{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:QNCTE5H5NNSQF77YQPYN4SILYB","short_pith_number":"pith:QNCTE5H5","canonical_record":{"source":{"id":"2501.18439","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-30T15:47:59Z","cross_cats_sorted":["q-bio.BM"],"title_canon_sha256":"71fcfac94c555989c641143d2e16aabda1fdba56f84f07d8dfb958a95c6c9753","abstract_canon_sha256":"458553b8a67f86142be1f2da75e1714ff67972645c4e98e36bf49193afd4b507"},"schema_version":"1.0"},"canonical_sha256":"83453274fd6b6502fff883f0de490bc053f38ca4fb21902cf15a0c952fd8ddeb","source":{"kind":"arxiv","id":"2501.18439","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.18439","created_at":"2026-07-05T10:07:34Z"},{"alias_kind":"arxiv_version","alias_value":"2501.18439v1","created_at":"2026-07-05T10:07:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.18439","created_at":"2026-07-05T10:07:34Z"},{"alias_kind":"pith_short_12","alias_value":"QNCTE5H5NNSQ","created_at":"2026-07-05T10:07:34Z"},{"alias_kind":"pith_short_16","alias_value":"QNCTE5H5NNSQF77Y","created_at":"2026-07-05T10:07:34Z"},{"alias_kind":"pith_short_8","alias_value":"QNCTE5H5","created_at":"2026-07-05T10:07:34Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:QNCTE5H5NNSQF77YQPYN4SILYB","target":"record","payload":{"canonical_record":{"source":{"id":"2501.18439","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-30T15:47:59Z","cross_cats_sorted":["q-bio.BM"],"title_canon_sha256":"71fcfac94c555989c641143d2e16aabda1fdba56f84f07d8dfb958a95c6c9753","abstract_canon_sha256":"458553b8a67f86142be1f2da75e1714ff67972645c4e98e36bf49193afd4b507"},"schema_version":"1.0"},"canonical_sha256":"83453274fd6b6502fff883f0de490bc053f38ca4fb21902cf15a0c952fd8ddeb","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:07:34.137352Z","signature_b64":"Zt1+WiZs4qcFpwjUh76DpJgkgaKiXAyx7MB+ryIigzIGSkT0qlWSdeQypTP6mYZ0JhUIwTnWUWXMHjNUnhFEAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"83453274fd6b6502fff883f0de490bc053f38ca4fb21902cf15a0c952fd8ddeb","last_reissued_at":"2026-07-05T10:07:34.136929Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:07:34.136929Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2501.18439","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":"2026-07-05T10:07:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HjcXDZYVXwIQkdOLX8eD8N5Pl1L6VJsGwOvFaAHLQGX0d9TKVycjMFGH3PqyM56gvOIQT4aks7jHr/BuJMJwBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T19:54:26.172281Z"},"content_sha256":"b6d4079bdef05b37cd1e0e916eab9e0802306f4982ad3b797cadb410e89f0a22","schema_version":"1.0","event_id":"sha256:b6d4079bdef05b37cd1e0e916eab9e0802306f4982ad3b797cadb410e89f0a22"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:QNCTE5H5NNSQF77YQPYN4SILYB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"MolGraph-xLSTM: A graph-based dual-level xLSTM framework with multi-head mixture-of-experts for enhanced molecular representation and interpretability","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["q-bio.BM"],"primary_cat":"cs.LG","authors_text":"Carson K. Leung, Pingzhao Hu, Yan Sun, Yan Yi Li, Yutong Lu, Zihao Jing","submitted_at":"2025-01-30T15:47:59Z","abstract_excerpt":"Predicting molecular properties is essential for drug discovery, and computational methods can greatly enhance this process. Molecular graphs have become a focus for representation learning, with Graph Neural Networks (GNNs) widely used. However, GNNs often struggle with capturing long-range dependencies. To address this, we propose MolGraph-xLSTM, a novel graph-based xLSTM model that enhances feature extraction and effectively models molecule long-range interactions.\n  Our approach processes molecular graphs at two scales: atom-level and motif-level. For atom-level graphs, a GNN-based xLSTM f"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.18439","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/2501.18439/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":"2026-07-05T10:07:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pYUMAMkhxyneKl/zZL52XEoUeT4VGkuE1bZVlueThvmcXVbHimV/EIEGadYf/zGZsTHS060corhSI0E0ahItDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T19:54:26.172788Z"},"content_sha256":"83d8372bead4b868aa9eaf796bba2dae8e2366e06abf90602419d564f2ff845e","schema_version":"1.0","event_id":"sha256:83d8372bead4b868aa9eaf796bba2dae8e2366e06abf90602419d564f2ff845e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/QNCTE5H5NNSQF77YQPYN4SILYB/bundle.json","state_url":"https://pith.science