKO0BWLRaPd4/inVIFSwfbl5b83vIdo3t7eMpYKSyRvB+0XHPlpUO6nNvwoE+uyVVIxd+0Kod9VqZvBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-29T03:16:50.953095Z"},"content_sha256":"1bdd143b9deecf5ccb985e50f4c4b5b11a82c1a5382fe4d4d4d3af9af1dfc92f","schema_version":"1.0","event_id":"sha256:1bdd143b9deecf5ccb985e50f4c4b5b11a82c1a5382fe4d4d4d3af9af1dfc92f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4P7VIORNZTBEBMHMX5UWJZAZ4A/bundle.json","state_url":"https://pith.science/pith/4P7VIORNZTBEBMHMX5UWJZAZ4A/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4P7VIORNZTBEBMHMX5UWJZAZ4A/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":"2026-06-29T03:16:50Z","links":{"resolver":"https://pith.science/pith/4P7VIORNZTBEBMHMX5UWJZAZ4A","bundle":"https://pith.science/pith/4P7VIORNZTBEBMHMX5UWJZAZ4A/bundle.json","state":"https://pith.science/pith/4P7VIORNZTBEBMHMX5UWJZAZ4A/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4P7VIORNZTBEBMHMX5UWJZAZ4A/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:4P7VIORNZTBEBMHMX5UWJZAZ4A","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":"50128127e7c9ebcb016c183b13b5269ad3741312ad88292e708ae6f127797d65","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-06-21T22:38:35Z","title_canon_sha256":"6aaa07eabfd92386d64590919888f5f1832bef03453d7a406d287cb4cf965a01"},"schema_version":"1.0","source":{"id":"2606.22702","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.22702","created_at":"2026-06-23T02:13:45Z"},{"alias_kind":"arxiv_version","alias_value":"2606.22702v1","created_at":"2026-06-23T02:13:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.22702","created_at":"2026-06-23T02:13:45Z"},{"alias_kind":"pith_short_12","alias_value":"4P7VIORNZTBE","created_at":"2026-06-23T02:13:45Z"},{"alias_kind":"pith_short_16","alias_value":"4P7VIORNZTBEBMHM","created_at":"2026-06-23T02:13:45Z"},{"alias_kind":"pith_short_8","alias_value":"4P7VIORN","created_at":"2026-06-23T02:13:45Z"}],"graph_snapshots":[{"event_id":"sha256:1bdd143b9deecf5ccb985e50f4c4b5b11a82c1a5382fe4d4d4d3af9af1dfc92f","target":"graph","created_at":"2026-06-23T02:13:45Z","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/2606.22702/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Traditional supervised methods for structured visual recognition tasks -- such as object detection, segmentation, and scene graph generation -- often produce deterministic, fixed outputs, limiting their ability to capture the inherent uncertainty in complex visual scenes. As a consequence, such point estimates are unable to capture the prediction uncertainty (or multi modality) intrinsic to these problems, often arising from natural ambiguities (e.g., ambiguity in size of partially occluded objects, local ambiguity of exact segmentation boundary, etc.) as well as noise and sparsity of training","authors_text":"Bj\\\"orn Ommer, Leonid Sigal, Siddhesh Khandelwal","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-06-21T22:38:35Z","title":"Modular Diffusion Models for Structured Visual Recognition"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.22702","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":"sha256:37aebb4530c1b23264e4db2d9050918088a778d63b3eab074411721d065f7994","target":"record","created_at":"2026-06-23T02:13:45Z","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":"50128127e7c9ebcb016c183b13b5269ad3741312ad88292e708ae6f127797d65","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-06-21T22:38:35Z","title_canon_sha256":"6aaa07eabfd92386d64590919888f5f1832bef03453d7a406d287cb4cf965a01"},"schema_version":"1.0","source":{"id":"2606.22702","kind":"arxiv","version":1}},"canonical_sha256":"e3ff543a2dccc240b0ecbf6964e419e0135fae42c3614215ffef07e5a8df9d40","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e3ff543a2dccc240b0ecbf6964e419e0135fae42c3614215ffef07e5a8df9d40","first_computed_at":"2026-06-23T02:13:45.228714Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-23T02:13:45.228714Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"2VMTFSGdJnfcNUrJavWYbY1rFdamIfCjuAm0RsbktCSMLySxTtAX3CoSpZyVFsvslj9+TQRvgk9rCmfkInJpCg==","signature_status":"signed_v1","signed_at":"2026-06-23T02:13:45.229134Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.22702","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:37aebb4530c1b23264e4db2d9050918088a778d63b3eab074411721d065f7994","sha256:1bdd143b9deecf5ccb985e50f4c4b5b11a82c1a5382fe4d4d4d3af9af1dfc92f"],"state_sha256":"28ffb4289d3686ec03ec45002a641426645140f3ea22367787c180f9cfff2d0c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"itdL0iuSrZr0EUAo5yPXNy04RQzVaOXC0hkQ9wWXVPf4gYZd2QQYXGyTGcIy5n+IphrQqdai7UMMP1zt9Kh0Cw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-29T03:16:50.956532Z","bundle_sha256":"73a288b720f6cda0269fa5de121a767d78a9b022025e2745c684ab88c58034c9"}}