{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:HTB2T7CM6D52YMT5ZMEFXSYDQV","short_pith_number":"pith:HTB2T7CM","canonical_record":{"source":{"id":"2208.12055","kind":"arxiv","version":6},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-08-25T12:33:31Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"934937129311f170897bda36d183f8692d428d8acaad44beb2d7e1517b8369d8","abstract_canon_sha256":"0c7d8b1901983c430e88e421bc2fb8951008ab71e2ebe21d6555f66537f66b2a"},"schema_version":"1.0"},"canonical_sha256":"3cc3a9fc4cf0fbac327dcb085bcb0385763def22b42706c7c80bbcf0d0f26fce","source":{"kind":"arxiv","id":"2208.12055","version":6},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2208.12055","created_at":"2026-07-05T05:59:03Z"},{"alias_kind":"arxiv_version","alias_value":"2208.12055v6","created_at":"2026-07-05T05:59:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2208.12055","created_at":"2026-07-05T05:59:03Z"},{"alias_kind":"pith_short_12","alias_value":"HTB2T7CM6D52","created_at":"2026-07-05T05:59:03Z"},{"alias_kind":"pith_short_16","alias_value":"HTB2T7CM6D52YMT5","created_at":"2026-07-05T05:59:03Z"},{"alias_kind":"pith_short_8","alias_value":"HTB2T7CM","created_at":"2026-07-05T05:59:03Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:HTB2T7CM6D52YMT5ZMEFXSYDQV","target":"record","payload":{"canonical_record":{"source":{"id":"2208.12055","kind":"arxiv","version":6},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-08-25T12:33:31Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"934937129311f170897bda36d183f8692d428d8acaad44beb2d7e1517b8369d8","abstract_canon_sha256":"0c7d8b1901983c430e88e421bc2fb8951008ab71e2ebe21d6555f66537f66b2a"},"schema_version":"1.0"},"canonical_sha256":"3cc3a9fc4cf0fbac327dcb085bcb0385763def22b42706c7c80bbcf0d0f26fce","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:59:03.933949Z","signature_b64":"qVmWFtFiJwmD8cLyPBhgTUfDSeDBIBSFOR1wuR495EiRS+cxeWPaoRv//RO6nfbGJzr2Gn/Sf7I3nCK08JonCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3cc3a9fc4cf0fbac327dcb085bcb0385763def22b42706c7c80bbcf0d0f26fce","last_reissued_at":"2026-07-05T05:59:03.933536Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:59:03.933536Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2208.12055","source_version":6,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:59:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"s0Ysgo59MbVNj6TLBE8InrpyKo3NUmjKDff67UE0fgNGm7SwsyQqVrYQzhN0ZbSLwgR45kHvhq4WR/P6duShBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-11T03:56:32.091173Z"},"content_sha256":"63acebe2a3fd6ff85e8d953b6953e2ab95b57c79edf99704d5fee23e63511a63","schema_version":"1.0","event_id":"sha256:63acebe2a3fd6ff85e8d953b6953e2ab95b57c79edf99704d5fee23e63511a63"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:HTB2T7CM6D52YMT5ZMEFXSYDQV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Combating Mode Collapse in GANs via Manifold Entropy Estimation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Bernard Ghanem, Bing Li, Hanbang Liang, Haoqian Wu, Haozhe Liu, Yawen Huang, Yefeng Zheng, Yuexiang Li","submitted_at":"2022-08-25T12:33:31Z","abstract_excerpt":"Generative Adversarial Networks (GANs) have shown compelling results in various tasks and applications in recent years. However, mode collapse remains a critical problem in GANs. In this paper, we propose a novel training pipeline to address the mode collapse issue of GANs. Different from existing methods, we propose to generalize the discriminator as feature embedding and maximize the entropy of distributions in the embedding space learned by the discriminator. Specifically, two regularization terms, i.e., Deep Local Linear Embedding (DLLE) and Deep Isometric feature Mapping (DIsoMap), are de"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2208.12055","kind":"arxiv","version":6},"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/2208.12055/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:59:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"92rf2XIJZMIJgw8x3IuL6SzIcDB/G7EBuGlAnVBDyZWx/45Udv3B+ZpMacxuhh5IQcyiF+vrCOZD2185woo6BQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-11T03:56:32.091581Z"},"content_sha256":"1c51083f3ea1b5d9637b4bca4a8673222e324b1f2eb1b99d71348de4966fc6c4","schema_version":"1.0","event_id":"sha256:1c51083f3ea1b5d9637b4bca4a8673222e324b1f2eb1b99d71348de4966fc6c4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HTB2T7CM6D52YMT5ZMEFXSYDQV/bundle.json","state_url":"https://pith.science