{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:NS5ZPAF5IZQKYPATKOYT6ZYASM","short_pith_number":"pith:NS5ZPAF5","canonical_record":{"source":{"id":"2606.06369","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-04T16:36:40Z","cross_cats_sorted":[],"title_canon_sha256":"6bb125403045591388b72ad41036df3292886cc603fe4227d0b5e7a322c54706","abstract_canon_sha256":"f3b081d8952eba87defcfd6305d4178fd5b45f7b59e7698d984220320df9aeb7"},"schema_version":"1.0"},"canonical_sha256":"6cbb9780bd4660ac3c1353b13f6700931b5c92d075399cb886396f5717a96410","source":{"kind":"arxiv","id":"2606.06369","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.06369","created_at":"2026-06-05T01:15:43Z"},{"alias_kind":"arxiv_version","alias_value":"2606.06369v1","created_at":"2026-06-05T01:15:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.06369","created_at":"2026-06-05T01:15:43Z"},{"alias_kind":"pith_short_12","alias_value":"NS5ZPAF5IZQK","created_at":"2026-06-05T01:15:43Z"},{"alias_kind":"pith_short_16","alias_value":"NS5ZPAF5IZQKYPAT","created_at":"2026-06-05T01:15:43Z"},{"alias_kind":"pith_short_8","alias_value":"NS5ZPAF5","created_at":"2026-06-05T01:15:43Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:NS5ZPAF5IZQKYPATKOYT6ZYASM","target":"record","payload":{"canonical_record":{"source":{"id":"2606.06369","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-04T16:36:40Z","cross_cats_sorted":[],"title_canon_sha256":"6bb125403045591388b72ad41036df3292886cc603fe4227d0b5e7a322c54706","abstract_canon_sha256":"f3b081d8952eba87defcfd6305d4178fd5b45f7b59e7698d984220320df9aeb7"},"schema_version":"1.0"},"canonical_sha256":"6cbb9780bd4660ac3c1353b13f6700931b5c92d075399cb886396f5717a96410","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-05T01:15:43.024059Z","signature_b64":"Wv0cUnYOUb8oVKxGKlY8WpiMflCUa2+AzouTI9w4l2wf5q+Gf59BHTvVwntJ5lOrqXdm6Oz8rW2zMouQvLqaAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6cbb9780bd4660ac3c1353b13f6700931b5c92d075399cb886396f5717a96410","last_reissued_at":"2026-06-05T01:15:43.023641Z","signature_status":"signed_v1","first_computed_at":"2026-06-05T01:15:43.023641Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2606.06369","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":"2026-06-05T01:15:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pWmnJYuV2og4nmjc4/ToK8ty14xwgWZnyjVslTWtHXoCIyKzF5NThOH4x1o+WzMSagtGr2CevhLdRhoCT9VMBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-20T07:17:54.825184Z"},"content_sha256":"f6eca137049f9aa879092fabc95ae404e3aa893e459f989a00657c4efeae8ab0","schema_version":"1.0","event_id":"sha256:f6eca137049f9aa879092fabc95ae404e3aa893e459f989a00657c4efeae8ab0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:NS5ZPAF5IZQKYPATKOYT6ZYASM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Visual Commonsense Driven Knowledge Refinements for Scene Graph Generation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Jakob Suchan, Ma\\\"elic Neau, Mehul Bhatt, Salim Baloch, Zoe Falomir","submitted_at":"2026-06-04T16:36:40Z","abstract_excerpt":"Learning-driven Scene Graph Generation (SGG) models excel on frequent relation types but degrade sharply under annotation sparsity, failing to capture reliable visual commonsense knowledge. We propose a model-agnostic, semantically-guided knowledge refinement framework that systematically mines commonsense-grounded constraints from training data - capturing spatial, functional, and qualitative relational regularities - and uses general declarative commonsense reasoning to correct and refine ranked SGG predictions at inference time. The framework requires no manual rule authoring, no model retr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.06369","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/2606.06369/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":"2026-06-05T01:15:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"coDj8s0GFJiFGZycArgDlUL+OznpYQXCACddcQyQ0y716S+d6o9TQV05L78s0XpfY/1sFpe60+GReluutJXQCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-20T07:17:54.825553Z"},"content_sha256":"fe89eeb5d18a1b8c7d32646e2a8d665c7c9c91457470c143d702e20c0dc1e7a9","schema_version":"1.0","event_id":"sha256:fe89eeb5d18a1b8c7d32646e2a8d665c7c9c91457470c143d702e20c0dc1e7a9"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/NS5ZPAF5IZQKYPATKOYT6ZYASM/bundle.json","state_url":"https