{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:5JMW5VYGCRQPBNFYQHUAODKA4K","short_pith_number":"pith:5JMW5VYG","canonical_record":{"source":{"id":"2503.06337","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-03-08T20:41:07Z","cross_cats_sorted":[],"title_canon_sha256":"9afda9cb0cd73e82574d011e665c55eacf37e25f2bbd3983c01db2012cefd341","abstract_canon_sha256":"2d21a2e579bebeb875a2eb00ed922656a585f04d7851cefa9a542a19f68e692a"},"schema_version":"1.0"},"canonical_sha256":"ea596ed7061460f0b4b881e8070d40e2a09770db28105688d66f8136e6bd79cd","source":{"kind":"arxiv","id":"2503.06337","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.06337","created_at":"2026-07-05T11:20:10Z"},{"alias_kind":"arxiv_version","alias_value":"2503.06337v4","created_at":"2026-07-05T11:20:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.06337","created_at":"2026-07-05T11:20:10Z"},{"alias_kind":"pith_short_12","alias_value":"5JMW5VYGCRQP","created_at":"2026-07-05T11:20:10Z"},{"alias_kind":"pith_short_16","alias_value":"5JMW5VYGCRQPBNFY","created_at":"2026-07-05T11:20:10Z"},{"alias_kind":"pith_short_8","alias_value":"5JMW5VYG","created_at":"2026-07-05T11:20:10Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:5JMW5VYGCRQPBNFYQHUAODKA4K","target":"record","payload":{"canonical_record":{"source":{"id":"2503.06337","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-03-08T20:41:07Z","cross_cats_sorted":[],"title_canon_sha256":"9afda9cb0cd73e82574d011e665c55eacf37e25f2bbd3983c01db2012cefd341","abstract_canon_sha256":"2d21a2e579bebeb875a2eb00ed922656a585f04d7851cefa9a542a19f68e692a"},"schema_version":"1.0"},"canonical_sha256":"ea596ed7061460f0b4b881e8070d40e2a09770db28105688d66f8136e6bd79cd","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:20:10.481730Z","signature_b64":"Rp8McL7VmZ+9zMxaWHndBgQ+/TwBP373tQqlriGXbAzdSTHvvnBOY7o+jRNgt3W05hMZWZp+DlOCE7+WZXcXAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ea596ed7061460f0b4b881e8070d40e2a09770db28105688d66f8136e6bd79cd","last_reissued_at":"2026-07-05T11:20:10.481225Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:20:10.481225Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2503.06337","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:20:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"d7TV2sD08bNvpm1mm8PlU5gPH9FxVFnTeTm50MkNwETO8pPRMiHALS7cBFqN763sX1B6wMU0gusDGOGdDxTTCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-24T02:40:24.083757Z"},"content_sha256":"3440a189e089cf438e42c3be8e5cdd1bcc1571c52b90a8eb3ae5afc792cfd8b9","schema_version":"1.0","event_id":"sha256:3440a189e089cf438e42c3be8e5cdd1bcc1571c52b90a8eb3ae5afc792cfd8b9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:5JMW5VYGCRQPBNFYQHUAODKA4K","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Pretraining Generative Flow Networks with Inexpensive Rewards for Molecular Graph Generation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Artem Cherkasov, Emmanuel Bengio, Gopeshh Subbaraj, Martin Ester, Mohit Pandey","submitted_at":"2025-03-08T20:41:07Z","abstract_excerpt":"Generative Flow Networks (GFlowNets) have recently emerged as a suitable framework for generating diverse and high-quality molecular structures by learning from rewards treated as unnormalized distributions. Previous works in this framework often restrict exploration by using predefined molecular fragments as building blocks, limiting the chemical space that can be accessed. In this work, we introduce Atomic GFlowNets (A-GFNs), a foundational generative model leveraging individual atoms as building blocks to explore drug-like chemical space more comprehensively. We propose an unsupervised pre-"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.06337","kind":"arxiv","version":4},"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/2503.06337/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":"2026-07-05T11:20:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PHQHPdinYeVBGu4MvKlzzl6FqhKJSaDh9MhM7lL92sC8UTW3KR+c7BTrjpG+tSvjn2DBfNRUB9s3ySMjkHbKDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-24T02:40:24.084553Z"},"content_sha256":"aeb96e1673ca7b5b831699d59a5fdc4b692a3349dba0254734de38f3238851b6","schema_version":"1.0","event_id":"sha256:aeb96e1673ca7b5b831699d59a5fdc4b692a3349dba0254734de38f3238851b6"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5JMW5VYGCRQPBNFYQHUAODKA4K/bundle.json","state_url":"https://pith.science/