{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:RAZMIADGEI3IGGCAGEIY3GGFNY","short_pith_number":"pith:RAZMIADG","canonical_record":{"source":{"id":"2305.15712","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-05-25T04:49:34Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"963542cf3c6c646182b5081956af54bbf381af0edd6a151ebddfff367187fd6b","abstract_canon_sha256":"4086e0ab9e2c7820a59c8729a8a74b391c73e69c8fe03e8a08613d9c536ba3a4"},"schema_version":"1.0"},"canonical_sha256":"8832c40066223683184031118d98c56e005385b4cd4225c6453e0cd3e574eed5","source":{"kind":"arxiv","id":"2305.15712","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.15712","created_at":"2026-07-05T07:19:45Z"},{"alias_kind":"arxiv_version","alias_value":"2305.15712v2","created_at":"2026-07-05T07:19:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.15712","created_at":"2026-07-05T07:19:45Z"},{"alias_kind":"pith_short_12","alias_value":"RAZMIADGEI3I","created_at":"2026-07-05T07:19:45Z"},{"alias_kind":"pith_short_16","alias_value":"RAZMIADGEI3IGGCA","created_at":"2026-07-05T07:19:45Z"},{"alias_kind":"pith_short_8","alias_value":"RAZMIADG","created_at":"2026-07-05T07:19:45Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:RAZMIADGEI3IGGCAGEIY3GGFNY","target":"record","payload":{"canonical_record":{"source":{"id":"2305.15712","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-05-25T04:49:34Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"963542cf3c6c646182b5081956af54bbf381af0edd6a151ebddfff367187fd6b","abstract_canon_sha256":"4086e0ab9e2c7820a59c8729a8a74b391c73e69c8fe03e8a08613d9c536ba3a4"},"schema_version":"1.0"},"canonical_sha256":"8832c40066223683184031118d98c56e005385b4cd4225c6453e0cd3e574eed5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:19:45.424159Z","signature_b64":"euOvjaYBPEb/PlvT/DO1GM6YjOqAploLi1OcAzLE17Y3dYMUmuTQ9rG4BuIQnx4oZNqb/0cfumTozQZACLbrDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8832c40066223683184031118d98c56e005385b4cd4225c6453e0cd3e574eed5","last_reissued_at":"2026-07-05T07:19:45.423230Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:19:45.423230Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2305.15712","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:19:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Xw/lLvCOE1Rg4IVQLkECuchzEWprhi5ZKG1x/2IbIfAlqQmGJDVg7m2J4CaVBVb4+ZDGSX8dULIiu5ACDbS9Dg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T05:48:25.480409Z"},"content_sha256":"7b71288d863af610226153ef56cd6a2c633860942189f0e6d64d80797112d992","schema_version":"1.0","event_id":"sha256:7b71288d863af610226153ef56cd6a2c633860942189f0e6d64d80797112d992"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:RAZMIADGEI3IGGCAGEIY3GGFNY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Knowledge Diffusion for Distillation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Chang Xu, Chen Qian, Fei Wang, Mingkai Zheng, Shan You, Tao Huang, Yuan Zhang","submitted_at":"2023-05-25T04:49:34Z","abstract_excerpt":"The representation gap between teacher and student is an emerging topic in knowledge distillation (KD). To reduce the gap and improve the performance, current methods often resort to complicated training schemes, loss functions, and feature alignments, which are task-specific and feature-specific. In this paper, we state that the essence of these methods is to discard the noisy information and distill the valuable information in the feature, and propose a novel KD method dubbed DiffKD, to explicitly denoise and match features using diffusion models. Our approach is based on the observation tha"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.15712","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/2305.15712/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":"2026-07-05T07:19:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"txvu0ZEptURlIYnzaulUkc/SbpoGZWwdlNU2dNIdsW/eohSuZD5hLCNW1jpTlxi24LLG0pYUy4CSkfnElVY3Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T05:48:25.480796Z"},"content_sha256":"380aea47fc04029fab412e2eabb0eaaba4e9de0521cee38c3e241b49abc64427","schema_version":"1.0","event_id":"sha256:380aea47fc04029fab412e2eabb0eaaba4e9de0521cee38c3e241b49abc64427"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/RAZMIADGEI3IGGCAGEIY3GGFNY/bundle.json","state_url":"https://pith.science/pith/RAZMIADGEI