{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:K5OEA4X6O2PIZSNJEEJRUVO3CA","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":"6c56fd756d532912bdfc329bb9e40082e12671efdf4969c9b3693e952cf6df99","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2022-05-13T23:12:38Z","title_canon_sha256":"361033722ca851c6730a99211ced05700e6b53204dc002bf5eb52a8858db0888"},"schema_version":"1.0","source":{"id":"2205.06924","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.06924","created_at":"2026-07-05T04:23:10Z"},{"alias_kind":"arxiv_version","alias_value":"2205.06924v1","created_at":"2026-07-05T04:23:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.06924","created_at":"2026-07-05T04:23:10Z"},{"alias_kind":"pith_short_12","alias_value":"K5OEA4X6O2PI","created_at":"2026-07-05T04:23:10Z"},{"alias_kind":"pith_short_16","alias_value":"K5OEA4X6O2PIZSNJ","created_at":"2026-07-05T04:23:10Z"},{"alias_kind":"pith_short_8","alias_value":"K5OEA4X6","created_at":"2026-07-05T04:23:10Z"}],"graph_snapshots":[{"event_id":"sha256:a773212cfaa484487e2e9b020c756197039de96e57ff50ba3972b9e87072c0ae","target":"graph","created_at":"2026-07-05T04:23:10Z","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/2205.06924/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper studies the cooperative learning of two generative flow models, in which the two models are iteratively updated based on the jointly synthesized examples. The first flow model is a normalizing flow that transforms an initial simple density to a target density by applying a sequence of invertible transformations. The second flow model is a Langevin flow that runs finite steps of gradient-based MCMC toward an energy-based model. We start from proposing a generative framework that trains an energy-based model with a normalizing flow as an amortized sampler to initialize the MCMC chains","authors_text":"Jianwen Xie, Jun Li, Ping Li, Yaxuan Zhu","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2022-05-13T23:12:38Z","title":"A Tale of Two Flows: Cooperative Learning of Langevin Flow and Normalizing Flow Toward Energy-Based Model"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.06924","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:aa89900ca85639e702a5a6434674ab6e152570e99b879bd99ad72c356a29d9ed","target":"record","created_at":"2026-07-05T04:23:10Z","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":"6c56fd756d532912bdfc329bb9e40082e12671efdf4969c9b3693e952cf6df99","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2022-05-13T23:12:38Z","title_canon_sha256":"361033722ca851c6730a99211ced05700e6b53204dc002bf5eb52a8858db0888"},"schema_version":"1.0","source":{"id":"2205.06924","kind":"arxiv","version":1}},"canonical_sha256":"575c4072fe769e8cc9a921131a55db10388ab19b25bf6650ae34f26cb6b77ccd","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"575c4072fe769e8cc9a921131a55db10388ab19b25bf6650ae34f26cb6b77ccd","first_computed_at":"2026-07-05T04:23:10.038376Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:23:10.038376Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"iYF+Iati4i20L0LJvIbhRC2FKpow5/xKmpMk9YXI0V0GcIRQp3egx6IXwjCTaAcycRDu+zuRADRXUgWnyyxjCw==","signature_status":"signed_v1","signed_at":"2026-07-05T04:23:10.038777Z","signed_message":"canonical_sha256_bytes"},"source_id":"2205.06924","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:aa89900ca85639e702a5a6434674ab6e152570e99b879bd99ad72c356a29d9ed","sha256:a773212cfaa484487e2e9b020c756197039de96e57ff50ba3972b9e87072c0ae"],"state_sha256":"ff5402247d91588a4774c3965c959712d4c90bbb5b3d75b68d26e0036d1342a1"}