{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:4TNIZV4RA4BOOETU6S5SOZWRP3","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":"4cba36541370ba3b8d35afc6d14d87206d3de7cb74893d3c2cdcf23b98b75bed","cross_cats_sorted":["cs.CL","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-03-26T03:05:20Z","title_canon_sha256":"7f6715c6be34930725e755ebb81cbb13df6d258400df910d6ac641c5a6ebd562"},"schema_version":"1.0","source":{"id":"2403.17343","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.17343","created_at":"2026-07-05T08:02:06Z"},{"alias_kind":"arxiv_version","alias_value":"2403.17343v3","created_at":"2026-07-05T08:02:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.17343","created_at":"2026-07-05T08:02:06Z"},{"alias_kind":"pith_short_12","alias_value":"4TNIZV4RA4BO","created_at":"2026-07-05T08:02:06Z"},{"alias_kind":"pith_short_16","alias_value":"4TNIZV4RA4BOOETU","created_at":"2026-07-05T08:02:06Z"},{"alias_kind":"pith_short_8","alias_value":"4TNIZV4R","created_at":"2026-07-05T08:02:06Z"}],"graph_snapshots":[{"event_id":"sha256:23f933236ca4ed3a27d6d034273530164c89e90672c24bb626519210b68afcbf","target":"graph","created_at":"2026-07-05T08:02:06Z","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/2403.17343/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this study, we uncover the unexpected efficacy of residual-based large language models (LLMs) as part of encoders for biomedical imaging tasks, a domain traditionally devoid of language or textual data. The approach diverges from established methodologies by utilizing a frozen transformer block, extracted from pre-trained LLMs, as an innovative encoder layer for the direct processing of visual tokens. This strategy represents a significant departure from the standard multi-modal vision-language frameworks, which typically hinge on language-driven prompts and inputs. We found that these LLMs","authors_text":"Jing Wu, Naira Hovakimyan, Suiyao Chen, Yucheng Zhou, Zhixin Lai","cross_cats":["cs.CL","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-03-26T03:05:20Z","title":"Residual-based Language Models are Free Boosters for Biomedical Imaging"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.17343","kind":"arxiv","version":3},"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:e4eaa1819c1fbad7d9c2242774b7dc567a2d98cf83a31bc4941f9f91ed9096bf","target":"record","created_at":"2026-07-05T08:02:06Z","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":"4cba36541370ba3b8d35afc6d14d87206d3de7cb74893d3c2cdcf23b98b75bed","cross_cats_sorted":["cs.CL","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-03-26T03:05:20Z","title_canon_sha256":"7f6715c6be34930725e755ebb81cbb13df6d258400df910d6ac641c5a6ebd562"},"schema_version":"1.0","source":{"id":"2403.17343","kind":"arxiv","version":3}},"canonical_sha256":"e4da8cd7910702e71274f4bb2766d17ee9d7723ce73614def10db0dc7b6df9c8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e4da8cd7910702e71274f4bb2766d17ee9d7723ce73614def10db0dc7b6df9c8","first_computed_at":"2026-07-05T08:02:06.479000Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:02:06.479000Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"7wUUjz4onRMsGqTbOb8vpFP4axIO9DQ+J4MJxHNfZyngldNnUJGVZuEERRz0MAFOFE4PpjftlUBMz5HnhPEnCg==","signature_status":"signed_v1","signed_at":"2026-07-05T08:02:06.479677Z","signed_message":"canonical_sha256_bytes"},"source_id":"2403.17343","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e4eaa1819c1fbad7d9c2242774b7dc567a2d98cf83a31bc4941f9f91ed9096bf","sha256:23f933236ca4ed3a27d6d034273530164c89e90672c24bb626519210b68afcbf"],"state_sha256":"e8425adfe5233eda1d9217ab8a8b88f66e87b3322050c15a3df11011829c754e"}