{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:2JYPPOESTIVUJEUVEH3SSCM35W","short_pith_number":"pith:2JYPPOES","canonical_record":{"source":{"id":"2310.00311","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-09-30T08:50:49Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"af8d81e1b2fd764d1549008f8e3d26d9e6ce9fbbce98033afe4a7372e518af7b","abstract_canon_sha256":"cc1d12d4032535f35577d820425e58591a3dff88a59cd28112e34d8e98b9c68a"},"schema_version":"1.0"},"canonical_sha256":"d270f7b8929a2b44929521f729099bed8ca678c4c2716be8adca998976727759","source":{"kind":"arxiv","id":"2310.00311","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.00311","created_at":"2026-07-05T06:56:04Z"},{"alias_kind":"arxiv_version","alias_value":"2310.00311v1","created_at":"2026-07-05T06:56:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.00311","created_at":"2026-07-05T06:56:04Z"},{"alias_kind":"pith_short_12","alias_value":"2JYPPOESTIVU","created_at":"2026-07-05T06:56:04Z"},{"alias_kind":"pith_short_16","alias_value":"2JYPPOESTIVUJEUV","created_at":"2026-07-05T06:56:04Z"},{"alias_kind":"pith_short_8","alias_value":"2JYPPOES","created_at":"2026-07-05T06:56:04Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:2JYPPOESTIVUJEUVEH3SSCM35W","target":"record","payload":{"canonical_record":{"source":{"id":"2310.00311","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-09-30T08:50:49Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"af8d81e1b2fd764d1549008f8e3d26d9e6ce9fbbce98033afe4a7372e518af7b","abstract_canon_sha256":"cc1d12d4032535f35577d820425e58591a3dff88a59cd28112e34d8e98b9c68a"},"schema_version":"1.0"},"canonical_sha256":"d270f7b8929a2b44929521f729099bed8ca678c4c2716be8adca998976727759","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:56:04.046541Z","signature_b64":"Tpf2AHPa6TfOp/E44AFWTyivje19xZ5iqOV9To+BAbx7tIuHRb8biHUme3E08uYKtxKcqg0qWksctP03Og3QDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d270f7b8929a2b44929521f729099bed8ca678c4c2716be8adca998976727759","last_reissued_at":"2026-07-05T06:56:04.046064Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:56:04.046064Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2310.00311","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":"2026-07-05T06:56:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"woMtxkMU06w25/M834guDzmCgdh9ZogXh/xVNe7X18pxiwBS3ZKUy+3E1CL4bt4fJtIuGLpJXXgTvaSrUeo9BQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T10:10:55.656875Z"},"content_sha256":"26d7ec4a19fb3ba336b0e170e5bc3fbf2238b8de4d220afa9e8552069479e334","schema_version":"1.0","event_id":"sha256:26d7ec4a19fb3ba336b0e170e5bc3fbf2238b8de4d220afa9e8552069479e334"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:2JYPPOESTIVUJEUVEH3SSCM35W","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Efficient Planning with Latent Diffusion","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Wenhao Li","submitted_at":"2023-09-30T08:50:49Z","abstract_excerpt":"Temporal abstraction and efficient planning pose significant challenges in offline reinforcement learning, mainly when dealing with domains that involve temporally extended tasks and delayed sparse rewards. Existing methods typically plan in the raw action space and can be inefficient and inflexible. Latent action spaces offer a more flexible paradigm, capturing only possible actions within the behavior policy support and decoupling the temporal structure between planning and modeling. However, current latent-action-based methods are limited to discrete spaces and require expensive planning. T"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.00311","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/2310.00311/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":"2026-07-05T06:56:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5AAX/SGiK6Emuy3hHytSo4dBB5y3FgP7w/f1+TO97kc50ogLpREW9Ey8o+zMI8FdbAp8U4sRx2tXyLDVxEz3Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T10:10:55.657387Z"},"content_sha256":"e390a435032244861bccba4cdad6cfead189ee5a204cbdd46c95bae7c53850c8","schema_version":"1.0","event_id":"sha256:e390a435032244861bccba4cdad6cfead189ee5a204cbdd46c95bae7c53850c8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2JYPPOESTIVUJEUVEH3SSCM35W/bundle.json","state_url":"https://pith.science