{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:YEXC7MVGB5HIISJW5MTYLLRBJI","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":"10535e73dd640eb3feb29359e4567b2f103f53793c076b5b4de9367e2892d22c","cross_cats_sorted":["cs.LG","cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-11-24T22:52:55Z","title_canon_sha256":"afcd9f91f3c8a848543e8217fbfda57c08b6d7f7573899a2dad7fee4d9df7978"},"schema_version":"1.0","source":{"id":"2211.15508","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.15508","created_at":"2026-07-05T05:20:04Z"},{"alias_kind":"arxiv_version","alias_value":"2211.15508v1","created_at":"2026-07-05T05:20:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.15508","created_at":"2026-07-05T05:20:04Z"},{"alias_kind":"pith_short_12","alias_value":"YEXC7MVGB5HI","created_at":"2026-07-05T05:20:04Z"},{"alias_kind":"pith_short_16","alias_value":"YEXC7MVGB5HIISJW","created_at":"2026-07-05T05:20:04Z"},{"alias_kind":"pith_short_8","alias_value":"YEXC7MVG","created_at":"2026-07-05T05:20:04Z"}],"graph_snapshots":[{"event_id":"sha256:9e079d88d750e32b5c60980fb687143e400e6115d66e8a24a14e495e6202818b","target":"graph","created_at":"2026-07-05T05:20:04Z","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/2211.15508/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Examining graphs for similarity is a well-known challenge, but one that is mandatory for grouping graphs together. We present a data-driven method to cluster traffic scenes that is self-supervised, i.e. without manual labelling. We leverage the semantic scene graph model to create a generic graph embedding of the traffic scene, which is then mapped to a low-dimensional embedding space using a Siamese network, in which clustering is performed. In the training process of our novel approach, we augment existing traffic scenes in the Cartesian space to generate positive similarity samples. This al","authors_text":"J. Marius Z\\\"ollner, Maximilian Zipfl, Moritz Jarosch","cross_cats":["cs.LG","cs.RO"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-11-24T22:52:55Z","title":"Self Supervised Clustering of Traffic Scenes using Graph Representations"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.15508","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:db2366245db99cb2e4f99e9911646191e211e9931e7d84602972a0239fdbf067","target":"record","created_at":"2026-07-05T05:20:04Z","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":"10535e73dd640eb3feb29359e4567b2f103f53793c076b5b4de9367e2892d22c","cross_cats_sorted":["cs.LG","cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-11-24T22:52:55Z","title_canon_sha256":"afcd9f91f3c8a848543e8217fbfda57c08b6d7f7573899a2dad7fee4d9df7978"},"schema_version":"1.0","source":{"id":"2211.15508","kind":"arxiv","version":1}},"canonical_sha256":"c12e2fb2a60f4e844936eb2785ae214a022f486d4d3cced40325f948907dcbbc","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c12e2fb2a60f4e844936eb2785ae214a022f486d4d3cced40325f948907dcbbc","first_computed_at":"2026-07-05T05:20:04.978275Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:20:04.978275Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"dziPQvrGFnf4yVXNttWcMFzJarD/KhcDfQq+5q5QxV4mOvDjE2z6IhOCJnwQ7JNXcWW6zEdobEiFHvBVxgnIDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T05:20:04.978720Z","signed_message":"canonical_sha256_bytes"},"source_id":"2211.15508","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:db2366245db99cb2e4f99e9911646191e211e9931e7d84602972a0239fdbf067","sha256:9e079d88d750e32b5c60980fb687143e400e6115d66e8a24a14e495e6202818b"],"state_sha256":"4e8af8ec3012d6e617405ef354f5fe9bbaf1b3b8a732eb47a2a3b759a6e8f82f"}