{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:ST2HUQGSGNWZISMVQFXSPQCR2U","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":"8c0f66f36ff0c58c675b6a197e9091c448b1789ca5641e82e8502e1b67e987e2","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2024-02-11T15:23:13Z","title_canon_sha256":"993204e865d5fe1f8bdeacc7840cba1591d5476fe86697510dd6e20dcdfe571c"},"schema_version":"1.0","source":{"id":"2402.07226","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.07226","created_at":"2026-07-05T07:44:02Z"},{"alias_kind":"arxiv_version","alias_value":"2402.07226v1","created_at":"2026-07-05T07:44:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.07226","created_at":"2026-07-05T07:44:02Z"},{"alias_kind":"pith_short_12","alias_value":"ST2HUQGSGNWZ","created_at":"2026-07-05T07:44:02Z"},{"alias_kind":"pith_short_16","alias_value":"ST2HUQGSGNWZISMV","created_at":"2026-07-05T07:44:02Z"},{"alias_kind":"pith_short_8","alias_value":"ST2HUQGS","created_at":"2026-07-05T07:44:02Z"}],"graph_snapshots":[{"event_id":"sha256:cd90dc0e252363c572060663dcaf69ebf1519713a8b851f11eaffef96dc31a23","target":"graph","created_at":"2026-07-05T07:44:02Z","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/2402.07226/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Offline Goal-Conditioned Reinforcement Learning (Offline GCRL) is an important problem in RL that focuses on acquiring diverse goal-oriented skills solely from pre-collected behavior datasets. In this setting, the reward feedback is typically absent except when the goal is achieved, which makes it difficult to learn policies especially from a finite dataset of suboptimal behaviors. In addition, realistic scenarios involve long-horizon planning, which necessitates the extraction of useful skills within sub-trajectories. Recently, the conditional diffusion model has been shown to be a promising ","authors_text":"Daiki E. Matsunaga, Kee-Eung Kim, Sungyoon Kim, Yunseon Choi","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2024-02-11T15:23:13Z","title":"Stitching Sub-Trajectories with Conditional Diffusion Model for Goal-Conditioned Offline RL"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.07226","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":"sha256:18ea1e43f665dfc145c93f0743ec3ead2de81a3420456a384c1d209636cd3f1c","target":"record","created_at":"2026-07-05T07:44:02Z","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":"8c0f66f36ff0c58c675b6a197e9091c448b1789ca5641e82e8502e1b67e987e2","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2024-02-11T15:23:13Z","title_canon_sha256":"993204e865d5fe1f8bdeacc7840cba1591d5476fe86697510dd6e20dcdfe571c"},"schema_version":"1.0","source":{"id":"2402.07226","kind":"arxiv","version":1}},"canonical_sha256":"94f47a40d2336d944995816f27c051d52636247b24afc6913ad360f5dcececbe","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"94f47a40d2336d944995816f27c051d52636247b24afc6913ad360f5dcececbe","first_computed_at":"2026-07-05T07:44:02.917231Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:44:02.917231Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Mxx7jdEpIKzIgcelukq4KfsrQQD0J0WAlBsWcpaDYn3/ZCw1XUsT1uctErdFV+/PJJ7DpCmOA6xE5mJ1sMQwCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T07:44:02.917782Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.07226","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:18ea1e43f665dfc145c93f0743ec3ead2de81a3420456a384c1d209636cd3f1c","sha256:cd90dc0e252363c572060663dcaf69ebf1519713a8b851f11eaffef96dc31a23"],"state_sha256":"3c160605dce93270e1d59dc85638754d0259412207b41a6b856b82cb56dab55f"}