/pith/2JYPPOESTIVUJEUVEH3SSCM35W/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2JYPPOESTIVUJEUVEH3SSCM35W/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":"2026-08-08T10:10:55Z","links":{"resolver":"https://pith.science/pith/2JYPPOESTIVUJEUVEH3SSCM35W","bundle":"https://pith.science/pith/2JYPPOESTIVUJEUVEH3SSCM35W/bundle.json","state":"https://pith.science/pith/2JYPPOESTIVUJEUVEH3SSCM35W/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2JYPPOESTIVUJEUVEH3SSCM35W/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:2JYPPOESTIVUJEUVEH3SSCM35W","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":"cc1d12d4032535f35577d820425e58591a3dff88a59cd28112e34d8e98b9c68a","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-09-30T08:50:49Z","title_canon_sha256":"af8d81e1b2fd764d1549008f8e3d26d9e6ce9fbbce98033afe4a7372e518af7b"},"schema_version":"1.0","source":{"id":"2310.00311","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.00311","created_at":"2026-07-05T06:56:04Z"},{"alias_kind":"arxiv_version","alias_value":"2310.00311v1","created_at":"2026-07-05T06:56:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.00311","created_at":"2026-07-05T06:56:04Z"},{"alias_kind":"pith_short_12","alias_value":"2JYPPOESTIVU","created_at":"2026-07-05T06:56:04Z"},{"alias_kind":"pith_short_16","alias_value":"2JYPPOESTIVUJEUV","created_at":"2026-07-05T06:56:04Z"},{"alias_kind":"pith_short_8","alias_value":"2JYPPOES","created_at":"2026-07-05T06:56:04Z"}],"graph_snapshots":[{"event_id":"sha256:e390a435032244861bccba4cdad6cfead189ee5a204cbdd46c95bae7c53850c8","target":"graph","created_at":"2026-07-05T06:56:04Z","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/2310.00311/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Temporal abstraction and efficient planning pose significant challenges in offline reinforcement learning, mainly when dealing with domains that involve temporally extended tasks and delayed sparse rewards. Existing methods typically plan in the raw action space and can be inefficient and inflexible. Latent action spaces offer a more flexible paradigm, capturing only possible actions within the behavior policy support and decoupling the temporal structure between planning and modeling. However, current latent-action-based methods are limited to discrete spaces and require expensive planning. T","authors_text":"Wenhao Li","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-09-30T08:50:49Z","title":"Efficient Planning with Latent Diffusion"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.00311","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":"sha256:26d7ec4a19fb3ba336b0e170e5bc3fbf2238b8de4d220afa9e8552069479e334","target":"record","created_at":"2026-07-05T06:56:04Z","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":"cc1d12d4032535f35577d820425e58591a3dff88a59cd28112e34d8e98b9c68a","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-09-30T08:50:49Z","title_canon_sha256":"af8d81e1b2fd764d1549008f8e3d26d9e6ce9fbbce98033afe4a7372e518af7b"},"schema_version":"1.0","source":{"id":"2310.00311","kind":"arxiv","version":1}},"canonical_sha256":"d270f7b8929a2b44929521f729099bed8ca678c4c2716be8adca998976727759","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d270f7b8929a2b44929521f729099bed8ca678c4c2716be8adca998976727759","first_computed_at":"2026-07-05T06:56:04.046064Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:56:04.046064Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Tpf2AHPa6TfOp/E44AFWTyivje19xZ5iqOV9To+BAbx7tIuHRb8biHUme3E08uYKtxKcqg0qWksctP03Og3QDg==","signature_status":"signed_v1","signed_at":"2026-07-05T06:56:04.046541Z","signed_message":"canonical_sha256_bytes"},"source_id":"2310.00311","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:26d7ec4a19fb3ba336b0e170e5bc3fbf2238b8de4d220afa9e8552069479e334","sha256:e390a435032244861bccba4cdad6cfead189ee5a204cbdd46c95bae7c53850c8"],"state_sha256":"f5203c444d7390a68a749c644c2f0229cdf33da71420294dabfb12cc815517af"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8BUIgWlt2wil3MDd68wsaHazgdr428GWdvHWtmUS4OTwl2t2ovhxhMbqPnKWDWdHZ5RimEhkd5EgXqRGL4MrBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T10:10:55.662393Z","bundle_sha256":"05f130ab77419a8738ba64d9def61dfcaa4dab32068b0dff5ecc9b1057a9b148"}}