{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:GULY2QZ47VK76HF2GA7EKCVDTP","short_pith_number":"pith:GULY2QZ4","canonical_record":{"source":{"id":"2403.05160","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2024-03-08T09:02:13Z","cross_cats_sorted":[],"title_canon_sha256":"db20093c4c5e342b5a9ac0dff57bbb98d2dec256551171befedeafcfd64abb1e","abstract_canon_sha256":"f63576acdf254790a6e3422953bca16ebeeca83c0b18aa64fa289598f8e6bae5"},"schema_version":"1.0"},"canonical_sha256":"35178d433cfd55ff1cba303e450aa39be545de2a1defe86057a9ed041e0c79aa","source":{"kind":"arxiv","id":"2403.05160","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.05160","created_at":"2026-07-05T09:28:11Z"},{"alias_kind":"arxiv_version","alias_value":"2403.05160v3","created_at":"2026-07-05T09:28:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.05160","created_at":"2026-07-05T09:28:11Z"},{"alias_kind":"pith_short_12","alias_value":"GULY2QZ47VK7","created_at":"2026-07-05T09:28:11Z"},{"alias_kind":"pith_short_16","alias_value":"GULY2QZ47VK76HF2","created_at":"2026-07-05T09:28:11Z"},{"alias_kind":"pith_short_8","alias_value":"GULY2QZ4","created_at":"2026-07-05T09:28:11Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:GULY2QZ47VK76HF2GA7EKCVDTP","target":"record","payload":{"canonical_record":{"source":{"id":"2403.05160","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2024-03-08T09:02:13Z","cross_cats_sorted":[],"title_canon_sha256":"db20093c4c5e342b5a9ac0dff57bbb98d2dec256551171befedeafcfd64abb1e","abstract_canon_sha256":"f63576acdf254790a6e3422953bca16ebeeca83c0b18aa64fa289598f8e6bae5"},"schema_version":"1.0"},"canonical_sha256":"35178d433cfd55ff1cba303e450aa39be545de2a1defe86057a9ed041e0c79aa","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:28:11.122811Z","signature_b64":"I/chxVsLTs+NwelE2uy6ylqGuqvO5/xOYmh8qP45l4mqPU7OjCAkNgYqJ4QZh7pEvHIQ934sGLGI2iRdoi6eCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"35178d433cfd55ff1cba303e450aa39be545de2a1defe86057a9ed041e0c79aa","last_reissued_at":"2026-07-05T09:28:11.122358Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:28:11.122358Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2403.05160","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:28:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MbNSLaGi83OQg4Pa4Z0B8Qq/ypSeP2FFAncxlCv5Mopb6KTMSAnSapzZAENEhRgTepk00s9zAI48nLNl/UlgCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T00:17:50.994357Z"},"content_sha256":"cb298a50598c3e26c8aa89740d6f4e5c354c31ca16029e7d595eee42cf467dd0","schema_version":"1.0","event_id":"sha256:cb298a50598c3e26c8aa89740d6f4e5c354c31ca16029e7d595eee42cf467dd0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:GULY2QZ47VK76HF2GA7EKCVDTP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"MamMIL: Multiple Instance Learning for Whole Slide Images with State Space Models","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Jian Zhang, Xiangyang Ji, Ye Zhang, Yifeng Wang, Yongbing Zhang, Zhi Wang, Zijie Fang","submitted_at":"2024-03-08T09:02:13Z","abstract_excerpt":"Recently, pathological diagnosis has achieved superior performance by combining deep learning models with the multiple instance learning (MIL) framework using whole slide images (WSIs). However, the giga-pixeled nature of WSIs poses a great challenge for efficient MIL. Existing studies either do not consider global dependencies among instances, or use approximations such as linear attentions to model the pair-to-pair instance interactions, which inevitably brings performance bottlenecks. To tackle this challenge, we propose a framework named MamMIL for WSI analysis by cooperating the selective"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.05160","kind":"arxiv","version":3},"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/2403.05160/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":"2026-07-05T09:28:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3FpsJ9vjaK1nivC17V0P/lVE7Bg+7kIUtCNCipmt+SapysFvorUxQhU+9jGHoBXURFjLxl3AKQd2i8jRsBXGBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T00:17:50.995140Z"},"content_sha256":"9f1d565564ef5ada19a4121a1eb51a598dd7ab99a04546ca48a6c530665bcb61","schema_version":"1.0","event_id":"sha256:9f1d565564ef5ada19a4121a1eb51a598dd7ab99a04546ca48a6c530665bcb61"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GULY2QZ47VK76HF2GA7EKCVDTP/bundle.json","state_url":"https://