{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:PAC7EI54CLPBWOH7MQCEGQBAOC","short_pith_number":"pith:PAC7EI54","canonical_record":{"source":{"id":"1712.01026","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-12-04T11:57:28Z","cross_cats_sorted":[],"title_canon_sha256":"b251ddd940dfec12a18241d1b01099e16864f914e1afc17dd45a0775ce1f690c","abstract_canon_sha256":"fc28999f7c780c121143e10c94b740f7d01b7c3f1cf2f7ec17e931bf89fdc922"},"schema_version":"1.0"},"canonical_sha256":"7805f223bc12de1b38ff640443402070b83db7fe8d8b9122ee300c8edb66ac88","source":{"kind":"arxiv","id":"1712.01026","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1712.01026","created_at":"2026-05-18T00:06:30Z"},{"alias_kind":"arxiv_version","alias_value":"1712.01026v4","created_at":"2026-05-18T00:06:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1712.01026","created_at":"2026-05-18T00:06:30Z"},{"alias_kind":"pith_short_12","alias_value":"PAC7EI54CLPB","created_at":"2026-05-18T12:31:37Z"},{"alias_kind":"pith_short_16","alias_value":"PAC7EI54CLPBWOH7","created_at":"2026-05-18T12:31:37Z"},{"alias_kind":"pith_short_8","alias_value":"PAC7EI54","created_at":"2026-05-18T12:31:37Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:PAC7EI54CLPBWOH7MQCEGQBAOC","target":"record","payload":{"canonical_record":{"source":{"id":"1712.01026","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-12-04T11:57:28Z","cross_cats_sorted":[],"title_canon_sha256":"b251ddd940dfec12a18241d1b01099e16864f914e1afc17dd45a0775ce1f690c","abstract_canon_sha256":"fc28999f7c780c121143e10c94b740f7d01b7c3f1cf2f7ec17e931bf89fdc922"},"schema_version":"1.0"},"canonical_sha256":"7805f223bc12de1b38ff640443402070b83db7fe8d8b9122ee300c8edb66ac88","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:06:30.839750Z","signature_b64":"R8h5Z1ykslxmpbysjZF4vOZPK5wbXATqDJxr+Ckee2K8kJJjdfyeXB5S/NGSXDMGn1kZKYwmKRCPn1yr07xkBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7805f223bc12de1b38ff640443402070b83db7fe8d8b9122ee300c8edb66ac88","last_reissued_at":"2026-05-18T00:06:30.839336Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:06:30.839336Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1712.01026","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:06:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1tuyrndHnNiw8Q8cIse96Jp0+8MZ/LQMQJiKCOwEk2N45TokeCytyOq/wT8bgQ6hPmRgt6VA9n7icLKfIgcZBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T04:44:16.142288Z"},"content_sha256":"18c4dc5b4b589a18a1fd67c52c22bec252cded3285791409ceab086fb132aa25","schema_version":"1.0","event_id":"sha256:18c4dc5b4b589a18a1fd67c52c22bec252cded3285791409ceab086fb132aa25"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:PAC7EI54CLPBWOH7MQCEGQBAOC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Wasserstein Divergence for GANs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Dinesh Acharya, Janine Thoma, Jiqing Wu, Luc Van Gool, Zhiwu Huang","submitted_at":"2017-12-04T11:57:28Z","abstract_excerpt":"In many domains of computer vision, generative adversarial networks (GANs) have achieved great success, among which the family of Wasserstein GANs (WGANs) is considered to be state-of-the-art due to the theoretical contributions and competitive qualitative performance. However, it is very challenging to approximate the $k$-Lipschitz constraint required by the Wasserstein-1 metric~(W-met). In this paper, we propose a novel Wasserstein divergence~(W-div), which is a relaxed version of W-met and does not require the $k$-Lipschitz constraint. As a concrete application, we introduce a Wasserstein d"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1712.01026","kind":"arxiv","version":4},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"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":"2026-05-18T00:06:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8gSOzLqO3NovbL2XuG3T6ND5jnSORmd3UQJW2BO503bIbUT0fa6CtVm0yKApmDeLI0B6uECT2V6TgclQ8Zn7BA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T04:44:16.142669Z"},"content_sha256":"42cd26ee58a4ee016453ce96dc16308d642293eb96e2d23a31bf2d50cbb44086","schema_version":"1.0","event_id":"sha256:42cd26ee58a4ee016453ce96dc16308d642293eb96e2d23a31bf2d50cbb44086"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/PAC7EI54CLPBWOH7MQCEGQBAOC/bundle.json","state_url":"https://pith.science