pith/5JMW5VYGCRQPBNFYQHUAODKA4K/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5JMW5VYGCRQPBNFYQHUAODKA4K/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":"2026-08-24T02:40:24Z","links":{"resolver":"https://pith.science/pith/5JMW5VYGCRQPBNFYQHUAODKA4K","bundle":"https://pith.science/pith/5JMW5VYGCRQPBNFYQHUAODKA4K/bundle.json","state":"https://pith.science/pith/5JMW5VYGCRQPBNFYQHUAODKA4K/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5JMW5VYGCRQPBNFYQHUAODKA4K/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:5JMW5VYGCRQPBNFYQHUAODKA4K","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":"2d21a2e579bebeb875a2eb00ed922656a585f04d7851cefa9a542a19f68e692a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-03-08T20:41:07Z","title_canon_sha256":"9afda9cb0cd73e82574d011e665c55eacf37e25f2bbd3983c01db2012cefd341"},"schema_version":"1.0","source":{"id":"2503.06337","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.06337","created_at":"2026-07-05T11:20:10Z"},{"alias_kind":"arxiv_version","alias_value":"2503.06337v4","created_at":"2026-07-05T11:20:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.06337","created_at":"2026-07-05T11:20:10Z"},{"alias_kind":"pith_short_12","alias_value":"5JMW5VYGCRQP","created_at":"2026-07-05T11:20:10Z"},{"alias_kind":"pith_short_16","alias_value":"5JMW5VYGCRQPBNFY","created_at":"2026-07-05T11:20:10Z"},{"alias_kind":"pith_short_8","alias_value":"5JMW5VYG","created_at":"2026-07-05T11:20:10Z"}],"graph_snapshots":[{"event_id":"sha256:aeb96e1673ca7b5b831699d59a5fdc4b692a3349dba0254734de38f3238851b6","target":"graph","created_at":"2026-07-05T11:20:10Z","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/2503.06337/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Generative Flow Networks (GFlowNets) have recently emerged as a suitable framework for generating diverse and high-quality molecular structures by learning from rewards treated as unnormalized distributions. Previous works in this framework often restrict exploration by using predefined molecular fragments as building blocks, limiting the chemical space that can be accessed. In this work, we introduce Atomic GFlowNets (A-GFNs), a foundational generative model leveraging individual atoms as building blocks to explore drug-like chemical space more comprehensively. We propose an unsupervised pre-","authors_text":"Artem Cherkasov, Emmanuel Bengio, Gopeshh Subbaraj, Martin Ester, Mohit Pandey","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-03-08T20:41:07Z","title":"Pretraining Generative Flow Networks with Inexpensive Rewards for Molecular Graph Generation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.06337","kind":"arxiv","version":4},"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":"sha256:3440a189e089cf438e42c3be8e5cdd1bcc1571c52b90a8eb3ae5afc792cfd8b9","target":"record","created_at":"2026-07-05T11:20:10Z","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":"2d21a2e579bebeb875a2eb00ed922656a585f04d7851cefa9a542a19f68e692a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-03-08T20:41:07Z","title_canon_sha256":"9afda9cb0cd73e82574d011e665c55eacf37e25f2bbd3983c01db2012cefd341"},"schema_version":"1.0","source":{"id":"2503.06337","kind":"arxiv","version":4}},"canonical_sha256":"ea596ed7061460f0b4b881e8070d40e2a09770db28105688d66f8136e6bd79cd","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ea596ed7061460f0b4b881e8070d40e2a09770db28105688d66f8136e6bd79cd","first_computed_at":"2026-07-05T11:20:10.481225Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:20:10.481225Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Rp8McL7VmZ+9zMxaWHndBgQ+/TwBP373tQqlriGXbAzdSTHvvnBOY7o+jRNgt3W05hMZWZp+DlOCE7+WZXcXAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:20:10.481730Z","signed_message":"canonical_sha256_bytes"},"source_id":"2503.06337","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3440a189e089cf438e42c3be8e5cdd1bcc1571c52b90a8eb3ae5afc792cfd8b9","sha256:aeb96e1673ca7b5b831699d59a5fdc4b692a3349dba0254734de38f3238851b6"],"state_sha256":"b0804cf51348caf9e0932a33dc99183cb9b9d34039769450445f0b630e50c7ac"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rJnlWaRajb6EN7FFtEHMAb/tmcv1tWWseCSK9c219m3IjRJh81/r238pDm6q9STM4VwqUuY16shpeX701pdhDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-24T02:40:24.090618Z","bundle_sha256":"0385c69a90976b93dcb1fac99e3602da875bbed4461a84aa6a9499cfcdc3d6d2"}}