pith.science/pith/GULY2QZ47VK76HF2GA7EKCVDTP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GULY2QZ47VK76HF2GA7EKCVDTP/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":"2026-08-06T00:17:50Z","links":{"resolver":"https://pith.science/pith/GULY2QZ47VK76HF2GA7EKCVDTP","bundle":"https://pith.science/pith/GULY2QZ47VK76HF2GA7EKCVDTP/bundle.json","state":"https://pith.science/pith/GULY2QZ47VK76HF2GA7EKCVDTP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GULY2QZ47VK76HF2GA7EKCVDTP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:GULY2QZ47VK76HF2GA7EKCVDTP","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":"f63576acdf254790a6e3422953bca16ebeeca83c0b18aa64fa289598f8e6bae5","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2024-03-08T09:02:13Z","title_canon_sha256":"db20093c4c5e342b5a9ac0dff57bbb98d2dec256551171befedeafcfd64abb1e"},"schema_version":"1.0","source":{"id":"2403.05160","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.05160","created_at":"2026-07-05T09:28:11Z"},{"alias_kind":"arxiv_version","alias_value":"2403.05160v3","created_at":"2026-07-05T09:28:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.05160","created_at":"2026-07-05T09:28:11Z"},{"alias_kind":"pith_short_12","alias_value":"GULY2QZ47VK7","created_at":"2026-07-05T09:28:11Z"},{"alias_kind":"pith_short_16","alias_value":"GULY2QZ47VK76HF2","created_at":"2026-07-05T09:28:11Z"},{"alias_kind":"pith_short_8","alias_value":"GULY2QZ4","created_at":"2026-07-05T09:28:11Z"}],"graph_snapshots":[{"event_id":"sha256:9f1d565564ef5ada19a4121a1eb51a598dd7ab99a04546ca48a6c530665bcb61","target":"graph","created_at":"2026-07-05T09:28:11Z","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/2403.05160/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recently, pathological diagnosis has achieved superior performance by combining deep learning models with the multiple instance learning (MIL) framework using whole slide images (WSIs). However, the giga-pixeled nature of WSIs poses a great challenge for efficient MIL. Existing studies either do not consider global dependencies among instances, or use approximations such as linear attentions to model the pair-to-pair instance interactions, which inevitably brings performance bottlenecks. To tackle this challenge, we propose a framework named MamMIL for WSI analysis by cooperating the selective","authors_text":"Jian Zhang, Xiangyang Ji, Ye Zhang, Yifeng Wang, Yongbing Zhang, Zhi Wang, Zijie Fang","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2024-03-08T09:02:13Z","title":"MamMIL: Multiple Instance Learning for Whole Slide Images with State Space Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.05160","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:cb298a50598c3e26c8aa89740d6f4e5c354c31ca16029e7d595eee42cf467dd0","target":"record","created_at":"2026-07-05T09:28:11Z","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":"f63576acdf254790a6e3422953bca16ebeeca83c0b18aa64fa289598f8e6bae5","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2024-03-08T09:02:13Z","title_canon_sha256":"db20093c4c5e342b5a9ac0dff57bbb98d2dec256551171befedeafcfd64abb1e"},"schema_version":"1.0","source":{"id":"2403.05160","kind":"arxiv","version":3}},"canonical_sha256":"35178d433cfd55ff1cba303e450aa39be545de2a1defe86057a9ed041e0c79aa","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"35178d433cfd55ff1cba303e450aa39be545de2a1defe86057a9ed041e0c79aa","first_computed_at":"2026-07-05T09:28:11.122358Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:28:11.122358Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"I/chxVsLTs+NwelE2uy6ylqGuqvO5/xOYmh8qP45l4mqPU7OjCAkNgYqJ4QZh7pEvHIQ934sGLGI2iRdoi6eCA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:28:11.122811Z","signed_message":"canonical_sha256_bytes"},"source_id":"2403.05160","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:cb298a50598c3e26c8aa89740d6f4e5c354c31ca16029e7d595eee42cf467dd0","sha256:9f1d565564ef5ada19a4121a1eb51a598dd7ab99a04546ca48a6c530665bcb61"],"state_sha256":"b91143d34aa9e15ade103769812877f254f0bbdab02a3a27e09ed114bdde1e54"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6QvYankynirHsw85JkgxkeNxXt+DCqQcJzfKHDE7kywhQQteVBdG9islBxkAxb1wxZR0InPe0B7DicVoWn0uCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T00:17:51.001454Z","bundle_sha256":"177baca12c0521a16646e8ccd5037049867b3bf6e297f34cc8bcfb51c1962edf"}}