{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:2XZFJ5DN7SBXG4DB33H4AEBBI2","short_pith_number":"pith:2XZFJ5DN","canonical_record":{"source":{"id":"2506.17645","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-06-21T08:56:45Z","cross_cats_sorted":[],"title_canon_sha256":"d05deed424db2b38c87ad163538e0302b6c73edeeed3ca77f2f9f50a8c8b2142","abstract_canon_sha256":"602f5a0f9cf471c6e03ad81d092ca800ee8222cbdff7b2af84ab74893ffdbcf5"},"schema_version":"1.0"},"canonical_sha256":"d5f254f46dfc83737061decfc0102146a1935dd4dd59a3edf3b47f811615f44d","source":{"kind":"arxiv","id":"2506.17645","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.17645","created_at":"2026-07-05T11:25:21Z"},{"alias_kind":"arxiv_version","alias_value":"2506.17645v1","created_at":"2026-07-05T11:25:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.17645","created_at":"2026-07-05T11:25:21Z"},{"alias_kind":"pith_short_12","alias_value":"2XZFJ5DN7SBX","created_at":"2026-07-05T11:25:21Z"},{"alias_kind":"pith_short_16","alias_value":"2XZFJ5DN7SBXG4DB","created_at":"2026-07-05T11:25:21Z"},{"alias_kind":"pith_short_8","alias_value":"2XZFJ5DN","created_at":"2026-07-05T11:25:21Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:2XZFJ5DN7SBXG4DB33H4AEBBI2","target":"record","payload":{"canonical_record":{"source":{"id":"2506.17645","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-06-21T08:56:45Z","cross_cats_sorted":[],"title_canon_sha256":"d05deed424db2b38c87ad163538e0302b6c73edeeed3ca77f2f9f50a8c8b2142","abstract_canon_sha256":"602f5a0f9cf471c6e03ad81d092ca800ee8222cbdff7b2af84ab74893ffdbcf5"},"schema_version":"1.0"},"canonical_sha256":"d5f254f46dfc83737061decfc0102146a1935dd4dd59a3edf3b47f811615f44d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:25:21.006143Z","signature_b64":"029f50CY7g/23Z+/R15jZJEAPMCYWq1ci/Z5Y2UoiyuVefGWu2kY2EdHMG3I7DwOtwYpaW6TKE9j9SV+5fJMCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d5f254f46dfc83737061decfc0102146a1935dd4dd59a3edf3b47f811615f44d","last_reissued_at":"2026-07-05T11:25:21.005632Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:25:21.005632Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2506.17645","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":"2026-07-05T11:25:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"F61YLTte1g3RbGHYzDHQbIzpOOF5P/CFrHnUWLPZdgCHySC2puEa91PkpbRwIfAV0g/UoUDofQEnyFhm9r+aAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T10:10:57.896491Z"},"content_sha256":"bbcd43d7ba68ad093da58fb7d974253538b226e2f4710fcec9b44f703ffb5d50","schema_version":"1.0","event_id":"sha256:bbcd43d7ba68ad093da58fb7d974253538b226e2f4710fcec9b44f703ffb5d50"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:2XZFJ5DN7SBXG4DB33H4AEBBI2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Histopathology Image Report Generation by Vision Language Model with Multimodal In-Context Learning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Fu-En Yang, Hsuan-Yu Fan, Shih-Wen Liu, Wei-Ta Chu, Yu-Chiang Frank Wang","submitted_at":"2025-06-21T08:56:45Z","abstract_excerpt":"Automating medical report generation from histopathology images is a critical challenge requiring effective visual representations and domain-specific knowledge. Inspired by the common practices of human experts, we propose an in-context learning framework called PathGenIC that integrates context derived from the training set with a multimodal in-context learning (ICL) mechanism. Our method dynamically retrieves semantically similar whole slide image (WSI)-report pairs and incorporates adaptive feedback to enhance contextual relevance and generation quality. Evaluated on the HistGen benchmark,"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.17645","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/2506.17645/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":"2026-07-05T11:25:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Adv6AlzUVBC7KM7mDI/uDIUhLt8P8/4GnqFUAIBwlaUNpkn9k+JoniqYjiDeXiavU4tDEEgCP+TkvSdj9AYvBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T10:10:57.959970Z"},"content_sha256":"e35b9ef6c0e1380f5d4ccf87b69cfb76aecb2aeb24c9850a30d77837bcfd31ce","schema_version":"1.0","event_id":"sha256:e35b9ef6c0e1380f5d4ccf87b69cfb76aecb2aeb24c9850a30d77837bcfd31ce"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2XZFJ5DN7SBXG4DB33H4AEBBI2/bundle.json","state_url":"https://