{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:PE6RSFVMQIKMUA7RHYXKHKZIVG","short_pith_number":"pith:PE6RSFVM","canonical_record":{"source":{"id":"2305.17891","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-05-29T05:35:44Z","cross_cats_sorted":[],"title_canon_sha256":"4151548c60d0127622d1de93efacf7834377765c2122d70dfcef0f3662459159","abstract_canon_sha256":"17e91ee5c841ee6a4d5eb8e1adb13a73e079fe21506caf3523de4407696fa29c"},"schema_version":"1.0"},"canonical_sha256":"793d1916ac8214ca03f13e2ea3ab28a9a38e3aff24df7ade3553f94e526403e8","source":{"kind":"arxiv","id":"2305.17891","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.17891","created_at":"2026-07-05T07:38:28Z"},{"alias_kind":"arxiv_version","alias_value":"2305.17891v2","created_at":"2026-07-05T07:38:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.17891","created_at":"2026-07-05T07:38:28Z"},{"alias_kind":"pith_short_12","alias_value":"PE6RSFVMQIKM","created_at":"2026-07-05T07:38:28Z"},{"alias_kind":"pith_short_16","alias_value":"PE6RSFVMQIKMUA7R","created_at":"2026-07-05T07:38:28Z"},{"alias_kind":"pith_short_8","alias_value":"PE6RSFVM","created_at":"2026-07-05T07:38:28Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:PE6RSFVMQIKMUA7RHYXKHKZIVG","target":"record","payload":{"canonical_record":{"source":{"id":"2305.17891","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-05-29T05:35:44Z","cross_cats_sorted":[],"title_canon_sha256":"4151548c60d0127622d1de93efacf7834377765c2122d70dfcef0f3662459159","abstract_canon_sha256":"17e91ee5c841ee6a4d5eb8e1adb13a73e079fe21506caf3523de4407696fa29c"},"schema_version":"1.0"},"canonical_sha256":"793d1916ac8214ca03f13e2ea3ab28a9a38e3aff24df7ade3553f94e526403e8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:38:28.262999Z","signature_b64":"ZnWvzdL0r1WNYA4ae8xRxQGNrD6YRriQ8Dn5tInwa9o63hp0EFIh1pJx363ay20Kb8wQyuy0VBclkpc0OnDICg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"793d1916ac8214ca03f13e2ea3ab28a9a38e3aff24df7ade3553f94e526403e8","last_reissued_at":"2026-07-05T07:38:28.262509Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:38:28.262509Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2305.17891","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:38:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rqXYv0o3ToX8QUmhaib1f7lBkIjAJXD3RPK7UdGevg7tWJkD43cNvnEGmZmbIbCreqJkVGjNff6hZOY91AQPCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T17:03:35.590283Z"},"content_sha256":"1f4a85e9cc8cb45610aed4421889a2c4f55238bc6d544d045468d2957e84f7da","schema_version":"1.0","event_id":"sha256:1f4a85e9cc8cb45610aed4421889a2c4f55238bc6d544d045468d2957e84f7da"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:PE6RSFVMQIKMUA7RHYXKHKZIVG","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"The Rise of AI Language Pathologists: Exploring Two-level Prompt Learning for Few-shot Weakly-supervised Whole Slide Image Classification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Kexue Fu, Linhao Qu, Manning Wang, Xiaoyuan Luo, Zhijian Song","submitted_at":"2023-05-29T05:35:44Z","abstract_excerpt":"This paper introduces the novel concept of few-shot weakly supervised learning for pathology Whole Slide Image (WSI) classification, denoted as FSWC. A solution is proposed based on prompt learning and the utilization of a large language model, GPT-4. Since a WSI is too large and needs to be divided into patches for processing, WSI classification is commonly approached as a Multiple Instance Learning (MIL) problem. In this context, each WSI is considered a bag, and the obtained patches are treated as instances. The objective of FSWC is to classify both bags and instances with only a limited nu"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.17891","kind":"arxiv","version":2},"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/2305.17891/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":"2026-07-05T07:38:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"klNtUS6v+tA1b6e9exQaY22Ss8UV/75wWXOrX4NeOnXYWyLrSEj7LhqfyNR6mUXUUbR2hy+6AU20zzweRG0dBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T17:03:35.590931Z"},"content_sha256":"7417ba166b32984e2aae025e6293055b497695a27edee3e18cfeca9ba61ebe40","schema_version":"1.0","event_id":"sha256:7417ba166b32984e2aae025e6293055b497695a27edee3e18cfeca9ba61ebe40"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/PE6RSFVMQIKMUA7RHYXKHKZIVG/bundle.json","state_url":"https://pith.science/pith/PE6RSFVMQIKMUA7RHYXKHKZIVG/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/PE6RSFVMQIKMUA7RHYXKHKZIVG/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":"2026-08-20T17:03:35Z","links":{"resolver":"https://pith.science/pith/PE6RSFVMQIKMUA7RHYXKHKZIVG","bundle":"https://pith.science/pith/PE6RSFVMQIKMUA7RHYXKHKZIVG/bundle.json","state":"https://pith.science/pith/PE6RSFVMQIKMUA7RHYXKHKZIVG/state.json","well_known_bundle":"https://pith.science/.well-known/pith/PE6RSFVMQIKMUA7RHYXKHKZIVG/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:PE6RSFVMQIKMUA7RHYXKHKZIVG","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":"17e91ee5c841ee6a4d5eb8e1adb13a73e079fe21506caf3523de4407696fa29c","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-05-29T05:35:44Z","title_canon_sha256":"4151548c60d0127622d1de93efacf7834377765c2122d70dfcef0f3662459159"},"schema_version":"1.0","source":{"id":"2305.17891","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.17891","created_at":"2026-07-05T07:38:28Z"},{"alias_kind":"arxiv_version","alias_value":"2305.17891v2","created_at":"2026-07-05T07:38:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.17891","created_at":"2026-07-05T07:38:28Z"},{"alias_kind":"pith_short_12","alias_value":"PE6RSFVMQIKM","created_at":"2026-07-05T07:38:28Z"},{"alias_kind":"pith_short_16","alias_value":"PE6RSFVMQIKMUA7R","created_at":"2026-07-05T07:38:28Z"},{"alias_kind":"pith_short_8","alias_value":"PE6RSFVM","created_at":"2026-07-05T07:38:28Z"}],"graph_snapshots":[{"event_id":"sha256:7417ba166b32984e2aae025e6293055b497695a27edee3e18cfeca9ba61ebe40","target":"graph","created_at":"2026-07-05T07:38:28Z","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/2305.17891/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper introduces the novel concept of few-shot weakly supervised learning for pathology Whole Slide Image (WSI) classification, denoted as FSWC. A solution is proposed based on prompt learning and the utilization of a large language model, GPT-4. Since a WSI is too large and needs to be divided into patches for processing, WSI classification is commonly approached as a Multiple Instance Learning (MIL) problem. In this context, each WSI is considered a bag, and the obtained patches are treated as instances. The objective of FSWC is to classify both bags and instances with only a limited nu","authors_text":"Kexue Fu, Linhao Qu, Manning Wang, Xiaoyuan Luo, Zhijian Song","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-05-29T05:35:44Z","title":"The Rise of AI Language Pathologists: Exploring Two-level Prompt Learning for Few-shot Weakly-supervised Whole Slide Image Classification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.17891","kind":"arxiv","version":2},"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":"sha256:1f4a85e9cc8cb45610aed4421889a2c4f55238bc6d544d045468d2957e84f7da","target":"record","created_at":"2026-07-05T07:38:28Z","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":"17e91ee5c841ee6a4d5eb8e1adb13a73e079fe21506caf3523de4407696fa29c","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-05-29T05:35:44Z","title_canon_sha256":"4151548c60d0127622d1de93efacf7834377765c2122d70dfcef0f3662459159"},"schema_version":"1.0","source":{"id":"2305.17891","kind":"arxiv","version":2}},"canonical_sha256":"793d1916ac8214ca03f13e2ea3ab28a9a38e3aff24df7ade3553f94e526403e8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"793d1916ac8214ca03f13e2ea3ab28a9a38e3aff24df7ade3553f94e526403e8","first_computed_at":"2026-07-05T07:38:28.262509Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:38:28.262509Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ZnWvzdL0r1WNYA4ae8xRxQGNrD6YRriQ8Dn5tInwa9o63hp0EFIh1pJx363ay20Kb8wQyuy0VBclkpc0OnDICg==","signature_status":"signed_v1","signed_at":"2026-07-05T07:38:28.262999Z","signed_message":"canonical_sha256_bytes"},"source_id":"2305.17891","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1f4a85e9cc8cb45610aed4421889a2c4f55238bc6d544d045468d2957e84f7da","sha256:7417ba166b32984e2aae025e6293055b497695a27edee3e18cfeca9ba61ebe40"],"state_sha256":"8e70b9aa1b4ac75505ec174d43d6135e7b62b8f59b324ee3ef2e07d2fef67562"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WUAXv7Fm7NI6otgsDCbH/KPLDN26bA1ifwHV3GLkiRZs8kinHAsEMa2kBWDhv4nO2Y2P7Xq0ZAodNaxShFCMBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-20T17:03:35.601605Z","bundle_sha256":"943a18bceca36a9ab158abde634f29d32638cd4156d29d8f31defab7844e2ed7"}}