{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:ORDPFH6UKNRDOZTBMCSCXGI5SP","short_pith_number":"pith:ORDPFH6U","canonical_record":{"source":{"id":"2509.22468","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-09-26T15:16:20Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"adba6091fc95207f26d38c39b14a688fed5662ff227d8ad8c997016e3a5101a3","abstract_canon_sha256":"a67dfb5191d2d8b2e306d03639b5ed8f84dd754bfbf61f285d963337999b1b7c"},"schema_version":"1.0"},"canonical_sha256":"7446f29fd4536237666160a42b991d93c07ae31bbcb6715b68c4bf8eb29e2362","source":{"kind":"arxiv","id":"2509.22468","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2509.22468","created_at":"2026-06-03T01:05:45Z"},{"alias_kind":"arxiv_version","alias_value":"2509.22468v2","created_at":"2026-06-03T01:05:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2509.22468","created_at":"2026-06-03T01:05:45Z"},{"alias_kind":"pith_short_12","alias_value":"ORDPFH6UKNRD","created_at":"2026-06-03T01:05:45Z"},{"alias_kind":"pith_short_16","alias_value":"ORDPFH6UKNRDOZTB","created_at":"2026-06-03T01:05:45Z"},{"alias_kind":"pith_short_8","alias_value":"ORDPFH6U","created_at":"2026-06-03T01:05:45Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:ORDPFH6UKNRDOZTBMCSCXGI5SP","target":"record","payload":{"canonical_record":{"source":{"id":"2509.22468","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-09-26T15:16:20Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"adba6091fc95207f26d38c39b14a688fed5662ff227d8ad8c997016e3a5101a3","abstract_canon_sha256":"a67dfb5191d2d8b2e306d03639b5ed8f84dd754bfbf61f285d963337999b1b7c"},"schema_version":"1.0"},"canonical_sha256":"7446f29fd4536237666160a42b991d93c07ae31bbcb6715b68c4bf8eb29e2362","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-03T01:05:45.319431Z","signature_b64":"YzGmAfj9uuO/blVwVibJt8vBu3185LaS1L3zNESZmtNWQ/LvD7c2uBMEGi8pC6n2LBrVPVqSl7uMKAIqPYOACA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7446f29fd4536237666160a42b991d93c07ae31bbcb6715b68c4bf8eb29e2362","last_reissued_at":"2026-06-03T01:05:45.319040Z","signature_status":"signed_v1","first_computed_at":"2026-06-03T01:05:45.319040Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2509.22468","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":"2026-06-03T01:05:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"K5+yI3YYf4vYPH7NmHVUNToAZggDBjbNI9X0cCXjVLf+AgQCnCyVxItcNxwGle6dDbVvnsXAE2p/gIzGZ0QACA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T19:15:09.906749Z"},"content_sha256":"7ffece148e0c651cf806131daaa3b4fe7fd4145925de31c65f14a9b540cba57c","schema_version":"1.0","event_id":"sha256:7ffece148e0c651cf806131daaa3b4fe7fd4145925de31c65f14a9b540cba57c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:ORDPFH6UKNRDOZTBMCSCXGI5SP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learning the Neighborhood: Contrast-Free Multimodal Self-Supervised Molecular Graph Pretraining","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Andrei Manolache, Boshra Ariguib, Mathias Niepert","submitted_at":"2025-09-26T15:16:20Z","abstract_excerpt":"High-quality molecular representations are essential for property prediction and molecular design, yet large labeled datasets remain scarce. While self-supervised pretraining on molecular graphs has shown promise, many existing approaches either depend on hand-crafted augmentations or complex generative objectives, and often rely solely on 2D topology, leaving valuable 3D structural information underutilized. To address this gap, we introduce C-FREE (Contrast-Free Representation learning on Ego-nets), a simple framework that integrates 2D graphs with ensembles of 3D conformers. C-FREE learns m"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2509.22468","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/2509.22468/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":"2026-06-03T01:05:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZAOnWu//NuLGcvTw9v9fA2l1HwD1umLpzmjNBAgI1+XT+REkhkM3y7veMFikwtyhhKg7NXmOKUR65GtThbbtAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T19:15:09.907586Z"},"content_sha256":"8601a278bab89f118e57b54e584cec525af75ee5c65f89ec8a6c8c8616b378dd","schema_version":"1.0","event_id":"sha256:8601a278bab89f118e57b54e584cec525af75ee5c65f89ec8a6c8c8616b378dd"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ORDPFH6UKNRDOZTBMCSCXGI5SP/bundle.json","state_url":"https://