/pith/HTB2T7CM6D52YMT5ZMEFXSYDQV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HTB2T7CM6D52YMT5ZMEFXSYDQV/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":"2026-07-11T03:56:32Z","links":{"resolver":"https://pith.science/pith/HTB2T7CM6D52YMT5ZMEFXSYDQV","bundle":"https://pith.science/pith/HTB2T7CM6D52YMT5ZMEFXSYDQV/bundle.json","state":"https://pith.science/pith/HTB2T7CM6D52YMT5ZMEFXSYDQV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HTB2T7CM6D52YMT5ZMEFXSYDQV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:HTB2T7CM6D52YMT5ZMEFXSYDQV","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":"0c7d8b1901983c430e88e421bc2fb8951008ab71e2ebe21d6555f66537f66b2a","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-08-25T12:33:31Z","title_canon_sha256":"934937129311f170897bda36d183f8692d428d8acaad44beb2d7e1517b8369d8"},"schema_version":"1.0","source":{"id":"2208.12055","kind":"arxiv","version":6}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2208.12055","created_at":"2026-07-05T05:59:03Z"},{"alias_kind":"arxiv_version","alias_value":"2208.12055v6","created_at":"2026-07-05T05:59:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2208.12055","created_at":"2026-07-05T05:59:03Z"},{"alias_kind":"pith_short_12","alias_value":"HTB2T7CM6D52","created_at":"2026-07-05T05:59:03Z"},{"alias_kind":"pith_short_16","alias_value":"HTB2T7CM6D52YMT5","created_at":"2026-07-05T05:59:03Z"},{"alias_kind":"pith_short_8","alias_value":"HTB2T7CM","created_at":"2026-07-05T05:59:03Z"}],"graph_snapshots":[{"event_id":"sha256:1c51083f3ea1b5d9637b4bca4a8673222e324b1f2eb1b99d71348de4966fc6c4","target":"graph","created_at":"2026-07-05T05:59:03Z","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/2208.12055/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Generative Adversarial Networks (GANs) have shown compelling results in various tasks and applications in recent years. However, mode collapse remains a critical problem in GANs. In this paper, we propose a novel training pipeline to address the mode collapse issue of GANs. Different from existing methods, we propose to generalize the discriminator as feature embedding and maximize the entropy of distributions in the embedding space learned by the discriminator. Specifically, two regularization terms, i.e., Deep Local Linear Embedding (DLLE) and Deep Isometric feature Mapping (DIsoMap), are de","authors_text":"Bernard Ghanem, Bing Li, Hanbang Liang, Haoqian Wu, Haozhe Liu, Yawen Huang, Yefeng Zheng, Yuexiang Li","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-08-25T12:33:31Z","title":"Combating Mode Collapse in GANs via Manifold Entropy Estimation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2208.12055","kind":"arxiv","version":6},"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":"sha256:63acebe2a3fd6ff85e8d953b6953e2ab95b57c79edf99704d5fee23e63511a63","target":"record","created_at":"2026-07-05T05:59:03Z","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":"0c7d8b1901983c430e88e421bc2fb8951008ab71e2ebe21d6555f66537f66b2a","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-08-25T12:33:31Z","title_canon_sha256":"934937129311f170897bda36d183f8692d428d8acaad44beb2d7e1517b8369d8"},"schema_version":"1.0","source":{"id":"2208.12055","kind":"arxiv","version":6}},"canonical_sha256":"3cc3a9fc4cf0fbac327dcb085bcb0385763def22b42706c7c80bbcf0d0f26fce","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3cc3a9fc4cf0fbac327dcb085bcb0385763def22b42706c7c80bbcf0d0f26fce","first_computed_at":"2026-07-05T05:59:03.933536Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:59:03.933536Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"qVmWFtFiJwmD8cLyPBhgTUfDSeDBIBSFOR1wuR495EiRS+cxeWPaoRv//RO6nfbGJzr2Gn/Sf7I3nCK08JonCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T05:59:03.933949Z","signed_message":"canonical_sha256_bytes"},"source_id":"2208.12055","source_kind":"arxiv","source_version":6}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:63acebe2a3fd6ff85e8d953b6953e2ab95b57c79edf99704d5fee23e63511a63","sha256:1c51083f3ea1b5d9637b4bca4a8673222e324b1f2eb1b99d71348de4966fc6c4"],"state_sha256":"5d0668467b20c8066b86ee3141d9489c49ac3fb07eb5a5562700cde70d717f8c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ES1RDu16cQKGTnyluV8YH8RGczp/BMmpcENntvcdiZgR4BKaHpKhP5LRUu3r65zU9yF+wRd9hgNWCohh5kvfBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-11T03:56:32.093755Z","bundle_sha256":"f348f48d86eef7576969f07e256389196a2fd65cdd43e7ac0d46a1db5dda5114"}}