{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:7QV34EWNOPSJT2M5O7O6ERX4CB","short_pith_number":"pith:7QV34EWN","canonical_record":{"source":{"id":"2605.22050","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-05-21T06:36:59Z","cross_cats_sorted":[],"title_canon_sha256":"f8e5ea125f2ba1142ee589d615481ef0340e798af2fbade5f038758d6104503f","abstract_canon_sha256":"4d6563ff77b77819f38d637a2469e3d6e7a666961b6c1db2b7f59068ebdea3f1"},"schema_version":"1.0"},"canonical_sha256":"fc2bbe12cd73e499e99d77dde246fc106e0c13d18aefb8fa853e6828572c4aa0","source":{"kind":"arxiv","id":"2605.22050","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.22050","created_at":"2026-05-22T01:04:22Z"},{"alias_kind":"arxiv_version","alias_value":"2605.22050v1","created_at":"2026-05-22T01:04:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.22050","created_at":"2026-05-22T01:04:22Z"},{"alias_kind":"pith_short_12","alias_value":"7QV34EWNOPSJ","created_at":"2026-05-22T01:04:22Z"},{"alias_kind":"pith_short_16","alias_value":"7QV34EWNOPSJT2M5","created_at":"2026-05-22T01:04:22Z"},{"alias_kind":"pith_short_8","alias_value":"7QV34EWN","created_at":"2026-05-22T01:04:22Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:7QV34EWNOPSJT2M5O7O6ERX4CB","target":"record","payload":{"canonical_record":{"source":{"id":"2605.22050","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-05-21T06:36:59Z","cross_cats_sorted":[],"title_canon_sha256":"f8e5ea125f2ba1142ee589d615481ef0340e798af2fbade5f038758d6104503f","abstract_canon_sha256":"4d6563ff77b77819f38d637a2469e3d6e7a666961b6c1db2b7f59068ebdea3f1"},"schema_version":"1.0"},"canonical_sha256":"fc2bbe12cd73e499e99d77dde246fc106e0c13d18aefb8fa853e6828572c4aa0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-22T01:04:22.415464Z","signature_b64":"o8tD60/H/6MuE9/MHbBlTuCwrm6WbHMLCn4DCrg3PXQgmFuigQjjTqA2BrMiK9ZxKuZcd63Qs6qrfXOtYdS1CA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fc2bbe12cd73e499e99d77dde246fc106e0c13d18aefb8fa853e6828572c4aa0","last_reissued_at":"2026-05-22T01:04:22.414642Z","signature_status":"signed_v1","first_computed_at":"2026-05-22T01:04:22.414642Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.22050","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":"2026-05-22T01:04:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tKYgVsDjdSvCiRr10VQHQfWW/LKQWbtTqnciEd4d50Te1yitpOiYN+gbN6z9PNqs9G707n4juxRJ4R2qaBW9Dg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T22:09:38.269017Z"},"content_sha256":"5a90a3cff2f1a4112cf59daf82b708d61af9a41d53aca36ce8155865b447b254","schema_version":"1.0","event_id":"sha256:5a90a3cff2f1a4112cf59daf82b708d61af9a41d53aca36ce8155865b447b254"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:7QV34EWNOPSJT2M5O7O6ERX4CB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Broken Memories: Detecting and Mitigating Memorization in Diffusion Models with Degraded Generations","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chen Chen, Feifei Li, Geng Hong, Min Yang, Mi Zhang, Xiaoyu You, Yuanmin Huang","submitted_at":"2026-05-21T06:36:59Z","abstract_excerpt":"While diffusion models excel at generating high-quality images, their tendency to memorize training data poses significant privacy and copyright risks. In this work, we for the first time identify that memorization induces internal numerical instability, often manifesting as visually ``broken'' artifacts. Inspired by stability analysis in numerical methods, we introduce empirical stability regions based on latent update norms to quantitatively characterize stable behavior during generation. Leveraging this, we propose a principled, on-the-fly framework for step-wise detection and adaptive