{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:ZKS3BGUDN7JNF2MUW3762WADDU","short_pith_number":"pith:ZKS3BGUD","canonical_record":{"source":{"id":"2108.00968","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2021-08-02T15:13:52Z","cross_cats_sorted":["cs.AI","stat.ML"],"title_canon_sha256":"6c43a5aeb9a95227c2e4bf3949d3e817dc354c1ca86a5c1eea465baec6e90c4f","abstract_canon_sha256":"2d6ca11490721ccf2f6ee33d42e1068e3556ea76e5c629da451c2840a1ad1532"},"schema_version":"1.0"},"canonical_sha256":"caa5b09a836fd2d2e994b6ffed58031d36617524f54f100246bd6836943dc648","source":{"kind":"arxiv","id":"2108.00968","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2108.00968","created_at":"2026-07-05T03:24:30Z"},{"alias_kind":"arxiv_version","alias_value":"2108.00968v2","created_at":"2026-07-05T03:24:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2108.00968","created_at":"2026-07-05T03:24:30Z"},{"alias_kind":"pith_short_12","alias_value":"ZKS3BGUDN7JN","created_at":"2026-07-05T03:24:30Z"},{"alias_kind":"pith_short_16","alias_value":"ZKS3BGUDN7JNF2MU","created_at":"2026-07-05T03:24:30Z"},{"alias_kind":"pith_short_8","alias_value":"ZKS3BGUD","created_at":"2026-07-05T03:24:30Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:ZKS3BGUDN7JNF2MUW3762WADDU","target":"record","payload":{"canonical_record":{"source":{"id":"2108.00968","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2021-08-02T15:13:52Z","cross_cats_sorted":["cs.AI","stat.ML"],"title_canon_sha256":"6c43a5aeb9a95227c2e4bf3949d3e817dc354c1ca86a5c1eea465baec6e90c4f","abstract_canon_sha256":"2d6ca11490721ccf2f6ee33d42e1068e3556ea76e5c629da451c2840a1ad1532"},"schema_version":"1.0"},"canonical_sha256":"caa5b09a836fd2d2e994b6ffed58031d36617524f54f100246bd6836943dc648","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:24:30.828218Z","signature_b64":"lH6wsVZDdn1insTVCKbZyQBG90cUkZ7WM7E636NQtFXbvBR5Zh9BjhToLWsVSK6CR8+Paw0ux7VJHbOz2/zlCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"caa5b09a836fd2d2e994b6ffed58031d36617524f54f100246bd6836943dc648","last_reissued_at":"2026-07-05T03:24:30.827787Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:24:30.827787Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2108.00968","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T03:24:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fREQImI4E17+fqCf0Wxrgw7jv02NYGfBycvS8n2P60lkOpvV91w1D7+p+Hs88z2DBTFFZGDikXzBNKWCRO7lBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T07:19:06.203376Z"},"content_sha256":"dfebe868101696e06b9a46d50880c07f932bbc06ff4abb75afc9ce5393eb13fe","schema_version":"1.0","event_id":"sha256:dfebe868101696e06b9a46d50880c07f932bbc06ff4abb75afc9ce5393eb13fe"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:ZKS3BGUDN7JNF2MUW3762WADDU","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Robust Semantic Segmentation with Superpixel-Mix","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":["cs.AI","stat.ML"],"primary_cat":"cs.CV","authors_text":"Andrei Bursuc, Angela Yao, Gianni Franchi, Mai Lan Ha, Nacim Belkhir, Volker Blanz, Yufei Hu","submitted_at":"2021-08-02T15:13:52Z","abstract_excerpt":"Along with predictive performance and runtime speed, reliability is a key requirement for real-world semantic segmentation. Reliability encompasses robustness, predictive uncertainty and reduced bias. To improve reliability, we introduce Superpixel-mix, a new superpixel-based data augmentation method with teacher-student consistency training. Unlike other mixing-based augmentation techniques, mixing superpixels between images is aware of object boundaries, while yielding consistent gains in segmentation accuracy. Our proposed technique achieves state-of-the-art results in semi-supervised seman"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2108.00968","kind":"arxiv","version":2},"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/2108.00968/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":"2026-07-05T03:24:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vnvK5/UbSt7nGwYXzjJ/Jmg0m2I0FD5PPrhLSAawqje/+L/hMOznpDYdMm4GQ3ME4j/sUF3ywnzON+dxuL7yDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T07:19:06.204172Z"},"content_sha256":"035bd4720a22f3fb7b7d0c965e1e8c804fb860c86f2079b12fdc31a0dd8b5ebc","schema_version":"1.0","event_id":"sha256:035bd4720a22f3fb7b7d0c965e1e8c804fb860c86f2079b12fdc31a0dd8b5ebc"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZKS3BGUDN7JNF2MUW3762WADDU/bundle.json","state