{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:27QZILTGV2QNFYS7MQTLY3ADEV","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":"29cca52a9f5eee8a4c022cea80b60ccd9654dd9b2f6abfea477b586ab65e9247","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-08-15T03:02:36Z","title_canon_sha256":"eae9f78e3b81bfb0be8ee0b0c1f723d3131e98e2cad4feefc61c7d86930896ff"},"schema_version":"1.0","source":{"id":"2508.11176","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.11176","created_at":"2026-07-05T11:54:19Z"},{"alias_kind":"arxiv_version","alias_value":"2508.11176v1","created_at":"2026-07-05T11:54:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.11176","created_at":"2026-07-05T11:54:19Z"},{"alias_kind":"pith_short_12","alias_value":"27QZILTGV2QN","created_at":"2026-07-05T11:54:19Z"},{"alias_kind":"pith_short_16","alias_value":"27QZILTGV2QNFYS7","created_at":"2026-07-05T11:54:19Z"},{"alias_kind":"pith_short_8","alias_value":"27QZILTG","created_at":"2026-07-05T11:54:19Z"}],"graph_snapshots":[{"event_id":"sha256:62501af9df24a6e0c6a23889bc96cf8476cf916fbecec57878e589d3839f1456","target":"graph","created_at":"2026-07-05T11:54:19Z","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/2508.11176/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Adapter-based approaches have garnered attention for fine-tuning pre-trained Vision-Language Models (VLMs) on few-shot classification tasks. These methods strive to develop a lightweight module that better aligns visual and (category) textual representations, thereby enhancing performance on downstream few-shot learning tasks. However, existing adapters generally learn/align (category) textual-visual modalities via explicit spatial proximity in the underlying embedding space, which i) fails to capture the inherent one-to-many associations between categories and image samples and ii) struggles ","authors_text":"Bin Luo, Bo Jiang, Jin Tang, Xiao Wang, Yuhe Ding, Yumiao Zhao","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-08-15T03:02:36Z","title":"Fine-Grained VLM Fine-tuning via Latent Hierarchical Adapter Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.11176","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":"sha256:7edd4d67773c676ef1d15c0d2f44c8f506357aab5a1a77bd7918d8c635de2f5a","target":"record","created_at":"2026-07-05T11:54:19Z","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":"29cca52a9f5eee8a4c022cea80b60ccd9654dd9b2f6abfea477b586ab65e9247","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-08-15T03:02:36Z","title_canon_sha256":"eae9f78e3b81bfb0be8ee0b0c1f723d3131e98e2cad4feefc61c7d86930896ff"},"schema_version":"1.0","source":{"id":"2508.11176","kind":"arxiv","version":1}},"canonical_sha256":"d7e1942e66aea0d2e25f6426bc6c032551947134a20cf4932f6f5ee4ea87dc7e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d7e1942e66aea0d2e25f6426bc6c032551947134a20cf4932f6f5ee4ea87dc7e","first_computed_at":"2026-07-05T11:54:19.920430Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:54:19.920430Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"LhZQ++dcuTuUPXcvfXPw6AN9VkIdlxVd8XW26/2T3O3kOZhYlmfLColWyWs7W0T7U39YN0mi9B+Cuhnh7x1lDw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:54:19.920890Z","signed_message":"canonical_sha256_bytes"},"source_id":"2508.11176","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7edd4d67773c676ef1d15c0d2f44c8f506357aab5a1a77bd7918d8c635de2f5a","sha256:62501af9df24a6e0c6a23889bc96cf8476cf916fbecec57878e589d3839f1456"],"state_sha256":"f431aa9c2d8a4c6bcaf9e1aaa8d0cce414ef7da0f51c690c06a6026086bd20d7"}