miti"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.22050","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/2605.22050/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":"2026-05-22T01:04:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"N7hFVUQBiqymUIZ8Tc7ROak1v7LZ2YInTHtSMZ9N0H7uv323KRr5MlL6c3Cq46Veb75KIMsgVLEacjeUT6PACQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T22:09:38.269767Z"},"content_sha256":"cf85e42239ba5442723ebd659ac9236ae6ee7812b0d26f1b59073016589c5753","schema_version":"1.0","event_id":"sha256:cf85e42239ba5442723ebd659ac9236ae6ee7812b0d26f1b59073016589c5753"},{"event_type":"integrity_finding","subject_pith_number":"pith:2026:7QV34EWNOPSJT2M5O7O6ERX4CB","target":"integrity","payload":{"note":"Citing paper attributes a specific factual claim to reference [26], which resolves to arXiv:2103.00020. The claim's distinctive tokens have only 7% overlap with any chunk of the cited paper's stored text (threshold for unsupported is 15%). The attribution could not be verified against the cited work.","snippet":"memorized prompts induce significantly larger guidance mag-\nnitudes and distinct attention patterns compared to non-memorized\nones.","arxiv_id":"2605.22050","detector":"citation_quote_validity","evidence":{"ref_index":26,"claim_text":"memorized prompts induce significantly larger guidance mag-\nnitudes and distinct attention patterns compared to non-memorized\nones.","claim_offset":9227,"verdict_class":"threshold_with_margin","chunks_checked":24,"cited_arxiv_id":"2103.00020","best_overlap_score":0.071,"supported_threshold":0.5,"best_overlap_chunk_id":"ecfb9641-180c-44d4-85f7-ed3c1d6f6a1e","unsupported_threshold":0.15},"severity":"advisory","ref_index":26,"audited_at":"2026-05-22T19:50:31.678044Z","event_type":"pith.integrity.v1","detected_doi":null,"detector_url":"https://pith.science/pith-integrity-protocol#citation_quote_validity","external_url":null,"finding_type":"unsupported_attribution","evidence_hash":"2624f93c91e58c387f998960a0db73b7b4a6e848892d94dd539dd8b36970693a","paper_version":1,"verdict_class":"threshold_with_margin","resolved_title":null,"detector_version":"0.1.0","detected_arxiv_id":"2103.00020","integrity_event_id":6490,"payload_sha256":"daca267f592f5a481032c6eca73ca611f9edbab82f798f67228af0de1f2135e7","signature_b64":"J1WAFkizTzbao26iSvaInBHIOqLEFZr3fXU/UXuXXQcJcqA0UEsgcoRNO8Z85MPwyzEUk5W2mcXgd1xx8Lz8AA==","signing_key_id":"pith-v1-2026-05"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-22T19:51:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fb07ydjIm54ySfWQXafGnGCaRKAUaFJyy17wnFKhJmo9jzAec2puugJYZjSvQNGzr/O1GRkrHkQZ2H29TW4oAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T22:09:38.271863Z"},"content_sha256":"ab768eb863b719ab8e7c7020a5ab362155f752aeee4b1a109015125f9eb69baa","schema_version":"1.0","event_id":"sha256:ab768eb863b719ab8e7c7020a5ab362155f752aeee4b1a109015125f9eb69baa"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7QV34EWNOPSJT2M5O7O6ERX4CB/bundle.json","state_url":"https://pith.science/pith/7QV34EWNOPSJT2M5O7O6ERX4CB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7QV34EWNOPSJT2M5O7O6ERX4CB/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":"2026-05-25T22:09:38Z","links":{"resolver":"https://pith.science/pith/7QV34EWNOPSJT2M5O7O6ERX4CB","bundle":"https://pith.science/pith/7QV34EWNOPSJT2M5O7O6ERX4CB/bundle.json","state":"https://pith.science/pith/7QV34EWNOPSJT2M5O7O6ERX4CB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7QV34EWNOPSJT2M5O7O6ERX4CB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:7QV34EWNOPSJT2M5O7O6ERX4CB","merge_version":"pith-open-graph-merge-v1","event_count":3,"valid_event_count":3,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"4d6563ff77b77819f38d637a2469e3d6e7a666961b6c1db2b7f59068ebdea3f1","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