/pith/PAC7EI54CLPBWOH7MQCEGQBAOC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/PAC7EI54CLPBWOH7MQCEGQBAOC/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":"2026-05-27T04:44:16Z","links":{"resolver":"https://pith.science/pith/PAC7EI54CLPBWOH7MQCEGQBAOC","bundle":"https://pith.science/pith/PAC7EI54CLPBWOH7MQCEGQBAOC/bundle.json","state":"https://pith.science/pith/PAC7EI54CLPBWOH7MQCEGQBAOC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/PAC7EI54CLPBWOH7MQCEGQBAOC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:PAC7EI54CLPBWOH7MQCEGQBAOC","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":"fc28999f7c780c121143e10c94b740f7d01b7c3f1cf2f7ec17e931bf89fdc922","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-12-04T11:57:28Z","title_canon_sha256":"b251ddd940dfec12a18241d1b01099e16864f914e1afc17dd45a0775ce1f690c"},"schema_version":"1.0","source":{"id":"1712.01026","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1712.01026","created_at":"2026-05-18T00:06:30Z"},{"alias_kind":"arxiv_version","alias_value":"1712.01026v4","created_at":"2026-05-18T00:06:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1712.01026","created_at":"2026-05-18T00:06:30Z"},{"alias_kind":"pith_short_12","alias_value":"PAC7EI54CLPB","created_at":"2026-05-18T12:31:37Z"},{"alias_kind":"pith_short_16","alias_value":"PAC7EI54CLPBWOH7","created_at":"2026-05-18T12:31:37Z"},{"alias_kind":"pith_short_8","alias_value":"PAC7EI54","created_at":"2026-05-18T12:31:37Z"}],"graph_snapshots":[{"event_id":"sha256:42cd26ee58a4ee016453ce96dc16308d642293eb96e2d23a31bf2d50cbb44086","target":"graph","created_at":"2026-05-18T00:06:30Z","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"},"paper":{"abstract_excerpt":"In many domains of computer vision, generative adversarial networks (GANs) have achieved great success, among which the family of Wasserstein GANs (WGANs) is considered to be state-of-the-art due to the theoretical contributions and competitive qualitative performance. However, it is very challenging to approximate the $k$-Lipschitz constraint required by the Wasserstein-1 metric~(W-met). In this paper, we propose a novel Wasserstein divergence~(W-div), which is a relaxed version of W-met and does not require the $k$-Lipschitz constraint. As a concrete application, we introduce a Wasserstein d","authors_text":"Dinesh Acharya, Janine Thoma, Jiqing Wu, Luc Van Gool, Zhiwu Huang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-12-04T11:57:28Z","title":"Wasserstein Divergence for GANs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1712.01026","kind":"arxiv","version":4},"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":"sha256:18c4dc5b4b589a18a1fd67c52c22bec252cded3285791409ceab086fb132aa25","target":"record","created_at":"2026-05-18T00:06:30Z","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":"fc28999f7c780c121143e10c94b740f7d01b7c3f1cf2f7ec17e931bf89fdc922","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-12-04T11:57:28Z","title_canon_sha256":"b251ddd940dfec12a18241d1b01099e16864f914e1afc17dd45a0775ce1f690c"},"schema_version":"1.0","source":{"id":"1712.01026","kind":"arxiv","version":4}},"canonical_sha256":"7805f223bc12de1b38ff640443402070b83db7fe8d8b9122ee300c8edb66ac88","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7805f223bc12de1b38ff640443402070b83db7fe8d8b9122ee300c8edb66ac88","first_computed_at":"2026-05-18T00:06:30.839336Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:06:30.839336Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"R8h5Z1ykslxmpbysjZF4vOZPK5wbXATqDJxr+Ckee2K8kJJjdfyeXB5S/NGSXDMGn1kZKYwmKRCPn1yr07xkBw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:06:30.839750Z","signed_message":"canonical_sha256_bytes"},"source_id":"1712.01026","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:18c4dc5b4b589a18a1fd67c52c22bec252cded3285791409ceab086fb132aa25","sha256:42cd26ee58a4ee016453ce96dc16308d642293eb96e2d23a31bf2d50cbb44086"],"state_sha256":"57022bf73603320e2a05f0317f38fcf0db2b5fcb9d4d36f7b123c4256d02a7b8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Y+X3q7YcWf97QZ+6xfWgMKM+ErSY9r+xQtTJnl/HEN4tCYaftfg+F6leT26c37E4xxrvXWljWJ99eKKB0FiOBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-27T04:44:16.144974Z","bundle_sha256":"8f419cca3a71756774482d72ed1955a4743d4f0d5660635d3d9d83d218e8d5df"}}