{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:NKLDJLTOWXPAT3MILRGDMQY6PM","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":"85a433c7d4b326bf2811e6a1607bbf688e6a2ee7b29092fea2e41e46f551e099","cross_cats_sorted":["cs.LG","cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2024-06-13T18:00:24Z","title_canon_sha256":"8615a595b51f1113d255f7631a824bba4470ff64d4d2f04ac3fd04c4eb4240fe"},"schema_version":"1.0","source":{"id":"2406.09509","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.09509","created_at":"2026-07-05T09:26:28Z"},{"alias_kind":"arxiv_version","alias_value":"2406.09509v2","created_at":"2026-07-05T09:26:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.09509","created_at":"2026-07-05T09:26:28Z"},{"alias_kind":"pith_short_12","alias_value":"NKLDJLTOWXPA","created_at":"2026-07-05T09:26:28Z"},{"alias_kind":"pith_short_16","alias_value":"NKLDJLTOWXPAT3MI","created_at":"2026-07-05T09:26:28Z"},{"alias_kind":"pith_short_8","alias_value":"NKLDJLTO","created_at":"2026-07-05T09:26:28Z"}],"graph_snapshots":[{"event_id":"sha256:79ebfae11f728dfd8f5d270b3477d8416cfb2a0d45fe31dc43830a01d07a7d23","target":"graph","created_at":"2026-07-05T09:26:28Z","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/2406.09509/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Leveraging the powerful generative capability of diffusion models (DMs) to build decision-making agents has achieved extensive success. However, there is still a demand for an easy-to-use and modularized open-source library that offers customized and efficient development for DM-based decision-making algorithms. In this work, we introduce CleanDiffuser, the first DM library specifically designed for decision-making algorithms. By revisiting the roles of DMs in the decision-making domain, we identify a set of essential sub-modules that constitute the core of CleanDiffuser, allowing for the impl","authors_text":"Fei Ni, Jianye Hao, Pengyi Li, Yan Zheng, Yifu Yuan, Yi Ma, Zibin Dong","cross_cats":["cs.LG","cs.RO"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2024-06-13T18:00:24Z","title":"CleanDiffuser: An Easy-to-use Modularized Library for Diffusion Models in Decision Making"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.09509","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:d4a47b87173382ad8d02998317fdf666952847552572a17b0fc1723c462819f5","target":"record","created_at":"2026-07-05T09:26:28Z","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":"85a433c7d4b326bf2811e6a1607bbf688e6a2ee7b29092fea2e41e46f551e099","cross_cats_sorted":["cs.LG","cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2024-06-13T18:00:24Z","title_canon_sha256":"8615a595b51f1113d255f7631a824bba4470ff64d4d2f04ac3fd04c4eb4240fe"},"schema_version":"1.0","source":{"id":"2406.09509","kind":"arxiv","version":2}},"canonical_sha256":"6a9634ae6eb5de09ed885c4c36431e7b25c4e6d9919caeae7916f641fd44e01b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6a9634ae6eb5de09ed885c4c36431e7b25c4e6d9919caeae7916f641fd44e01b","first_computed_at":"2026-07-05T09:26:28.304796Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:26:28.304796Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"SWv0Mn/PmlTSiwplP+7LOOovXZtKY8x9pYATNtDoZDdv9LY1d1emZ3Ab4O/CEnvdEJv1zW8nvhc5HauSjpM/Cg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:26:28.305295Z","signed_message":"canonical_sha256_bytes"},"source_id":"2406.09509","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d4a47b87173382ad8d02998317fdf666952847552572a17b0fc1723c462819f5","sha256:79ebfae11f728dfd8f5d270b3477d8416cfb2a0d45fe31dc43830a01d07a7d23"],"state_sha256":"7dc00da0e175a36cd2f3d35d76390a92d506891a1e4b16d9e503ea634d31e110"}