{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:QX5SFY6LGXT5HULKGQESEMPIL5","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":"3f5fb178f870d4a36005eca87b21536b0d97f0170b011cf4b2857034ed37be30","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2020-11-17T19:58:56Z","title_canon_sha256":"6c36f73f063ccae7282725492d04d31a3488d4fddb2fb2e9e4a5bf0f98919f96"},"schema_version":"1.0","source":{"id":"2011.08909","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2011.08909","created_at":"2026-07-05T02:33:22Z"},{"alias_kind":"arxiv_version","alias_value":"2011.08909v2","created_at":"2026-07-05T02:33:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2011.08909","created_at":"2026-07-05T02:33:22Z"},{"alias_kind":"pith_short_12","alias_value":"QX5SFY6LGXT5","created_at":"2026-07-05T02:33:22Z"},{"alias_kind":"pith_short_16","alias_value":"QX5SFY6LGXT5HULK","created_at":"2026-07-05T02:33:22Z"},{"alias_kind":"pith_short_8","alias_value":"QX5SFY6L","created_at":"2026-07-05T02:33:22Z"}],"graph_snapshots":[{"event_id":"sha256:c2a109ce93147378562bda5b96e987e195cd6d488fa65ba6b385603fd39723af","target":"graph","created_at":"2026-07-05T02:33:22Z","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/2011.08909/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We study the problem of predicting and controlling the future state distribution of an autonomous agent. This problem, which can be viewed as a reframing of goal-conditioned reinforcement learning (RL), is centered around learning a conditional probability density function over future states. Instead of directly estimating this density function, we indirectly estimate this density function by training a classifier to predict whether an observation comes from the future. Via Bayes' rule, predictions from our classifier can be transformed into predictions over future states. Importantly, an off-","authors_text":"Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2020-11-17T19:58:56Z","title":"C-Learning: Learning to Achieve Goals via Recursive Classification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2011.08909","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":"sha256:39c04f0e77d17861b468d4d43b1823cc2bbb163c5f4c1bfa5debe7d1f036baed","target":"record","created_at":"2026-07-05T02:33:22Z","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":"3f5fb178f870d4a36005eca87b21536b0d97f0170b011cf4b2857034ed37be30","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2020-11-17T19:58:56Z","title_canon_sha256":"6c36f73f063ccae7282725492d04d31a3488d4fddb2fb2e9e4a5bf0f98919f96"},"schema_version":"1.0","source":{"id":"2011.08909","kind":"arxiv","version":2}},"canonical_sha256":"85fb22e3cb35e7d3d16a34092231e85f6ec4595259a3b418f9112f522af4dc68","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"85fb22e3cb35e7d3d16a34092231e85f6ec4595259a3b418f9112f522af4dc68","first_computed_at":"2026-07-05T02:33:22.590359Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:33:22.590359Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"WkPJ/iddthQoPKzzOxWBoekrNJNhiC8uIfc5VLdlyAdTudRQqA3PNt9zqEskF6M3X40d/FvAKnFLLLNzBNihDg==","signature_status":"signed_v1","signed_at":"2026-07-05T02:33:22.590829Z","signed_message":"canonical_sha256_bytes"},"source_id":"2011.08909","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:39c04f0e77d17861b468d4d43b1823cc2bbb163c5f4c1bfa5debe7d1f036baed","sha256:c2a109ce93147378562bda5b96e987e195cd6d488fa65ba6b385603fd39723af"],"state_sha256":"31ae85616fcc5d2ee0886c708550d351117499cee4c62f90a2bbfda890f660ff"}