{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:AO4RQVZIOPJTZSVTSLQM26L5DE","short_pith_number":"pith:AO4RQVZI","canonical_record":{"source":{"id":"2605.17693","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-05-17T23:21:24Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"25a69264feaa7a828ea1c9364ee2d0ffdf205fee98f2532e2f15eaaf993d0c37","abstract_canon_sha256":"74675e7cbe4178c8f8768cd83a8afb6222c02207f93883d23437b85d2f206a73"},"schema_version":"1.0"},"canonical_sha256":"03b918572873d33ccab392e0cd797d1917270190c3d4baa2fadb58356dc21d4a","source":{"kind":"arxiv","id":"2605.17693","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.17693","created_at":"2026-05-20T00:04:53Z"},{"alias_kind":"arxiv_version","alias_value":"2605.17693v1","created_at":"2026-05-20T00:04:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.17693","created_at":"2026-05-20T00:04:53Z"},{"alias_kind":"pith_short_12","alias_value":"AO4RQVZIOPJT","created_at":"2026-05-20T00:04:53Z"},{"alias_kind":"pith_short_16","alias_value":"AO4RQVZIOPJTZSVT","created_at":"2026-05-20T00:04:53Z"},{"alias_kind":"pith_short_8","alias_value":"AO4RQVZI","created_at":"2026-05-20T00:04:53Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:AO4RQVZIOPJTZSVTSLQM26L5DE","target":"record","payload":{"canonical_record":{"source":{"id":"2605.17693","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-05-17T23:21:24Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"25a69264feaa7a828ea1c9364ee2d0ffdf205fee98f2532e2f15eaaf993d0c37","abstract_canon_sha256":"74675e7cbe4178c8f8768cd83a8afb6222c02207f93883d23437b85d2f206a73"},"schema_version":"1.0"},"canonical_sha256":"03b918572873d33ccab392e0cd797d1917270190c3d4baa2fadb58356dc21d4a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T00:04:53.112192Z","signature_b64":"ogUffNUjNV4Tp22xS4gpDsZ/jOVhbqq/5O8Hg/xBL8cQNO6jquFEtlfVLGyNYlu0EDiKw7imn608ium0dgvPBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"03b918572873d33ccab392e0cd797d1917270190c3d4baa2fadb58356dc21d4a","last_reissued_at":"2026-05-20T00:04:53.111432Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T00:04:53.111432Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.17693","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":"2026-05-20T00:04:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NWoWd93oo7FjuyslB1cP6lM4ZgMOPT0JgUX7tsQSdSiOY6Jk4/KWbexShmv5E/JXxfN56Mp27ySnpkN48RgcAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T08:52:13.111993Z"},"content_sha256":"4633a6acb57142b8ff75f3a66116b661c55466ca0451c6ec78d21c54b276399c","schema_version":"1.0","event_id":"sha256:4633a6acb57142b8ff75f3a66116b661c55466ca0451c6ec78d21c54b276399c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:AO4RQVZIOPJTZSVTSLQM26L5DE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Fine-tuning Pocket-Aware Diffusion Models via Denoising Policy Optimization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Daniel Kudenko, Megha Khosla, Yuan Xue","submitted_at":"2026-05-17T23:21:24Z","abstract_excerpt":"Structure-based drug design has been accelerated by pocket-aware 3D generative models, yet most methods primarily fit the training distribution and may fall short of satisfying multiple properties required in real-world therapeutic drug discovery. Recently, increasing attention has focused on structure-based molecule optimization (SBMO), which targets fine-grained control over multiple specified molecular properties. In this paper, we present DEPPA, a novel SBMO approach building upon Denoising Diffusion Policy Optimization for fine-tuning a pre-trained pocket-aware diffusion model via reinfor"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.17693","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/2605.17693/integrity.json","findings":[],"available":true,"detectors_run":[{"name":"cited_work_retraction","ran_at":"2026-05-19T21:51:57.424144Z","status":"completed","version":"1.0.0","findings_count":0},{"name":"shingle_duplication","ran_at":"2026-05-19T21:49:43.948160Z","status":"skipped","version":"0.1.0","findings_count":0},{"name":"citation_quote_validity","ran_at":"2026-05-19T21:49:43.747077Z","status":"skipped","version":"0.1.0","findings_count":0},{"name":"ai_meta_artifact","ran_at":"2026-05-19T21:33:23.520337Z","status":"skipped","version":"1.0.0","findings_count":0},{"name":"claim_evidence","ran_at":"2026-05-19T21:21:57.430077Z","status":"completed","version":"1.0.0","findings_count":0}],"snapshot_sha256":"83a834c7802ffd5307c962a675bcef0586fa8e99fc5a24901ac36e5cd6e571f1"},"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":"2026-05-20T00:04:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"20V47Mgdaa07exoF99whzk+/EAwWj5vlHYVuvY4QmvVjHR1J3gvIYU23TXGHu7Ywd4VvZUgyU7RZ2dVwepO/Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T08:52:13.112449Z"},"content_sha256":"a877423f3e6221cd4219ecb7598ec6d2f284e19218b95c28811d90c4687b3e7d","schema_version":"1.0","event_id":"sha256:a877423f3e6221cd4219ecb7598ec6d2f284e19218b95c28811d90c4687b3e7d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/AO4RQVZIOPJTZSVTSLQM26L5DE/bundle.json","state_url":"https://pith.science/pith/AO4RQVZIOPJTZSVTSLQM26L5DE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/AO4RQVZIOPJTZSVTSLQM26L5DE/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":"2026-05-28T08:52:13Z","links":{"resolver":"https://pith.science/pith/AO4RQVZIOPJTZSVTSLQM26L5DE","bundle":"https://pith.science/pith/AO4RQVZIOPJTZSVTSLQM26L5DE/bundle.json","state":"https://pith.science/pith/AO4RQVZIOPJTZSVTSLQM26L5DE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/AO4RQVZIOPJTZSVTSLQM26L5DE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:AO4RQVZIOPJTZSVTSLQM26L5DE","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":"74675e7cbe4178c8f8768cd83a8afb6222c02207f93883d23437b85d2f206a73","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-05-17T23:21:24Z","title_canon_sha256":"25a69264feaa7a828ea1c9364ee2d0ffdf205fee98f2532e2f15eaaf993d0c37"},"schema_version":"1.0","source":{"id":"2605.17693","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.17693","created_at":"2026-05-20T00:04:53Z"},{"alias_kind":"arxiv_version","alias_value":"2605.17693v1","created_at":"2026-05-20T00:04:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.17693","created_at":"2026-05-20T00:04:53Z"},{"alias_kind":"pith_short_12","alias_value":"AO4RQVZIOPJT","created_at":"2026-05-20T00:04:53Z"},{"alias_kind":"pith_short_16","alias_value":"AO4RQVZIOPJTZSVT","created_at":"2026-05-20T00:04:53Z"},{"alias_kind":"pith_short_8","alias_value":"AO4RQVZI","created_at":"2026-05-20T00:04:53Z"}],"graph_snapshots":[{"event_id":"sha256:a877423f3e6221cd4219ecb7598ec6d2f284e19218b95c28811d90c4687b3e7d","target":"graph","created_at":"2026-05-20T00:04:53Z","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":[{"findings_count":0,"name":"cited_work_retraction","ran_at":"2026-05-19T21:51:57.424144Z","status":"completed","version":"1.0.0"},{"findings_count":0,"name":"shingle_duplication","ran_at":"2026-05-19T21:49:43.948160Z","status":"skipped","version":"0.1.0"},{"findings_count":0,"name":"citation_quote_validity","ran_at":"2026-05-19T21:49:43.747077Z","status":"skipped","version":"0.1.0"},{"findings_count":0,"name":"ai_meta_artifact","ran_at":"2026-05-19T21:33:23.520337Z","status":"skipped","version":"1.0.0"},{"findings_count":0,"name":"claim_evidence","ran_at":"2026-05-19T21:21:57.430077Z","status":"completed","version":"1.0.0"}],"endpoint":"/pith/2605.17693/integrity.json","findings":[],"snapshot_sha256":"83a834c7802ffd5307c962a675bcef0586fa8e99fc5a24901ac36e5cd6e571f1","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Structure-based drug design has been accelerated by pocket-aware 3D generative models, yet most methods primarily fit the training distribution and may fall short of satisfying multiple properties required in real-world therapeutic drug discovery. Recently, increasing attention has focused on structure-based molecule optimization (SBMO), which targets fine-grained control over multiple specified molecular properties. In this paper, we present DEPPA, a novel SBMO approach building upon Denoising Diffusion Policy Optimization for fine-tuning a pre-trained pocket-aware diffusion model via reinfor","authors_text":"Daniel Kudenko, Megha Khosla, Yuan Xue","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-05-17T23:21:24Z","title":"Fine-tuning Pocket-Aware Diffusion Models via Denoising Policy Optimization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.17693","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":"sha256:4633a6acb57142b8ff75f3a66116b661c55466ca0451c6ec78d21c54b276399c","target":"record","created_at":"2026-05-20T00:04:53Z","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":"74675e7cbe4178c8f8768cd83a8afb6222c02207f93883d23437b85d2f206a73","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-05-17T23:21:24Z","title_canon_sha256":"25a69264feaa7a828ea1c9364ee2d0ffdf205fee98f2532e2f15eaaf993d0c37"},"schema_version":"1.0","source":{"id":"2605.17693","kind":"arxiv","version":1}},"canonical_sha256":"03b918572873d33ccab392e0cd797d1917270190c3d4baa2fadb58356dc21d4a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"03b918572873d33ccab392e0cd797d1917270190c3d4baa2fadb58356dc21d4a","first_computed_at":"2026-05-20T00:04:53.111432Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-20T00:04:53.111432Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ogUffNUjNV4Tp22xS4gpDsZ/jOVhbqq/5O8Hg/xBL8cQNO6jquFEtlfVLGyNYlu0EDiKw7imn608ium0dgvPBw==","signature_status":"signed_v1","signed_at":"2026-05-20T00:04:53.112192Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.17693","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4633a6acb57142b8ff75f3a66116b661c55466ca0451c6ec78d21c54b276399c","sha256:a877423f3e6221cd4219ecb7598ec6d2f284e19218b95c28811d90c4687b3e7d"],"state_sha256":"a2907a0635aa88ead85fa51bfce3a9d8432da916015edb50ac837f4cb21d9ddd"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fBRutWSqlNxNIkhhHnfsyyzpGUJBFvPC9SwYkz27ziptsOsI04Wzvqck7Efna8xgg0409YN4Z4PdHXKfrH1pCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-28T08:52:13.114716Z","bundle_sha256":"33568b575d4f606e0cd209d77971347270eb0278334bad4362d411857b598338"}}