{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:WURGNKY66MYIIMSJ32HH55QLTQ","short_pith_number":"pith:WURGNKY6","canonical_record":{"source":{"id":"2410.00398","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-10-01T04:41:44Z","cross_cats_sorted":[],"title_canon_sha256":"3c1814d5ff0c0555cb333d4898fff000fff2023912ab6c59d5b77abe49906436","abstract_canon_sha256":"a0fdfd4246c7f7a2a2f120265962fe713059789f88a98a5052cb10a07ad78c91"},"schema_version":"1.0"},"canonical_sha256":"b52266ab1ef330843249de8e7ef60b9c0d0810f02a58aaf6b411434005f26fca","source":{"kind":"arxiv","id":"2410.00398","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.00398","created_at":"2026-07-05T09:14:04Z"},{"alias_kind":"arxiv_version","alias_value":"2410.00398v1","created_at":"2026-07-05T09:14:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.00398","created_at":"2026-07-05T09:14:04Z"},{"alias_kind":"pith_short_12","alias_value":"WURGNKY66MYI","created_at":"2026-07-05T09:14:04Z"},{"alias_kind":"pith_short_16","alias_value":"WURGNKY66MYIIMSJ","created_at":"2026-07-05T09:14:04Z"},{"alias_kind":"pith_short_8","alias_value":"WURGNKY6","created_at":"2026-07-05T09:14:04Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:WURGNKY66MYIIMSJ32HH55QLTQ","target":"record","payload":{"canonical_record":{"source":{"id":"2410.00398","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-10-01T04:41:44Z","cross_cats_sorted":[],"title_canon_sha256":"3c1814d5ff0c0555cb333d4898fff000fff2023912ab6c59d5b77abe49906436","abstract_canon_sha256":"a0fdfd4246c7f7a2a2f120265962fe713059789f88a98a5052cb10a07ad78c91"},"schema_version":"1.0"},"canonical_sha256":"b52266ab1ef330843249de8e7ef60b9c0d0810f02a58aaf6b411434005f26fca","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:14:04.483322Z","signature_b64":"8Ejb2Pcyadni2sBmxFcsMgSR/ZTx6rCIoPmrReRvIyz9SngUNS0NoNbKhcVxeJ6+tvaYAIngQ308eyZoQJ94Bw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b52266ab1ef330843249de8e7ef60b9c0d0810f02a58aaf6b411434005f26fca","last_reissued_at":"2026-07-05T09:14:04.482806Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:14:04.482806Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2410.00398","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":"2026-07-05T09:14:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VD8AQm9KIZJUybWYN5xAn07E8mbYqNdgRbc4n1kPx1v+jrhJc3T4a5MRdtXr8bhDFIXPLQ2vt8u23F9j7wUkAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T15:12:50.393554Z"},"content_sha256":"3a7eca1a8abc2825b8a7b5d98202f2ca4735ba4d8ac6f5808c0235bfb608814f","schema_version":"1.0","event_id":"sha256:3a7eca1a8abc2825b8a7b5d98202f2ca4735ba4d8ac6f5808c0235bfb608814f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:WURGNKY66MYIIMSJ32HH55QLTQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"CusConcept: Customized Visual Concept Decomposition with Diffusion Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Kai Han, Shaozhe Hao, Zhi Xu","submitted_at":"2024-10-01T04:41:44Z","abstract_excerpt":"Enabling generative models to decompose visual concepts from a single image is a complex and challenging problem. In this paper, we study a new and challenging task, customized concept decomposition, wherein the objective is to leverage diffusion models to decompose a single image and generate visual concepts from various perspectives. To address this challenge, we propose a two-stage framework, CusConcept (short for Customized Visual Concept Decomposition), to extract customized visual concept embedding vectors that can be embedded into prompts for text-to-image generation. In the first stage"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.00398","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/2410.00398/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":"2026-07-05T09:14:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"L3jffMwAB7imQmd/M3hpCvGmnHTRScYNLC/ZZS4STa1rjAtA74n21GyVMWbMx5eBNDhfrn4NYsVEP2MRWbL1CQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T15:12:50.393931Z"},"content_sha256":"b3a499a1001196e21ec4ac370307beed138a2824c9dabc6debe2aa5ca2aff8e1","schema_version":"1.0","event_id":"sha256:b3a499a1001196e21ec4ac370307beed138a2824c9dabc6debe2aa5ca2aff8e1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WURGNKY66MYIIMSJ32HH55QLTQ/bundle.json","state_url":"https://pith