{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:FJVQKAODMLS65YGLIGTTMU7ZAF","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":"678c0ad986cb149f6f5e0bd42c8f4021907e95f7302eacd786c4c2a5a53ceff8","cross_cats_sorted":["cs.GR","cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2025-01-02T18:52:11Z","title_canon_sha256":"f27b4bbff3ebaa47dca5b4840c7c4d2e7d328cda7179c87600d65872c47dd850"},"schema_version":"1.0","source":{"id":"2501.01407","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.01407","created_at":"2026-07-05T09:56:19Z"},{"alias_kind":"arxiv_version","alias_value":"2501.01407v1","created_at":"2026-07-05T09:56:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.01407","created_at":"2026-07-05T09:56:19Z"},{"alias_kind":"pith_short_12","alias_value":"FJVQKAODMLS6","created_at":"2026-07-05T09:56:19Z"},{"alias_kind":"pith_short_16","alias_value":"FJVQKAODMLS65YGL","created_at":"2026-07-05T09:56:19Z"},{"alias_kind":"pith_short_8","alias_value":"FJVQKAOD","created_at":"2026-07-05T09:56:19Z"}],"graph_snapshots":[{"event_id":"sha256:52d752c83d35b054ff63702bb8cadb789ae6762494974a1feb04c654f8b1ae93","target":"graph","created_at":"2026-07-05T09:56:19Z","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/2501.01407/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Personalizing text-to-image models to generate images of specific subjects across diverse scenes and styles is a rapidly advancing field. Current approaches often face challenges in maintaining a balance between identity preservation and alignment with the input text prompt. Some methods rely on a single textual token to represent a subject, which limits expressiveness, while others employ richer representations but disrupt the model's prior, diminishing prompt alignment. In this work, we introduce Nested Attention, a novel mechanism that injects a rich and expressive image representation into","authors_text":"Daniel Cohen-Or, Daniil Ostashev, Kfir Aberman, Or Patashnik, Rinon Gal, Sergey Tulyakov","cross_cats":["cs.GR","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2025-01-02T18:52:11Z","title":"Nested Attention: Semantic-aware Attention Values for Concept Personalization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.01407","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":"sha256:16344c6f27502d086b86dcf6dee97e3be58d72dd9a0fc5c5f1d43f19c553e783","target":"record","created_at":"2026-07-05T09:56:19Z","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":"678c0ad986cb149f6f5e0bd42c8f4021907e95f7302eacd786c4c2a5a53ceff8","cross_cats_sorted":["cs.GR","cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2025-01-02T18:52:11Z","title_canon_sha256":"f27b4bbff3ebaa47dca5b4840c7c4d2e7d328cda7179c87600d65872c47dd850"},"schema_version":"1.0","source":{"id":"2501.01407","kind":"arxiv","version":1}},"canonical_sha256":"2a6b0501c362e5eee0cb41a73653f90147f8b6a72ffe488c1478441030641268","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2a6b0501c362e5eee0cb41a73653f90147f8b6a72ffe488c1478441030641268","first_computed_at":"2026-07-05T09:56:19.427008Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:56:19.427008Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"wJnJBUsDKD3spa6V36+CglX5wJDsYZWLMiKw4i7U71H+glq2dDEWJ90IIwAzkwBs+mT6bhQo4jts95Y/RDEACA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:56:19.427475Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.01407","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:16344c6f27502d086b86dcf6dee97e3be58d72dd9a0fc5c5f1d43f19c553e783","sha256:52d752c83d35b054ff63702bb8cadb789ae6762494974a1feb04c654f8b1ae93"],"state_sha256":"322fda05e7714c6e1be5874f1424f20281652637322c26b3fccea0679ed742de"}