pith.science/pith/2XZFJ5DN7SBXG4DB33H4AEBBI2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2XZFJ5DN7SBXG4DB33H4AEBBI2/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":"2026-08-18T10:10:57Z","links":{"resolver":"https://pith.science/pith/2XZFJ5DN7SBXG4DB33H4AEBBI2","bundle":"https://pith.science/pith/2XZFJ5DN7SBXG4DB33H4AEBBI2/bundle.json","state":"https://pith.science/pith/2XZFJ5DN7SBXG4DB33H4AEBBI2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2XZFJ5DN7SBXG4DB33H4AEBBI2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:2XZFJ5DN7SBXG4DB33H4AEBBI2","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":"602f5a0f9cf471c6e03ad81d092ca800ee8222cbdff7b2af84ab74893ffdbcf5","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-06-21T08:56:45Z","title_canon_sha256":"d05deed424db2b38c87ad163538e0302b6c73edeeed3ca77f2f9f50a8c8b2142"},"schema_version":"1.0","source":{"id":"2506.17645","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.17645","created_at":"2026-07-05T11:25:21Z"},{"alias_kind":"arxiv_version","alias_value":"2506.17645v1","created_at":"2026-07-05T11:25:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.17645","created_at":"2026-07-05T11:25:21Z"},{"alias_kind":"pith_short_12","alias_value":"2XZFJ5DN7SBX","created_at":"2026-07-05T11:25:21Z"},{"alias_kind":"pith_short_16","alias_value":"2XZFJ5DN7SBXG4DB","created_at":"2026-07-05T11:25:21Z"},{"alias_kind":"pith_short_8","alias_value":"2XZFJ5DN","created_at":"2026-07-05T11:25:21Z"}],"graph_snapshots":[{"event_id":"sha256:e35b9ef6c0e1380f5d4ccf87b69cfb76aecb2aeb24c9850a30d77837bcfd31ce","target":"graph","created_at":"2026-07-05T11:25:21Z","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/2506.17645/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Automating medical report generation from histopathology images is a critical challenge requiring effective visual representations and domain-specific knowledge. Inspired by the common practices of human experts, we propose an in-context learning framework called PathGenIC that integrates context derived from the training set with a multimodal in-context learning (ICL) mechanism. Our method dynamically retrieves semantically similar whole slide image (WSI)-report pairs and incorporates adaptive feedback to enhance contextual relevance and generation quality. Evaluated on the HistGen benchmark,","authors_text":"Fu-En Yang, Hsuan-Yu Fan, Shih-Wen Liu, Wei-Ta Chu, Yu-Chiang Frank Wang","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-06-21T08:56:45Z","title":"Histopathology Image Report Generation by Vision Language Model with Multimodal In-Context Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.17645","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:bbcd43d7ba68ad093da58fb7d974253538b226e2f4710fcec9b44f703ffb5d50","target":"record","created_at":"2026-07-05T11:25:21Z","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":"602f5a0f9cf471c6e03ad81d092ca800ee8222cbdff7b2af84ab74893ffdbcf5","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-06-21T08:56:45Z","title_canon_sha256":"d05deed424db2b38c87ad163538e0302b6c73edeeed3ca77f2f9f50a8c8b2142"},"schema_version":"1.0","source":{"id":"2506.17645","kind":"arxiv","version":1}},"canonical_sha256":"d5f254f46dfc83737061decfc0102146a1935dd4dd59a3edf3b47f811615f44d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d5f254f46dfc83737061decfc0102146a1935dd4dd59a3edf3b47f811615f44d","first_computed_at":"2026-07-05T11:25:21.005632Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:25:21.005632Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"029f50CY7g/23Z+/R15jZJEAPMCYWq1ci/Z5Y2UoiyuVefGWu2kY2EdHMG3I7DwOtwYpaW6TKE9j9SV+5fJMCw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:25:21.006143Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.17645","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:bbcd43d7ba68ad093da58fb7d974253538b226e2f4710fcec9b44f703ffb5d50","sha256:e35b9ef6c0e1380f5d4ccf87b69cfb76aecb2aeb24c9850a30d77837bcfd31ce"],"state_sha256":"ac98dd299ec7b0fc23fecf366c99065766ed79c2afcb8bc4fcfa80f83b22737c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0xBnzo0Gvyse0YTAU4leGSWXxNf0EJ4mqXSOevDad9PaDDqAVHnqchdSP+hSe8SAjf3kQhEdPg+bE6W8GNPCDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-18T10:10:57.971658Z","bundle_sha256":"9a66b50beddade6cecfe1f88b34ec6a6ecdd7d706b2f7a559dd115b8d84e6473"}}