-05-21T06:36:59Z","title_canon_sha256":"f8e5ea125f2ba1142ee589d615481ef0340e798af2fbade5f038758d6104503f"},"schema_version":"1.0","source":{"id":"2605.22050","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.22050","created_at":"2026-05-22T01:04:22Z"},{"alias_kind":"arxiv_version","alias_value":"2605.22050v1","created_at":"2026-05-22T01:04:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.22050","created_at":"2026-05-22T01:04:22Z"},{"alias_kind":"pith_short_12","alias_value":"7QV34EWNOPSJ","created_at":"2026-05-22T01:04:22Z"},{"alias_kind":"pith_short_16","alias_value":"7QV34EWNOPSJT2M5","created_at":"2026-05-22T01:04:22Z"},{"alias_kind":"pith_short_8","alias_value":"7QV34EWN","created_at":"2026-05-22T01:04:22Z"}],"graph_snapshots":[{"event_id":"sha256:cf85e42239ba5442723ebd659ac9236ae6ee7812b0d26f1b59073016589c5753","target":"graph","created_at":"2026-05-22T01:04:22Z","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/2605.22050/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"While diffusion models excel at generating high-quality images, their tendency to memorize training data poses significant privacy and copyright risks. In this work, we for the first time identify that memorization induces internal numerical instability, often manifesting as visually ``broken'' artifacts. Inspired by stability analysis in numerical methods, we introduce empirical stability regions based on latent update norms to quantitatively characterize stable behavior during generation. Leveraging this, we propose a principled, on-the-fly framework for step-wise detection and adaptive miti","authors_text":"Chen Chen, Feifei Li, Geng Hong, Min Yang, Mi Zhang, Xiaoyu You, Yuanmin Huang","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-05-21T06:36:59Z","title":"Broken Memories: Detecting and Mitigating Memorization in Diffusion Models with Degraded Generations"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.22050","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":"sha256:5a90a3cff2f1a4112cf59daf82b708d61af9a41d53aca36ce8155865b447b254","target":"record","created_at":"2026-05-22T01:04:22Z","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":"4d6563ff77b77819f38d637a2469e3d6e7a666961b6c1db2b7f59068ebdea3f1","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-05-21T06:36:59Z","title_canon_sha256":"f8e5ea125f2ba1142ee589d615481ef0340e798af2fbade5f038758d6104503f"},"schema_version":"1.0","source":{"id":"2605.22050","kind":"arxiv","version":1}},"canonical_sha256":"fc2bbe12cd73e499e99d77dde246fc106e0c13d18aefb8fa853e6828572c4aa0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fc2bbe12cd73e499e99d77dde246fc106e0c13d18aefb8fa853e6828572c4aa0","first_computed_at":"2026-05-22T01:04:22.414642Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-22T01:04:22.414642Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"o8tD60/H/6MuE9/MHbBlTuCwrm6WbHMLCn4DCrg3PXQgmFuigQjjTqA2BrMiK9ZxKuZcd63Qs6qrfXOtYdS1CA==","signature_status":"signed_v1","signed_at":"2026-05-22T01:04:22.415464Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.22050","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5a90a3cff2f1a4112cf59daf82b708d61af9a41d53aca36ce8155865b447b254","sha256:cf85e42239ba5442723ebd659ac9236ae6ee7812b0d26f1b59073016589c5753","sha256:ab768eb863b719ab8e7c7020a5ab362155f752aeee4b1a109015125f9eb69baa"],"state_sha256":"4883255b7d2fb1f245a07687e9cb8a61a9a8b35f68c453ff91108512f37bd1ec"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"udHNyhL7g2mntqflQTqWcOSHjXLX31YU+DuyMsxsV61RVsm2qaKXGkW17pfpba1sGSOZgEDlmIUumaf7zIjCAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-25T22:09:38.275838Z","bundle_sha256":"9abe0d5fd23ccb80a3c369e1e3a9552849bc592fbaa5567f59571e3ed57cfddd"}}