{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:W5G32PDATTGXC5QQPRIK4X2VP7","short_pith_number":"pith:W5G32PDA","canonical_record":{"source":{"id":"2209.09839","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-09-20T16:32:06Z","cross_cats_sorted":[],"title_canon_sha256":"e336def0fb6c38029283979d659f48146d4cfe49a036f8f3ec02861f41edca08","abstract_canon_sha256":"7d7a63e6069d2b480bd43817e0ab099fa57d09be6873f8c13b9a60b80fe95350"},"schema_version":"1.0"},"canonical_sha256":"b74dbd3c609ccd7176107c50ae5f557fcb8c1253e25e3868468712eee7ed2886","source":{"kind":"arxiv","id":"2209.09839","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2209.09839","created_at":"2026-07-05T04:59:35Z"},{"alias_kind":"arxiv_version","alias_value":"2209.09839v1","created_at":"2026-07-05T04:59:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2209.09839","created_at":"2026-07-05T04:59:35Z"},{"alias_kind":"pith_short_12","alias_value":"W5G32PDATTGX","created_at":"2026-07-05T04:59:35Z"},{"alias_kind":"pith_short_16","alias_value":"W5G32PDATTGXC5QQ","created_at":"2026-07-05T04:59:35Z"},{"alias_kind":"pith_short_8","alias_value":"W5G32PDA","created_at":"2026-07-05T04:59:35Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:W5G32PDATTGXC5QQPRIK4X2VP7","target":"record","payload":{"canonical_record":{"source":{"id":"2209.09839","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-09-20T16:32:06Z","cross_cats_sorted":[],"title_canon_sha256":"e336def0fb6c38029283979d659f48146d4cfe49a036f8f3ec02861f41edca08","abstract_canon_sha256":"7d7a63e6069d2b480bd43817e0ab099fa57d09be6873f8c13b9a60b80fe95350"},"schema_version":"1.0"},"canonical_sha256":"b74dbd3c609ccd7176107c50ae5f557fcb8c1253e25e3868468712eee7ed2886","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:59:35.109822Z","signature_b64":"tTYOys3vznY+l+l2q0fN8Jqr7x708GxI4SgFLfnUF7HxjzuAytnAFglpeilNjwteyaS2/QgNk37dNQngR/WkBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b74dbd3c609ccd7176107c50ae5f557fcb8c1253e25e3868468712eee7ed2886","last_reissued_at":"2026-07-05T04:59:35.109402Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:59:35.109402Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2209.09839","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":"2026-07-05T04:59:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3cy0Ud2Q/jHbGXF1+GJuEY49Gbq/UICKiSbAEj1bgmtsXariI2C4Nj++B6lHGOKo8vnzDKz+VlzFaLVtLUuYDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T06:25:37.838536Z"},"content_sha256":"ccc9abb7dcae5ef4c4af69aee18ca86657fd99a19672b99d57b0156b5d67627b","schema_version":"1.0","event_id":"sha256:ccc9abb7dcae5ef4c4af69aee18ca86657fd99a19672b99d57b0156b5d67627b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:W5G32PDATTGXC5QQPRIK4X2VP7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Improving Replay-Based Continual Semantic Segmentation with Smart Data Selection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bj\\\"orn Mauthe, J\\\"urgen Beyerer, Tobias Kalb","submitted_at":"2022-09-20T16:32:06Z","abstract_excerpt":"Continual learning for Semantic Segmentation (CSS) is a rapidly emerging field, in which the capabilities of the segmentation model are incrementally improved by learning new classes or new domains. A central challenge in Continual Learning is overcoming the effects of catastrophic forgetting, which refers to the sudden drop in accuracy on previously learned tasks after the model is trained on new classes or domains. In continual classification this challenge is often overcome by replaying a small selection of samples from previous tasks, however replay is rarely considered in CSS. Therefore, "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2209.09839","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/2209.09839/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":"2026-07-05T04:59:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SR2NC7Bg5tkp97Mn7NuDEfJask6zPwzMOJT8CIn1Js1p23dBs3g7okGRIP75o7ejYTxLKqkxEXO4RrhLremFDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T06:25:37.839463Z"},"content_sha256":"79762cc20dd09580ce23b48228389acff432fb124189ac1bd8575b1387a64265","schema_version":"1.0","event_id":"sha256:79762cc20dd09580ce23b48228389acff432fb124189ac1bd8575b1387a64265"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/W5G32PDATTGXC5QQPRIK4X2VP7/bundle.json","state_url":"https://pith.science