{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:XKKIUQQB5AKVYXQJTAHVYNP23H","short_pith_number":"pith:XKKIUQQB","canonical_record":{"source":{"id":"2501.15142","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-25T08:53:42Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"259e4c6aa2f5ffe9a8c4e1833c895420dea5b91242baa8183268fa81fc84615b","abstract_canon_sha256":"336cc8d56296ac602d90413c3c198164c2ba910acf4f1c0daaec9be575a0d7cf"},"schema_version":"1.0"},"canonical_sha256":"ba948a4201e8155c5e09980f5c35fad9fb8b503790f17dc6ca1d3b424c7722a3","source":{"kind":"arxiv","id":"2501.15142","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.15142","created_at":"2026-07-05T10:05:25Z"},{"alias_kind":"arxiv_version","alias_value":"2501.15142v1","created_at":"2026-07-05T10:05:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.15142","created_at":"2026-07-05T10:05:25Z"},{"alias_kind":"pith_short_12","alias_value":"XKKIUQQB5AKV","created_at":"2026-07-05T10:05:25Z"},{"alias_kind":"pith_short_16","alias_value":"XKKIUQQB5AKVYXQJ","created_at":"2026-07-05T10:05:25Z"},{"alias_kind":"pith_short_8","alias_value":"XKKIUQQB","created_at":"2026-07-05T10:05:25Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:XKKIUQQB5AKVYXQJTAHVYNP23H","target":"record","payload":{"canonical_record":{"source":{"id":"2501.15142","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-25T08:53:42Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"259e4c6aa2f5ffe9a8c4e1833c895420dea5b91242baa8183268fa81fc84615b","abstract_canon_sha256":"336cc8d56296ac602d90413c3c198164c2ba910acf4f1c0daaec9be575a0d7cf"},"schema_version":"1.0"},"canonical_sha256":"ba948a4201e8155c5e09980f5c35fad9fb8b503790f17dc6ca1d3b424c7722a3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:05:25.016193Z","signature_b64":"b/M9KRlMlGKdMvk9AfRcBwM9OmHTmzgl/F5T/NlQdgU1sbxWwDCPeD3wviXyQo1TWos6ToW3pTF173wNmGJ0Cg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ba948a4201e8155c5e09980f5c35fad9fb8b503790f17dc6ca1d3b424c7722a3","last_reissued_at":"2026-07-05T10:05:25.015774Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:05:25.015774Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2501.15142","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":"2026-07-05T10:05:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5MZpMfc9VOFaXoqMvhvmMc72Bk+o5yBpRBefUAWyEcD0tWtrpa5IlS4aNKN3yRY649lDeD/PpGSNydMRFlSiDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T16:25:27.181824Z"},"content_sha256":"5204d7ec7555bf74f4d05d3f07ea6e39dc531d8b29ec279afd0a42842ef15833","schema_version":"1.0","event_id":"sha256:5204d7ec7555bf74f4d05d3f07ea6e39dc531d8b29ec279afd0a42842ef15833"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:XKKIUQQB5AKVYXQJTAHVYNP23H","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"DAGPrompT: Pushing the Limits of Graph Prompting with a Distribution-aware Graph Prompt Tuning Approach","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Bo Zheng, Guojie Song, Liang Wang, Qin Chen","submitted_at":"2025-01-25T08:53:42Z","abstract_excerpt":"The pre-train then fine-tune approach has advanced GNNs by enabling general knowledge capture without task-specific labels. However, an objective gap between pre-training and downstream tasks limits its effectiveness. Recent graph prompting methods aim to close this gap through task reformulations and learnable prompts. Despite this, they struggle with complex graphs like heterophily graphs. Freezing the GNN encoder can reduce the impact of prompting, while simple prompts fail to handle diverse hop-level distributions. This paper identifies two key challenges in adapting graph prompting method"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.15142","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/2501.15142/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":"2026-07-05T10:05:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fbtdbsw0pzm1TKRzINsNxDR7zrDpE6hFfTrqC9+lhmrvDPvSjtlHH1tWfrslwIV5WHBOLiFCuLCyGEjc3IB2Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T16:25:27.182921Z"},"content_sha256":"60d5d261cf6d79695fdbd655c362a1b8c1b6858f6c015b021207fdc390690d46","schema_version":"1.0","event_id":"sha256:60d5d261cf6d79695fdbd655c362a1b8c1b6858f6c015b021207fdc390690d46"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XKKIUQQB5AKVYXQJTAHVYNP23H/bundle.json","state_url":"https://