{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2020:LEOEEUIYIZUVOIR7LVPBVZ2GNG","short_pith_number":"pith:LEOEEUIY","schema_version":"1.0","canonical_sha256":"591c425118466957223f5d5e1ae7466995b07d9fa84db8d351f9ee531d86cc2d","source":{"kind":"arxiv","id":"2008.13723","version":1},"attestation_state":"computed","paper":{"title":"Langevin Cooling for Domain Translation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Klaus-Robert M\\\"uller, Shinichi Nakajima, Vignesh Srinivasan, Wojciech Samek","submitted_at":"2020-08-31T16:43:17Z","abstract_excerpt":"Domain translation is the task of finding correspondence between two domains. Several Deep Neural Network (DNN) models, e.g., CycleGAN and cross-lingual language models, have shown remarkable successes on this task under the unsupervised setting---the mappings between the domains are learned from two independent sets of training data in both domains (without paired samples). However, those methods typically do not perform well on a significant proportion of test samples. In this paper, we hypothesize that many of such unsuccessful samples lie at the fringe---relatively low-density areas---of d"},"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":"2008.13723","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-08-31T16:43:17Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"943c1cdfc494a916b35eddbd9e4ec7d543f310b4c49761491da8a6278e86a88d","abstract_canon_sha256":"79147d54fffb8e83b40b1465c113cfc4cf02114f9f8953437e7f2cc3cde0f260"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:31:46.160652Z","signature_b64":"GM+Gk2EwuGG21N3A2dSbb0oZb2ki9HRAoCO8s1A/NAZpsxL0r9cGnpkLUU5ddRVlvCjazql076RTT4itb//pCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"591c425118466957223f5d5e1ae7466995b07d9fa84db8d351f9ee531d86cc2d","last_reissued_at":"2026-07-05T01:31:46.160137Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:31:46.160137Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Langevin Cooling for Domain Translation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Klaus-Robert M\\\"uller, Shinichi Nakajima, Vignesh Srinivasan, Wojciech Samek","submitted_at":"2020-08-31T16:43:17Z","abstract_excerpt":"Domain translation is the task of finding correspondence between two domains. Several Deep Neural Network (DNN) models, e.g., CycleGAN and cross-lingual language models, have shown remarkable successes on this task under the unsupervised setting---the mappings between the domains are learned from two independent sets of training data in both domains (without paired samples). However, those methods typically do not perform well on a significant proportion of test samples. In this paper, we hypothesize that many of such unsuccessful samples lie at the fringe---relatively low-density areas---of d"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2008.13723","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/2008.13723/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":"2008.13723","created_at":"2026-07-05T01:31:46.160194+00:00"},{"alias_kind":"arxiv_version","alias_value":"2008.13723v1","created_at":"2026-07-05T01:31:46.160194+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2008.13723","created_at":"2026-07-05T01:31:46.160194+00:00"},{"alias_kind":"pith_short_12","alias_value":"LEOEEUIYIZUV","created_at":"2026-07-05T01:31:46.160194+00:00"},{"alias_kind":"pith_short_16","alias_value":"LEOEEUIYIZUVOIR7","created_at":"2026-07-05T01:31:46.160194+00:00"},{"alias_kind":"pith_short_8","alias_value":"LEOEEUIY","created_at":"2026-07-05T01:31:46.160194+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/LEOEEUIYIZUVOIR7LVPBVZ2GNG","json":"https://pith.science/pith/LEOEEUIYIZUVOIR7LVPBVZ2GNG.json","graph_json":"https://pith.science/api/pith-number/LEOEEUIYIZUVOIR7LVPBVZ2GNG/graph.json","events_json":"https://pith.science/api/pith-number/LEOEEUIYIZUVOIR7LVPBVZ2GNG/events.json","paper":"https://pith.science/paper/LEOEEUIY"},"agent_actions":{"view_html":"https://pith.science/pith/LEOEEUIYIZUVOIR7LVPBVZ2GNG","download_json":"https://pith.science/pith/LEOEEUIYIZUVOIR7LVPBVZ2GNG.json","view_paper":"https://pith.science/paper/LEOEEUIY","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2008.13723&json=true","fetch_graph":"https://pith.science/api/pith-number/LEOEEUIYIZUVOIR7LVPBVZ2GNG/graph.json","fetch_events":"https://pith.science/api/pith-number/LEOEEUIYIZUVOIR7LVPBVZ2GNG/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/LEOEEUIYIZUVOIR7LVPBVZ2GNG/action/timestamp_anchor","attest_storage":"https://pith.science/pith/LEOEEUIYIZUVOIR7LVPBVZ2GNG/action/storage_attestation","attest_author":"https://pith.science/pith/LEOEEUIYIZUVOIR7LVPBVZ2GNG/action/author_attestation","sign_citation":"https://pith.science/pith/LEOEEUIYIZUVOIR7LVPBVZ2GNG/action/citation_signature","submit_replication":"https://pith.science/pith/LEOEEUIYIZUVOIR7LVPBVZ2GNG/action/replication_record"}},"created_at":"2026-07-05T01:31:46.160194+00:00","updated_at":"2026-07-05T01:31:46.160194+00:00"}