{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:PA6LWRCGXOM47QGF4QZPORB5D4","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":"fb1672b8e695cf3db70e9572dc2eb2b21092f971fbb87279dee23d1b27585ef1","cross_cats_sorted":["cs.CL","cs.MM"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-11-21T10:37:56Z","title_canon_sha256":"f503d3f3d9d0402b9d9f0106864967bb2b2ab9a94a4aa1d9c440d45262b0b2d0"},"schema_version":"1.0","source":{"id":"2211.11337","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.11337","created_at":"2026-07-05T10:07:22Z"},{"alias_kind":"arxiv_version","alias_value":"2211.11337v4","created_at":"2026-07-05T10:07:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.11337","created_at":"2026-07-05T10:07:22Z"},{"alias_kind":"pith_short_12","alias_value":"PA6LWRCGXOM4","created_at":"2026-07-05T10:07:22Z"},{"alias_kind":"pith_short_16","alias_value":"PA6LWRCGXOM47QGF","created_at":"2026-07-05T10:07:22Z"},{"alias_kind":"pith_short_8","alias_value":"PA6LWRCG","created_at":"2026-07-05T10:07:22Z"}],"graph_snapshots":[{"event_id":"sha256:c0d94f784972845c75c4ddbd9446b077f284cd8452dc1767dd0ae6e3a2b21bc5","target":"graph","created_at":"2026-07-05T10:07:22Z","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/2211.11337/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"State-of-the-arts text-to-image generation models such as Imagen and Stable Diffusion Model have succeed remarkable progresses in synthesizing high-quality, feature-rich images with high resolution guided by human text prompts. Since certain characteristics of image content \\emph{e.g.}, very specific object entities or styles, are very hard to be accurately described by text, some example-based image generation approaches have been proposed, \\emph{i.e.} generating new concepts based on absorbing the salient features of a few input references. Despite of acknowledged successes, these methods ha","authors_text":"Liang Lin, Pengxu Wei, ZiYi Dong","cross_cats":["cs.CL","cs.MM"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-11-21T10:37:56Z","title":"DreamArtist++: Controllable One-Shot Text-to-Image Generation via Positive-Negative Adapter"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.11337","kind":"arxiv","version":4},"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":"sha256:77b61052e64df733d814973cd9d5f06b798b2b48f0fad34c7137fbdb57398ef0","target":"record","created_at":"2026-07-05T10:07:22Z","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":"fb1672b8e695cf3db70e9572dc2eb2b21092f971fbb87279dee23d1b27585ef1","cross_cats_sorted":["cs.CL","cs.MM"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-11-21T10:37:56Z","title_canon_sha256":"f503d3f3d9d0402b9d9f0106864967bb2b2ab9a94a4aa1d9c440d45262b0b2d0"},"schema_version":"1.0","source":{"id":"2211.11337","kind":"arxiv","version":4}},"canonical_sha256":"783cbb4446bb99cfc0c5e432f7443d1f3a297f9399d9b8c435dceaf7ceb557c3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"783cbb4446bb99cfc0c5e432f7443d1f3a297f9399d9b8c435dceaf7ceb557c3","first_computed_at":"2026-07-05T10:07:22.110827Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:07:22.110827Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"iVXB66lpt0rVRKZdc4dlw80UrtYxsBvkzAu3j5xq0CL7RbeouaiDRQnuCkTHG9Lu9VVjV5wMIvaHboLuqcWEAw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:07:22.111283Z","signed_message":"canonical_sha256_bytes"},"source_id":"2211.11337","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:77b61052e64df733d814973cd9d5f06b798b2b48f0fad34c7137fbdb57398ef0","sha256:c0d94f784972845c75c4ddbd9446b077f284cd8452dc1767dd0ae6e3a2b21bc5"],"state_sha256":"a27ecf88e74d47b375605cb251c6a1978d9e6f040e1c2801f5870cfe18c8906c"}