.science/pith/WURGNKY66MYIIMSJ32HH55QLTQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WURGNKY66MYIIMSJ32HH55QLTQ/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":"2026-07-07T15:12:50Z","links":{"resolver":"https://pith.science/pith/WURGNKY66MYIIMSJ32HH55QLTQ","bundle":"https://pith.science/pith/WURGNKY66MYIIMSJ32HH55QLTQ/bundle.json","state":"https://pith.science/pith/WURGNKY66MYIIMSJ32HH55QLTQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WURGNKY66MYIIMSJ32HH55QLTQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:WURGNKY66MYIIMSJ32HH55QLTQ","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":"a0fdfd4246c7f7a2a2f120265962fe713059789f88a98a5052cb10a07ad78c91","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-10-01T04:41:44Z","title_canon_sha256":"3c1814d5ff0c0555cb333d4898fff000fff2023912ab6c59d5b77abe49906436"},"schema_version":"1.0","source":{"id":"2410.00398","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.00398","created_at":"2026-07-05T09:14:04Z"},{"alias_kind":"arxiv_version","alias_value":"2410.00398v1","created_at":"2026-07-05T09:14:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.00398","created_at":"2026-07-05T09:14:04Z"},{"alias_kind":"pith_short_12","alias_value":"WURGNKY66MYI","created_at":"2026-07-05T09:14:04Z"},{"alias_kind":"pith_short_16","alias_value":"WURGNKY66MYIIMSJ","created_at":"2026-07-05T09:14:04Z"},{"alias_kind":"pith_short_8","alias_value":"WURGNKY6","created_at":"2026-07-05T09:14:04Z"}],"graph_snapshots":[{"event_id":"sha256:b3a499a1001196e21ec4ac370307beed138a2824c9dabc6debe2aa5ca2aff8e1","target":"graph","created_at":"2026-07-05T09:14:04Z","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/2410.00398/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Enabling generative models to decompose visual concepts from a single image is a complex and challenging problem. In this paper, we study a new and challenging task, customized concept decomposition, wherein the objective is to leverage diffusion models to decompose a single image and generate visual concepts from various perspectives. To address this challenge, we propose a two-stage framework, CusConcept (short for Customized Visual Concept Decomposition), to extract customized visual concept embedding vectors that can be embedded into prompts for text-to-image generation. In the first stage","authors_text":"Kai Han, Shaozhe Hao, Zhi Xu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-10-01T04:41:44Z","title":"CusConcept: Customized Visual Concept Decomposition with Diffusion Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.00398","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":"sha256:3a7eca1a8abc2825b8a7b5d98202f2ca4735ba4d8ac6f5808c0235bfb608814f","target":"record","created_at":"2026-07-05T09:14:04Z","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":"a0fdfd4246c7f7a2a2f120265962fe713059789f88a98a5052cb10a07ad78c91","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-10-01T04:41:44Z","title_canon_sha256":"3c1814d5ff0c0555cb333d4898fff000fff2023912ab6c59d5b77abe49906436"},"schema_version":"1.0","source":{"id":"2410.00398","kind":"arxiv","version":1}},"canonical_sha256":"b52266ab1ef330843249de8e7ef60b9c0d0810f02a58aaf6b411434005f26fca","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b52266ab1ef330843249de8e7ef60b9c0d0810f02a58aaf6b411434005f26fca","first_computed_at":"2026-07-05T09:14:04.482806Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:14:04.482806Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"8Ejb2Pcyadni2sBmxFcsMgSR/ZTx6rCIoPmrReRvIyz9SngUNS0NoNbKhcVxeJ6+tvaYAIngQ308eyZoQJ94Bw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:14:04.483322Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.00398","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3a7eca1a8abc2825b8a7b5d98202f2ca4735ba4d8ac6f5808c0235bfb608814f","sha256:b3a499a1001196e21ec4ac370307beed138a2824c9dabc6debe2aa5ca2aff8e1"],"state_sha256":"a1581d89b276434a666f0c8afa19a5e3952f89be095cadb65af46bbb87cc10bf"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"imt5hS9xd4nenb7ofp08HD69TyaYsCWUk6jCNw7M5LdJh6Ci0IvklFbDo/WYwexvrUFn8FyXvABK2lld0pxSDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T15:12:50.395903Z","bundle_sha256":"b1e4ffaa80083201b006b585bce23f644422bdc761269fa3914b0076c4a7784c"}}