/pith/W5G32PDATTGXC5QQPRIK4X2VP7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/W5G32PDATTGXC5QQPRIK4X2VP7/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":"2026-08-04T06:25:37Z","links":{"resolver":"https://pith.science/pith/W5G32PDATTGXC5QQPRIK4X2VP7","bundle":"https://pith.science/pith/W5G32PDATTGXC5QQPRIK4X2VP7/bundle.json","state":"https://pith.science/pith/W5G32PDATTGXC5QQPRIK4X2VP7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/W5G32PDATTGXC5QQPRIK4X2VP7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:W5G32PDATTGXC5QQPRIK4X2VP7","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":"7d7a63e6069d2b480bd43817e0ab099fa57d09be6873f8c13b9a60b80fe95350","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-09-20T16:32:06Z","title_canon_sha256":"e336def0fb6c38029283979d659f48146d4cfe49a036f8f3ec02861f41edca08"},"schema_version":"1.0","source":{"id":"2209.09839","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2209.09839","created_at":"2026-07-05T04:59:35Z"},{"alias_kind":"arxiv_version","alias_value":"2209.09839v1","created_at":"2026-07-05T04:59:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2209.09839","created_at":"2026-07-05T04:59:35Z"},{"alias_kind":"pith_short_12","alias_value":"W5G32PDATTGX","created_at":"2026-07-05T04:59:35Z"},{"alias_kind":"pith_short_16","alias_value":"W5G32PDATTGXC5QQ","created_at":"2026-07-05T04:59:35Z"},{"alias_kind":"pith_short_8","alias_value":"W5G32PDA","created_at":"2026-07-05T04:59:35Z"}],"graph_snapshots":[{"event_id":"sha256:79762cc20dd09580ce23b48228389acff432fb124189ac1bd8575b1387a64265","target":"graph","created_at":"2026-07-05T04:59:35Z","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/2209.09839/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Continual learning for Semantic Segmentation (CSS) is a rapidly emerging field, in which the capabilities of the segmentation model are incrementally improved by learning new classes or new domains. A central challenge in Continual Learning is overcoming the effects of catastrophic forgetting, which refers to the sudden drop in accuracy on previously learned tasks after the model is trained on new classes or domains. In continual classification this challenge is often overcome by replaying a small selection of samples from previous tasks, however replay is rarely considered in CSS. Therefore, ","authors_text":"Bj\\\"orn Mauthe, J\\\"urgen Beyerer, Tobias Kalb","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-09-20T16:32:06Z","title":"Improving Replay-Based Continual Semantic Segmentation with Smart Data Selection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2209.09839","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:ccc9abb7dcae5ef4c4af69aee18ca86657fd99a19672b99d57b0156b5d67627b","target":"record","created_at":"2026-07-05T04:59:35Z","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":"7d7a63e6069d2b480bd43817e0ab099fa57d09be6873f8c13b9a60b80fe95350","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-09-20T16:32:06Z","title_canon_sha256":"e336def0fb6c38029283979d659f48146d4cfe49a036f8f3ec02861f41edca08"},"schema_version":"1.0","source":{"id":"2209.09839","kind":"arxiv","version":1}},"canonical_sha256":"b74dbd3c609ccd7176107c50ae5f557fcb8c1253e25e3868468712eee7ed2886","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b74dbd3c609ccd7176107c50ae5f557fcb8c1253e25e3868468712eee7ed2886","first_computed_at":"2026-07-05T04:59:35.109402Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:59:35.109402Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"tTYOys3vznY+l+l2q0fN8Jqr7x708GxI4SgFLfnUF7HxjzuAytnAFglpeilNjwteyaS2/QgNk37dNQngR/WkBA==","signature_status":"signed_v1","signed_at":"2026-07-05T04:59:35.109822Z","signed_message":"canonical_sha256_bytes"},"source_id":"2209.09839","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ccc9abb7dcae5ef4c4af69aee18ca86657fd99a19672b99d57b0156b5d67627b","sha256:79762cc20dd09580ce23b48228389acff432fb124189ac1bd8575b1387a64265"],"state_sha256":"ce5db60e0ba4e124cb4432c1cea0fa666e5109cdb13c2a29907ba89aa7a99a0c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aBrqeG3+vXHlpnjBHJ1bgvucrSs9XdTL4hU7sgfhdkxWjx0E3TXfMBFws39z7C0T/AlDUGGMG2r9mCFkBaA1BA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T06:25:37.846394Z","bundle_sha256":"4dd3324f05896fc62a21b0c328e83896db514e48dd9af8f57622a113c650539d"}}