pith.science/pith/ORDPFH6UKNRDOZTBMCSCXGI5SP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ORDPFH6UKNRDOZTBMCSCXGI5SP/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":"2026-08-07T19:15:09Z","links":{"resolver":"https://pith.science/pith/ORDPFH6UKNRDOZTBMCSCXGI5SP","bundle":"https://pith.science/pith/ORDPFH6UKNRDOZTBMCSCXGI5SP/bundle.json","state":"https://pith.science/pith/ORDPFH6UKNRDOZTBMCSCXGI5SP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ORDPFH6UKNRDOZTBMCSCXGI5SP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:ORDPFH6UKNRDOZTBMCSCXGI5SP","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":"a67dfb5191d2d8b2e306d03639b5ed8f84dd754bfbf61f285d963337999b1b7c","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-09-26T15:16:20Z","title_canon_sha256":"adba6091fc95207f26d38c39b14a688fed5662ff227d8ad8c997016e3a5101a3"},"schema_version":"1.0","source":{"id":"2509.22468","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2509.22468","created_at":"2026-06-03T01:05:45Z"},{"alias_kind":"arxiv_version","alias_value":"2509.22468v2","created_at":"2026-06-03T01:05:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2509.22468","created_at":"2026-06-03T01:05:45Z"},{"alias_kind":"pith_short_12","alias_value":"ORDPFH6UKNRD","created_at":"2026-06-03T01:05:45Z"},{"alias_kind":"pith_short_16","alias_value":"ORDPFH6UKNRDOZTB","created_at":"2026-06-03T01:05:45Z"},{"alias_kind":"pith_short_8","alias_value":"ORDPFH6U","created_at":"2026-06-03T01:05:45Z"}],"graph_snapshots":[{"event_id":"sha256:8601a278bab89f118e57b54e584cec525af75ee5c65f89ec8a6c8c8616b378dd","target":"graph","created_at":"2026-06-03T01:05:45Z","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/2509.22468/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"High-quality molecular representations are essential for property prediction and molecular design, yet large labeled datasets remain scarce. While self-supervised pretraining on molecular graphs has shown promise, many existing approaches either depend on hand-crafted augmentations or complex generative objectives, and often rely solely on 2D topology, leaving valuable 3D structural information underutilized. To address this gap, we introduce C-FREE (Contrast-Free Representation learning on Ego-nets), a simple framework that integrates 2D graphs with ensembles of 3D conformers. C-FREE learns m","authors_text":"Andrei Manolache, Boshra Ariguib, Mathias Niepert","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-09-26T15:16:20Z","title":"Learning the Neighborhood: Contrast-Free Multimodal Self-Supervised Molecular Graph Pretraining"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2509.22468","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":"sha256:7ffece148e0c651cf806131daaa3b4fe7fd4145925de31c65f14a9b540cba57c","target":"record","created_at":"2026-06-03T01:05:45Z","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":"a67dfb5191d2d8b2e306d03639b5ed8f84dd754bfbf61f285d963337999b1b7c","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-09-26T15:16:20Z","title_canon_sha256":"adba6091fc95207f26d38c39b14a688fed5662ff227d8ad8c997016e3a5101a3"},"schema_version":"1.0","source":{"id":"2509.22468","kind":"arxiv","version":2}},"canonical_sha256":"7446f29fd4536237666160a42b991d93c07ae31bbcb6715b68c4bf8eb29e2362","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7446f29fd4536237666160a42b991d93c07ae31bbcb6715b68c4bf8eb29e2362","first_computed_at":"2026-06-03T01:05:45.319040Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-03T01:05:45.319040Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"YzGmAfj9uuO/blVwVibJt8vBu3185LaS1L3zNESZmtNWQ/LvD7c2uBMEGi8pC6n2LBrVPVqSl7uMKAIqPYOACA==","signature_status":"signed_v1","signed_at":"2026-06-03T01:05:45.319431Z","signed_message":"canonical_sha256_bytes"},"source_id":"2509.22468","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7ffece148e0c651cf806131daaa3b4fe7fd4145925de31c65f14a9b540cba57c","sha256:8601a278bab89f118e57b54e584cec525af75ee5c65f89ec8a6c8c8616b378dd"],"state_sha256":"82706cd86317b8482b91580f5ce29706c18f4a71b3fb7a93272c9f98e15f1e9a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sDki46cMYWA4lbIhxMGr6ES9tR6iUoXd3k/lmbfIQ/WtaGPwiM+Cnx8q4DOZWprNMBdCXsXYZiyPBsoedjlZBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T19:15:09.914846Z","bundle_sha256":"07153a3010bd9716b159880e1f0ff1b48d63921e0cd94c1bdc399db074d92593"}}