3IGGCAGEIY3GGFNY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/RAZMIADGEI3IGGCAGEIY3GGFNY/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":"2026-07-07T05:48:25Z","links":{"resolver":"https://pith.science/pith/RAZMIADGEI3IGGCAGEIY3GGFNY","bundle":"https://pith.science/pith/RAZMIADGEI3IGGCAGEIY3GGFNY/bundle.json","state":"https://pith.science/pith/RAZMIADGEI3IGGCAGEIY3GGFNY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/RAZMIADGEI3IGGCAGEIY3GGFNY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:RAZMIADGEI3IGGCAGEIY3GGFNY","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":"4086e0ab9e2c7820a59c8729a8a74b391c73e69c8fe03e8a08613d9c536ba3a4","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-05-25T04:49:34Z","title_canon_sha256":"963542cf3c6c646182b5081956af54bbf381af0edd6a151ebddfff367187fd6b"},"schema_version":"1.0","source":{"id":"2305.15712","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.15712","created_at":"2026-07-05T07:19:45Z"},{"alias_kind":"arxiv_version","alias_value":"2305.15712v2","created_at":"2026-07-05T07:19:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.15712","created_at":"2026-07-05T07:19:45Z"},{"alias_kind":"pith_short_12","alias_value":"RAZMIADGEI3I","created_at":"2026-07-05T07:19:45Z"},{"alias_kind":"pith_short_16","alias_value":"RAZMIADGEI3IGGCA","created_at":"2026-07-05T07:19:45Z"},{"alias_kind":"pith_short_8","alias_value":"RAZMIADG","created_at":"2026-07-05T07:19:45Z"}],"graph_snapshots":[{"event_id":"sha256:380aea47fc04029fab412e2eabb0eaaba4e9de0521cee38c3e241b49abc64427","target":"graph","created_at":"2026-07-05T07:19:45Z","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/2305.15712/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The representation gap between teacher and student is an emerging topic in knowledge distillation (KD). To reduce the gap and improve the performance, current methods often resort to complicated training schemes, loss functions, and feature alignments, which are task-specific and feature-specific. In this paper, we state that the essence of these methods is to discard the noisy information and distill the valuable information in the feature, and propose a novel KD method dubbed DiffKD, to explicitly denoise and match features using diffusion models. Our approach is based on the observation tha","authors_text":"Chang Xu, Chen Qian, Fei Wang, Mingkai Zheng, Shan You, Tao Huang, Yuan Zhang","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-05-25T04:49:34Z","title":"Knowledge Diffusion for Distillation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.15712","kind":"arxiv","version":2},"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":"sha256:7b71288d863af610226153ef56cd6a2c633860942189f0e6d64d80797112d992","target":"record","created_at":"2026-07-05T07:19:45Z","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":"4086e0ab9e2c7820a59c8729a8a74b391c73e69c8fe03e8a08613d9c536ba3a4","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-05-25T04:49:34Z","title_canon_sha256":"963542cf3c6c646182b5081956af54bbf381af0edd6a151ebddfff367187fd6b"},"schema_version":"1.0","source":{"id":"2305.15712","kind":"arxiv","version":2}},"canonical_sha256":"8832c40066223683184031118d98c56e005385b4cd4225c6453e0cd3e574eed5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8832c40066223683184031118d98c56e005385b4cd4225c6453e0cd3e574eed5","first_computed_at":"2026-07-05T07:19:45.423230Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:19:45.423230Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"euOvjaYBPEb/PlvT/DO1GM6YjOqAploLi1OcAzLE17Y3dYMUmuTQ9rG4BuIQnx4oZNqb/0cfumTozQZACLbrDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T07:19:45.424159Z","signed_message":"canonical_sha256_bytes"},"source_id":"2305.15712","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7b71288d863af610226153ef56cd6a2c633860942189f0e6d64d80797112d992","sha256:380aea47fc04029fab412e2eabb0eaaba4e9de0521cee38c3e241b49abc64427"],"state_sha256":"e0cd226dc30f3429e329604de473f1659a26472f386d926f5f61e311e827f2fb"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YMmAbXDKp30G11cfDyLqSAF45+I3HPi3TsnFmKPhQ7xO5dDc0MOgoFAtNyvWITJ48iymETyJD0yzZTxyjpU0Cw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T05:48:25.483332Z","bundle_sha256":"e3668615b06d08ff8d6c5ca9835daeb66f703820251175504bcdf024b4d542d0"}}