/pith/QNCTE5H5NNSQF77YQPYN4SILYB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/QNCTE5H5NNSQF77YQPYN4SILYB/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":"2026-08-05T19:54:26Z","links":{"resolver":"https://pith.science/pith/QNCTE5H5NNSQF77YQPYN4SILYB","bundle":"https://pith.science/pith/QNCTE5H5NNSQF77YQPYN4SILYB/bundle.json","state":"https://pith.science/pith/QNCTE5H5NNSQF77YQPYN4SILYB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/QNCTE5H5NNSQF77YQPYN4SILYB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:QNCTE5H5NNSQF77YQPYN4SILYB","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":"458553b8a67f86142be1f2da75e1714ff67972645c4e98e36bf49193afd4b507","cross_cats_sorted":["q-bio.BM"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-30T15:47:59Z","title_canon_sha256":"71fcfac94c555989c641143d2e16aabda1fdba56f84f07d8dfb958a95c6c9753"},"schema_version":"1.0","source":{"id":"2501.18439","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.18439","created_at":"2026-07-05T10:07:34Z"},{"alias_kind":"arxiv_version","alias_value":"2501.18439v1","created_at":"2026-07-05T10:07:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.18439","created_at":"2026-07-05T10:07:34Z"},{"alias_kind":"pith_short_12","alias_value":"QNCTE5H5NNSQ","created_at":"2026-07-05T10:07:34Z"},{"alias_kind":"pith_short_16","alias_value":"QNCTE5H5NNSQF77Y","created_at":"2026-07-05T10:07:34Z"},{"alias_kind":"pith_short_8","alias_value":"QNCTE5H5","created_at":"2026-07-05T10:07:34Z"}],"graph_snapshots":[{"event_id":"sha256:83d8372bead4b868aa9eaf796bba2dae8e2366e06abf90602419d564f2ff845e","target":"graph","created_at":"2026-07-05T10:07:34Z","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/2501.18439/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Predicting molecular properties is essential for drug discovery, and computational methods can greatly enhance this process. Molecular graphs have become a focus for representation learning, with Graph Neural Networks (GNNs) widely used. However, GNNs often struggle with capturing long-range dependencies. To address this, we propose MolGraph-xLSTM, a novel graph-based xLSTM model that enhances feature extraction and effectively models molecule long-range interactions.\n  Our approach processes molecular graphs at two scales: atom-level and motif-level. For atom-level graphs, a GNN-based xLSTM f","authors_text":"Carson K. Leung, Pingzhao Hu, Yan Sun, Yan Yi Li, Yutong Lu, Zihao Jing","cross_cats":["q-bio.BM"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-30T15:47:59Z","title":"MolGraph-xLSTM: A graph-based dual-level xLSTM framework with multi-head mixture-of-experts for enhanced molecular representation and interpretability"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.18439","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:b6d4079bdef05b37cd1e0e916eab9e0802306f4982ad3b797cadb410e89f0a22","target":"record","created_at":"2026-07-05T10:07:34Z","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":"458553b8a67f86142be1f2da75e1714ff67972645c4e98e36bf49193afd4b507","cross_cats_sorted":["q-bio.BM"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-30T15:47:59Z","title_canon_sha256":"71fcfac94c555989c641143d2e16aabda1fdba56f84f07d8dfb958a95c6c9753"},"schema_version":"1.0","source":{"id":"2501.18439","kind":"arxiv","version":1}},"canonical_sha256":"83453274fd6b6502fff883f0de490bc053f38ca4fb21902cf15a0c952fd8ddeb","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"83453274fd6b6502fff883f0de490bc053f38ca4fb21902cf15a0c952fd8ddeb","first_computed_at":"2026-07-05T10:07:34.136929Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:07:34.136929Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Zt1+WiZs4qcFpwjUh76DpJgkgaKiXAyx7MB+ryIigzIGSkT0qlWSdeQypTP6mYZ0JhUIwTnWUWXMHjNUnhFEAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T10:07:34.137352Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.18439","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b6d4079bdef05b37cd1e0e916eab9e0802306f4982ad3b797cadb410e89f0a22","sha256:83d8372bead4b868aa9eaf796bba2dae8e2366e06abf90602419d564f2ff845e"],"state_sha256":"260344d0d2958438c5e07e14c3c014e00dab500d5bdfba8fe1a433b4021a6b99"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OJKPjB29E72v2d3eHwgihgr7UJcsUPLEnYdDb3iPo29WiDQgztOrhwOSjfR0Uy7a3/eNn4y5iApP4sL91cZkCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T19:54:26.176658Z","bundle_sha256":"67df38f34eb63f05c3e9d2948069e91437b73c562bb40315333d54fe23b07246"}}