pith.science/pith/XKKIUQQB5AKVYXQJTAHVYNP23H/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XKKIUQQB5AKVYXQJTAHVYNP23H/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":"2026-08-22T16:25:27Z","links":{"resolver":"https://pith.science/pith/XKKIUQQB5AKVYXQJTAHVYNP23H","bundle":"https://pith.science/pith/XKKIUQQB5AKVYXQJTAHVYNP23H/bundle.json","state":"https://pith.science/pith/XKKIUQQB5AKVYXQJTAHVYNP23H/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XKKIUQQB5AKVYXQJTAHVYNP23H/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:XKKIUQQB5AKVYXQJTAHVYNP23H","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":"336cc8d56296ac602d90413c3c198164c2ba910acf4f1c0daaec9be575a0d7cf","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-25T08:53:42Z","title_canon_sha256":"259e4c6aa2f5ffe9a8c4e1833c895420dea5b91242baa8183268fa81fc84615b"},"schema_version":"1.0","source":{"id":"2501.15142","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.15142","created_at":"2026-07-05T10:05:25Z"},{"alias_kind":"arxiv_version","alias_value":"2501.15142v1","created_at":"2026-07-05T10:05:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.15142","created_at":"2026-07-05T10:05:25Z"},{"alias_kind":"pith_short_12","alias_value":"XKKIUQQB5AKV","created_at":"2026-07-05T10:05:25Z"},{"alias_kind":"pith_short_16","alias_value":"XKKIUQQB5AKVYXQJ","created_at":"2026-07-05T10:05:25Z"},{"alias_kind":"pith_short_8","alias_value":"XKKIUQQB","created_at":"2026-07-05T10:05:25Z"}],"graph_snapshots":[{"event_id":"sha256:60d5d261cf6d79695fdbd655c362a1b8c1b6858f6c015b021207fdc390690d46","target":"graph","created_at":"2026-07-05T10:05:25Z","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/2501.15142/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The pre-train then fine-tune approach has advanced GNNs by enabling general knowledge capture without task-specific labels. However, an objective gap between pre-training and downstream tasks limits its effectiveness. Recent graph prompting methods aim to close this gap through task reformulations and learnable prompts. Despite this, they struggle with complex graphs like heterophily graphs. Freezing the GNN encoder can reduce the impact of prompting, while simple prompts fail to handle diverse hop-level distributions. This paper identifies two key challenges in adapting graph prompting method","authors_text":"Bo Zheng, Guojie Song, Liang Wang, Qin Chen","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-25T08:53:42Z","title":"DAGPrompT: Pushing the Limits of Graph Prompting with a Distribution-aware Graph Prompt Tuning Approach"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.15142","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":"sha256:5204d7ec7555bf74f4d05d3f07ea6e39dc531d8b29ec279afd0a42842ef15833","target":"record","created_at":"2026-07-05T10:05:25Z","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":"336cc8d56296ac602d90413c3c198164c2ba910acf4f1c0daaec9be575a0d7cf","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-25T08:53:42Z","title_canon_sha256":"259e4c6aa2f5ffe9a8c4e1833c895420dea5b91242baa8183268fa81fc84615b"},"schema_version":"1.0","source":{"id":"2501.15142","kind":"arxiv","version":1}},"canonical_sha256":"ba948a4201e8155c5e09980f5c35fad9fb8b503790f17dc6ca1d3b424c7722a3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ba948a4201e8155c5e09980f5c35fad9fb8b503790f17dc6ca1d3b424c7722a3","first_computed_at":"2026-07-05T10:05:25.015774Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:05:25.015774Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"b/M9KRlMlGKdMvk9AfRcBwM9OmHTmzgl/F5T/NlQdgU1sbxWwDCPeD3wviXyQo1TWos6ToW3pTF173wNmGJ0Cg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:05:25.016193Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.15142","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5204d7ec7555bf74f4d05d3f07ea6e39dc531d8b29ec279afd0a42842ef15833","sha256:60d5d261cf6d79695fdbd655c362a1b8c1b6858f6c015b021207fdc390690d46"],"state_sha256":"ab8a605481aeb7a3442eba97b7e405d225c9d10353389b0f0260b25dde77caa7"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0ew1OjpTSEi7dmgXYNhimnvvZDl+lVuCpYGl3JdMoxyiIkILme6fg79hoGx8zyHCWf7MxeKGjpf5XzA+wj0FDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-22T16:25:27.198610Z","bundle_sha256":"397d72fa58dc4efa5b8b42edcb0c39ff17a7b6dc440d36eba104279b339957d3"}}