{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:QXBKBCFKKII7S3F34Z2E7WMY4W","short_pith_number":"pith:QXBKBCFK","canonical_record":{"source":{"id":"2203.06321","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-03-12T02:42:04Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"d2cd159c5ba297c04fc600af71e4f6fbeb3d574e017b7f91386e4c25076e802d","abstract_canon_sha256":"bd69301c2c66de7c8ac38dbd461ccb2c6aa59b80af5aa18b11b2b659a29eb986"},"schema_version":"1.0"},"canonical_sha256":"85c2a088aa5211f96cbbe6744fd998e59158fc8d9a4a2ae4d4d37256a473d0df","source":{"kind":"arxiv","id":"2203.06321","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.06321","created_at":"2026-07-05T04:04:49Z"},{"alias_kind":"arxiv_version","alias_value":"2203.06321v1","created_at":"2026-07-05T04:04:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.06321","created_at":"2026-07-05T04:04:49Z"},{"alias_kind":"pith_short_12","alias_value":"QXBKBCFKKII7","created_at":"2026-07-05T04:04:49Z"},{"alias_kind":"pith_short_16","alias_value":"QXBKBCFKKII7S3F3","created_at":"2026-07-05T04:04:49Z"},{"alias_kind":"pith_short_8","alias_value":"QXBKBCFK","created_at":"2026-07-05T04:04:49Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:QXBKBCFKKII7S3F34Z2E7WMY4W","target":"record","payload":{"canonical_record":{"source":{"id":"2203.06321","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-03-12T02:42:04Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"d2cd159c5ba297c04fc600af71e4f6fbeb3d574e017b7f91386e4c25076e802d","abstract_canon_sha256":"bd69301c2c66de7c8ac38dbd461ccb2c6aa59b80af5aa18b11b2b659a29eb986"},"schema_version":"1.0"},"canonical_sha256":"85c2a088aa5211f96cbbe6744fd998e59158fc8d9a4a2ae4d4d37256a473d0df","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:04:49.640418Z","signature_b64":"LMLhHH9mFAQXyuKA4IW4T97V2EUZ5IfV1zw21q2KsOsbHVECEXlyXhtQuYoZYeCOnyRkAsFAoXrjnZ7cp6bXDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"85c2a088aa5211f96cbbe6744fd998e59158fc8d9a4a2ae4d4d37256a473d0df","last_reissued_at":"2026-07-05T04:04:49.639990Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:04:49.639990Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2203.06321","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T04:04:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ilo+IVY5hB/BJPZcV489+Xtq0XIICeCRAOBWsoU47x4u+v3cBu9i3Ij3DF89AOagYPyz4jRLS6RK+REDgDwuDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T04:52:21.437205Z"},"content_sha256":"c7b64ab4dc77e94f85f7f6bd15cb67007842d0017e21457e8b3ee0688d735dab","schema_version":"1.0","event_id":"sha256:c7b64ab4dc77e94f85f7f6bd15cb67007842d0017e21457e8b3ee0688d735dab"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:QXBKBCFKKII7S3F34Z2E7WMY4W","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Wavelet Knowledge Distillation: Towards Efficient Image-to-Image Translation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Kaisheng Ma, Linfeng Zhang, Ning Xu, Pengfei Wan, Xiaobing Tu, Xin Chen","submitted_at":"2022-03-12T02:42:04Z","abstract_excerpt":"Remarkable achievements have been attained with Generative Adversarial Networks (GANs) in image-to-image translation. However, due to a tremendous amount of parameters, state-of-the-art GANs usually suffer from low efficiency and bulky memory usage. To tackle this challenge, firstly, this paper investigates GANs performance from a frequency perspective. The results show that GANs, especially small GANs lack the ability to generate high-quality high frequency information. To address this problem, we propose a novel knowledge distillation method referred to as wavelet knowledge distillation. Ins"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.06321","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/2203.06321/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":"2026-07-05T04:04:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WuczNOSZDKlK7UjU4hY7UzFUODoxD54NC2jS1yltjk8e7PZd12Pdm4Z1Ld56vOhV+WIQQa2vZE9HO5Cy0aYpCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T04:52:21.438401Z"},"content_sha256":"8b728484817af5b684ed9f73d8ee3248360c7edbe85cae6e9dbccd5f27dbdec5","schema_version":"1.0","event_id":"sha256:8b728484817af5b684ed9f73d8ee3248360c7edbe85cae6e9dbccd5f27dbdec5"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/QXBKBCFKKII7S3F34Z2E7WMY4W/bundle.json","state_url":"https://pith.science/pith/QXBKBCFKKII7S3F34Z2E7WMY4W/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/QXBKBCFKKII7S3F34Z2E7WMY4W/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":"2026-08-18T04:52:21Z","links":{"resolver":"https://pith.science/pith/QXBKBCFKKII7S3F34Z2E7WMY4W","bundle":"https://pith.science/pith/QXBKBCFKKII7S3F34Z2E7WMY4W/bundle.json","state":"https://pith.science/pith/QXBKBCFKKII7S3F34Z2E7WMY4W/state.json","well_known_bundle":"https://pith.science/.well-known/pith/QXBKBCFKKII7S3F34Z2E7WMY4W/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:QXBKBCFKKII7S3F34Z2E7WMY4W","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":"bd69301c2c66de7c8ac38dbd461ccb2c6aa59b80af5aa18b11b2b659a29eb986","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-03-12T02:42:04Z","title_canon_sha256":"d2cd159c5ba297c04fc600af71e4f6fbeb3d574e017b7f91386e4c25076e802d"},"schema_version":"1.0","source":{"id":"2203.06321","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.06321","created_at":"2026-07-05T04:04:49Z"},{"alias_kind":"arxiv_version","alias_value":"2203.06321v1","created_at":"2026-07-05T04:04:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.06321","created_at":"2026-07-05T04:04:49Z"},{"alias_kind":"pith_short_12","alias_value":"QXBKBCFKKII7","created_at":"2026-07-05T04:04:49Z"},{"alias_kind":"pith_short_16","alias_value":"QXBKBCFKKII7S3F3","created_at":"2026-07-05T04:04:49Z"},{"alias_kind":"pith_short_8","alias_value":"QXBKBCFK","created_at":"2026-07-05T04:04:49Z"}],"graph_snapshots":[{"event_id":"sha256:8b728484817af5b684ed9f73d8ee3248360c7edbe85cae6e9dbccd5f27dbdec5","target":"graph","created_at":"2026-07-05T04:04:49Z","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/2203.06321/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Remarkable achievements have been attained with Generative Adversarial Networks (GANs) in image-to-image translation. However, due to a tremendous amount of parameters, state-of-the-art GANs usually suffer from low efficiency and bulky memory usage. To tackle this challenge, firstly, this paper investigates GANs performance from a frequency perspective. The results show that GANs, especially small GANs lack the ability to generate high-quality high frequency information. To address this problem, we propose a novel knowledge distillation method referred to as wavelet knowledge distillation. Ins","authors_text":"Kaisheng Ma, Linfeng Zhang, Ning Xu, Pengfei Wan, Xiaobing Tu, Xin Chen","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-03-12T02:42:04Z","title":"Wavelet Knowledge Distillation: Towards Efficient Image-to-Image Translation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.06321","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:c7b64ab4dc77e94f85f7f6bd15cb67007842d0017e21457e8b3ee0688d735dab","target":"record","created_at":"2026-07-05T04:04:49Z","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":"bd69301c2c66de7c8ac38dbd461ccb2c6aa59b80af5aa18b11b2b659a29eb986","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-03-12T02:42:04Z","title_canon_sha256":"d2cd159c5ba297c04fc600af71e4f6fbeb3d574e017b7f91386e4c25076e802d"},"schema_version":"1.0","source":{"id":"2203.06321","kind":"arxiv","version":1}},"canonical_sha256":"85c2a088aa5211f96cbbe6744fd998e59158fc8d9a4a2ae4d4d37256a473d0df","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"85c2a088aa5211f96cbbe6744fd998e59158fc8d9a4a2ae4d4d37256a473d0df","first_computed_at":"2026-07-05T04:04:49.639990Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:04:49.639990Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"LMLhHH9mFAQXyuKA4IW4T97V2EUZ5IfV1zw21q2KsOsbHVECEXlyXhtQuYoZYeCOnyRkAsFAoXrjnZ7cp6bXDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T04:04:49.640418Z","signed_message":"canonical_sha256_bytes"},"source_id":"2203.06321","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c7b64ab4dc77e94f85f7f6bd15cb67007842d0017e21457e8b3ee0688d735dab","sha256:8b728484817af5b684ed9f73d8ee3248360c7edbe85cae6e9dbccd5f27dbdec5"],"state_sha256":"87b97f47b0ee2b6e6b976128d2a948d326ec97ff648a71db4750f1ab12abf50b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"p1F0JoFsnORflqlxiVqZqiVp56aqaDGIIWpf1UZ1s8RjTTUFqCnF6pkF7noDhivMPaxjEvJ++za7yzCAQGpICQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-18T04:52:21.446624Z","bundle_sha256":"6d715f5dfe5b8a0bfcd44f2ae90644142296cbe9a061ad45aa53707c4ddcdb52"}}