_url":"https://pith.science/pith/ZKS3BGUDN7JNF2MUW3762WADDU/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZKS3BGUDN7JNF2MUW3762WADDU/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":"2026-08-07T07:19:06Z","links":{"resolver":"https://pith.science/pith/ZKS3BGUDN7JNF2MUW3762WADDU","bundle":"https://pith.science/pith/ZKS3BGUDN7JNF2MUW3762WADDU/bundle.json","state":"https://pith.science/pith/ZKS3BGUDN7JNF2MUW3762WADDU/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZKS3BGUDN7JNF2MUW3762WADDU/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:ZKS3BGUDN7JNF2MUW3762WADDU","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":"2d6ca11490721ccf2f6ee33d42e1068e3556ea76e5c629da451c2840a1ad1532","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2021-08-02T15:13:52Z","title_canon_sha256":"6c43a5aeb9a95227c2e4bf3949d3e817dc354c1ca86a5c1eea465baec6e90c4f"},"schema_version":"1.0","source":{"id":"2108.00968","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2108.00968","created_at":"2026-07-05T03:24:30Z"},{"alias_kind":"arxiv_version","alias_value":"2108.00968v2","created_at":"2026-07-05T03:24:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2108.00968","created_at":"2026-07-05T03:24:30Z"},{"alias_kind":"pith_short_12","alias_value":"ZKS3BGUDN7JN","created_at":"2026-07-05T03:24:30Z"},{"alias_kind":"pith_short_16","alias_value":"ZKS3BGUDN7JNF2MU","created_at":"2026-07-05T03:24:30Z"},{"alias_kind":"pith_short_8","alias_value":"ZKS3BGUD","created_at":"2026-07-05T03:24:30Z"}],"graph_snapshots":[{"event_id":"sha256:035bd4720a22f3fb7b7d0c965e1e8c804fb860c86f2079b12fdc31a0dd8b5ebc","target":"graph","created_at":"2026-07-05T03:24:30Z","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/2108.00968/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Along with predictive performance and runtime speed, reliability is a key requirement for real-world semantic segmentation. Reliability encompasses robustness, predictive uncertainty and reduced bias. To improve reliability, we introduce Superpixel-mix, a new superpixel-based data augmentation method with teacher-student consistency training. Unlike other mixing-based augmentation techniques, mixing superpixels between images is aware of object boundaries, while yielding consistent gains in segmentation accuracy. Our proposed technique achieves state-of-the-art results in semi-supervised seman","authors_text":"Andrei Bursuc, Angela Yao, Gianni Franchi, Mai Lan Ha, Nacim Belkhir, Volker Blanz, Yufei Hu","cross_cats":["cs.AI","stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2021-08-02T15:13:52Z","title":"Robust Semantic Segmentation with Superpixel-Mix"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2108.00968","kind":"arxiv","version":2},"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:dfebe868101696e06b9a46d50880c07f932bbc06ff4abb75afc9ce5393eb13fe","target":"record","created_at":"2026-07-05T03:24:30Z","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":"2d6ca11490721ccf2f6ee33d42e1068e3556ea76e5c629da451c2840a1ad1532","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2021-08-02T15:13:52Z","title_canon_sha256":"6c43a5aeb9a95227c2e4bf3949d3e817dc354c1ca86a5c1eea465baec6e90c4f"},"schema_version":"1.0","source":{"id":"2108.00968","kind":"arxiv","version":2}},"canonical_sha256":"caa5b09a836fd2d2e994b6ffed58031d36617524f54f100246bd6836943dc648","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"caa5b09a836fd2d2e994b6ffed58031d36617524f54f100246bd6836943dc648","first_computed_at":"2026-07-05T03:24:30.827787Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:24:30.827787Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"lH6wsVZDdn1insTVCKbZyQBG90cUkZ7WM7E636NQtFXbvBR5Zh9BjhToLWsVSK6CR8+Paw0ux7VJHbOz2/zlCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T03:24:30.828218Z","signed_message":"canonical_sha256_bytes"},"source_id":"2108.00968","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:dfebe868101696e06b9a46d50880c07f932bbc06ff4abb75afc9ce5393eb13fe","sha256:035bd4720a22f3fb7b7d0c965e1e8c804fb860c86f2079b12fdc31a0dd8b5ebc"],"state_sha256":"9ce95ab61fa0bf61499ccefa6e6e9a52e384d0cfe800564045868947fb6e4247"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"45XvMP106mqVx7pH1ZyT0Ndz1bIIIy1/LBebNiZ6+dGDK7fFFZBxjSFwhnxJHgixY6ux/jLaVdMxzdhpsFgPDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T07:19:06.209814Z","bundle_sha256":"d0011201c5871b77a1bf9890b3dc3ef900124040e2c25941141a5af0f309c0cb"}}