://pith.science/pith/NS5ZPAF5IZQKYPATKOYT6ZYASM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/NS5ZPAF5IZQKYPATKOYT6ZYASM/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":"2026-06-20T07:17:54Z","links":{"resolver":"https://pith.science/pith/NS5ZPAF5IZQKYPATKOYT6ZYASM","bundle":"https://pith.science/pith/NS5ZPAF5IZQKYPATKOYT6ZYASM/bundle.json","state":"https://pith.science/pith/NS5ZPAF5IZQKYPATKOYT6ZYASM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/NS5ZPAF5IZQKYPATKOYT6ZYASM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:NS5ZPAF5IZQKYPATKOYT6ZYASM","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":"f3b081d8952eba87defcfd6305d4178fd5b45f7b59e7698d984220320df9aeb7","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-04T16:36:40Z","title_canon_sha256":"6bb125403045591388b72ad41036df3292886cc603fe4227d0b5e7a322c54706"},"schema_version":"1.0","source":{"id":"2606.06369","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.06369","created_at":"2026-06-05T01:15:43Z"},{"alias_kind":"arxiv_version","alias_value":"2606.06369v1","created_at":"2026-06-05T01:15:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.06369","created_at":"2026-06-05T01:15:43Z"},{"alias_kind":"pith_short_12","alias_value":"NS5ZPAF5IZQK","created_at":"2026-06-05T01:15:43Z"},{"alias_kind":"pith_short_16","alias_value":"NS5ZPAF5IZQKYPAT","created_at":"2026-06-05T01:15:43Z"},{"alias_kind":"pith_short_8","alias_value":"NS5ZPAF5","created_at":"2026-06-05T01:15:43Z"}],"graph_snapshots":[{"event_id":"sha256:fe89eeb5d18a1b8c7d32646e2a8d665c7c9c91457470c143d702e20c0dc1e7a9","target":"graph","created_at":"2026-06-05T01:15:43Z","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/2606.06369/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Learning-driven Scene Graph Generation (SGG) models excel on frequent relation types but degrade sharply under annotation sparsity, failing to capture reliable visual commonsense knowledge. We propose a model-agnostic, semantically-guided knowledge refinement framework that systematically mines commonsense-grounded constraints from training data - capturing spatial, functional, and qualitative relational regularities - and uses general declarative commonsense reasoning to correct and refine ranked SGG predictions at inference time. The framework requires no manual rule authoring, no model retr","authors_text":"Jakob Suchan, Ma\\\"elic Neau, Mehul Bhatt, Salim Baloch, Zoe Falomir","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-04T16:36:40Z","title":"Visual Commonsense Driven Knowledge Refinements for Scene Graph Generation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.06369","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:f6eca137049f9aa879092fabc95ae404e3aa893e459f989a00657c4efeae8ab0","target":"record","created_at":"2026-06-05T01:15:43Z","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":"f3b081d8952eba87defcfd6305d4178fd5b45f7b59e7698d984220320df9aeb7","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-04T16:36:40Z","title_canon_sha256":"6bb125403045591388b72ad41036df3292886cc603fe4227d0b5e7a322c54706"},"schema_version":"1.0","source":{"id":"2606.06369","kind":"arxiv","version":1}},"canonical_sha256":"6cbb9780bd4660ac3c1353b13f6700931b5c92d075399cb886396f5717a96410","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6cbb9780bd4660ac3c1353b13f6700931b5c92d075399cb886396f5717a96410","first_computed_at":"2026-06-05T01:15:43.023641Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-05T01:15:43.023641Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Wv0cUnYOUb8oVKxGKlY8WpiMflCUa2+AzouTI9w4l2wf5q+Gf59BHTvVwntJ5lOrqXdm6Oz8rW2zMouQvLqaAw==","signature_status":"signed_v1","signed_at":"2026-06-05T01:15:43.024059Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.06369","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f6eca137049f9aa879092fabc95ae404e3aa893e459f989a00657c4efeae8ab0","sha256:fe89eeb5d18a1b8c7d32646e2a8d665c7c9c91457470c143d702e20c0dc1e7a9"],"state_sha256":"6294da1e3940c45d26f52952abde658d8576508f784e39d527b0ca2819aa6c5a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZRCnepYCAp2Fht5LnXFpX8Gtp42KW/odUz7UzGapKPPlFH+qdLH0zCT8gqa4hHIVHpbLcp8O/yhksja81hdDBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-20T07:17:54.827421Z","bundle_sha256":"8e8e35a5c8e7932c4a457f5b060be31ede2354c496d38885db2746b76703121d"}}