{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:ZQTWU643ZRSPXU56FP4XDJLKAW","short_pith_number":"pith:ZQTWU643","schema_version":"1.0","canonical_sha256":"cc276a7b9bcc64fbd3be2bf971a56a058da7658f842f8e49fc9c0510490709d3","source":{"kind":"arxiv","id":"2602.10637","version":2},"attestation_state":"computed","paper":{"title":"Coarse-Grained Boltzmann Generators","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cond-mat.stat-mech","physics.chem-ph","stat.ML"],"primary_cat":"cs.LG","authors_text":"Bojun Zhao, Jan Eckwert, Julija Zavadlav, Weilong Chen","submitted_at":"2026-02-11T08:37:13Z","abstract_excerpt":"Sampling equilibrium molecular configurations from the Boltzmann distribution is a longstanding challenge. Boltzmann Generators (BGs) address this by combining exact-likelihood generative models with importance sampling, but practical scalability is limited. Meanwhile, coarse-grained surrogates enable the modeling of larger systems by reducing effective dimensionality, yet often lack a reweighting procedure required to ensure asymptotically correct statistics. In this work, we propose Coarse-Grained Boltzmann Generators (CG-BGs), a framework for reduced-order generative modeling with importanc"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2602.10637","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-02-11T08:37:13Z","cross_cats_sorted":["cond-mat.stat-mech","physics.chem-ph","stat.ML"],"title_canon_sha256":"f2049b9abd69f5288290b938ffb6fb6a3db239cadb76597b27a741e2ee824877","abstract_canon_sha256":"330c74744994d13f22620d23027473627950a6210ce46f58aca444d08f4e83a2"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-29T02:05:40.930353Z","signature_b64":"hP24+1VG2w/Y+L3Z83fsEf/5sMJ7HLZv/u6CpUAf7srP9Dy7HPCfRTWcp6lj4zLFFxdKSP/2taXlPx95XY6YAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"cc276a7b9bcc64fbd3be2bf971a56a058da7658f842f8e49fc9c0510490709d3","last_reissued_at":"2026-05-29T02:05:40.929487Z","signature_status":"signed_v1","first_computed_at":"2026-05-29T02:05:40.929487Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Coarse-Grained Boltzmann Generators","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cond-mat.stat-mech","physics.chem-ph","stat.ML"],"primary_cat":"cs.LG","authors_text":"Bojun Zhao, Jan Eckwert, Julija Zavadlav, Weilong Chen","submitted_at":"2026-02-11T08:37:13Z","abstract_excerpt":"Sampling equilibrium molecular configurations from the Boltzmann distribution is a longstanding challenge. Boltzmann Generators (BGs) address this by combining exact-likelihood generative models with importance sampling, but practical scalability is limited. Meanwhile, coarse-grained surrogates enable the modeling of larger systems by reducing effective dimensionality, yet often lack a reweighting procedure required to ensure asymptotically correct statistics. In this work, we propose Coarse-Grained Boltzmann Generators (CG-BGs), a framework for reduced-order generative modeling with importanc"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2602.10637","kind":"arxiv","version":2},"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/2602.10637/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2602.10637","created_at":"2026-05-29T02:05:40.929611+00:00"},{"alias_kind":"arxiv_version","alias_value":"2602.10637v2","created_at":"2026-05-29T02:05:40.929611+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2602.10637","created_at":"2026-05-29T02:05:40.929611+00:00"},{"alias_kind":"pith_short_12","alias_value":"ZQTWU643ZRSP","created_at":"2026-05-29T02:05:40.929611+00:00"},{"alias_kind":"pith_short_16","alias_value":"ZQTWU643ZRSPXU56","created_at":"2026-05-29T02:05:40.929611+00:00"},{"alias_kind":"pith_short_8","alias_value":"ZQTWU643","created_at":"2026-05-29T02:05:40.929611+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/ZQTWU643ZRSPXU56FP4XDJLKAW","json":"https://pith.science/pith/ZQTWU643ZRSPXU56FP4XDJLKAW.json","graph_json":"https://pith.science/api/pith-number/ZQTWU643ZRSPXU56FP4XDJLKAW/graph.json","events_json":"https://pith.science/api/pith-number/ZQTWU643ZRSPXU56FP4XDJLKAW/events.json","paper":"https://pith.science/paper/ZQTWU643"},"agent_actions":{"view_html":"https://pith.science/pith/ZQTWU643ZRSPXU56FP4XDJLKAW","download_json":"https://pith.science/pith/ZQTWU643ZRSPXU56FP4XDJLKAW.json","view_paper":"https://pith.science/paper/ZQTWU643","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2602.10637&json=true","fetch_graph":"https://pith.science/api/pith-number/ZQTWU643ZRSPXU56FP4XDJLKAW/graph.json","fetch_events":"https://pith.science/api/pith-number/ZQTWU643ZRSPXU56FP4XDJLKAW/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ZQTWU643ZRSPXU56FP4XDJLKAW/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ZQTWU643ZRSPXU56FP4XDJLKAW/action/storage_attestation","attest_author":"https://pith.science/pith/ZQTWU643ZRSPXU56FP4XDJLKAW/action/author_attestation","sign_citation":"https://pith.science/pith/ZQTWU643ZRSPXU56FP4XDJLKAW/action/citation_signature","submit_replication":"https://pith.science/pith/ZQTWU643ZRSPXU56FP4XDJLKAW/action/replication_record"}},"created_at":"2026-05-29T02:05:40.929611+00:00","updated_at":"2026-05-29T02:05:40.929611+00:00"}