{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:A2HTKZHVFAXAAD3IXZXOZUT6VD","short_pith_number":"pith:A2HTKZHV","canonical_record":{"source":{"id":"2211.00824","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-11-02T02:02:51Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"35959fc9eece4f67d02085d582f7860326038dfc0029d06d85a9378fb1a117f3","abstract_canon_sha256":"b8f2a2c64bbf041a68328ced784cfa1fa6d0a2355173d733ff03fc219755dad1"},"schema_version":"1.0"},"canonical_sha256":"068f3564f5282e000f68be6eecd27ea8fc8009687b9a594603a1250de1947f84","source":{"kind":"arxiv","id":"2211.00824","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.00824","created_at":"2026-07-05T05:12:35Z"},{"alias_kind":"arxiv_version","alias_value":"2211.00824v1","created_at":"2026-07-05T05:12:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.00824","created_at":"2026-07-05T05:12:35Z"},{"alias_kind":"pith_short_12","alias_value":"A2HTKZHVFAXA","created_at":"2026-07-05T05:12:35Z"},{"alias_kind":"pith_short_16","alias_value":"A2HTKZHVFAXAAD3I","created_at":"2026-07-05T05:12:35Z"},{"alias_kind":"pith_short_8","alias_value":"A2HTKZHV","created_at":"2026-07-05T05:12:35Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:A2HTKZHVFAXAAD3IXZXOZUT6VD","target":"record","payload":{"canonical_record":{"source":{"id":"2211.00824","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-11-02T02:02:51Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"35959fc9eece4f67d02085d582f7860326038dfc0029d06d85a9378fb1a117f3","abstract_canon_sha256":"b8f2a2c64bbf041a68328ced784cfa1fa6d0a2355173d733ff03fc219755dad1"},"schema_version":"1.0"},"canonical_sha256":"068f3564f5282e000f68be6eecd27ea8fc8009687b9a594603a1250de1947f84","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:12:35.326451Z","signature_b64":"0+MuXLU90SRIKzV40frWQP9nGFzGSrhOSdKQFtv/CIBJE1zJqitVs93WOvHsJ12iZZP1h0d4S0mJIlUh5Be+Ag==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"068f3564f5282e000f68be6eecd27ea8fc8009687b9a594603a1250de1947f84","last_reissued_at":"2026-07-05T05:12:35.326013Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:12:35.326013Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2211.00824","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":"2026-07-05T05:12:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hBibPmqB0IzEy6049Mdf9tMnGCFJ5nmsYqSx04pJr5qA5leITomTUzeHrsr5+8umLGzo9ST/rKCpplnFsMgJCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T10:11:24.307313Z"},"content_sha256":"6b69b6151173a42267c7e9e0cf7bf78f60a536c39bbb9512c8f7fb7b60bcbd0d","schema_version":"1.0","event_id":"sha256:6b69b6151173a42267c7e9e0cf7bf78f60a536c39bbb9512c8f7fb7b60bcbd0d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:A2HTKZHVFAXAAD3IXZXOZUT6VD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Adversarial Auto-Augment with Label Preservation: A Representation Learning Principle Guided Approach","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.LG","authors_text":"Dacheng Tao, Fengxiang He, Furong Huang, Jiahao Su, Kaiwen Yang, Tianyi Zhou, Xinmei Tian, Yanchao Sun","submitted_at":"2022-11-02T02:02:51Z","abstract_excerpt":"Data augmentation is a critical contributing factor to the success of deep learning but heavily relies on prior domain knowledge which is not always available. Recent works on automatic data augmentation learn a policy to form a sequence of augmentation operations, which are still pre-defined and restricted to limited options. In this paper, we show that a prior-free autonomous data augmentation's objective can be derived from a representation learning principle that aims to preserve the minimum sufficient information of the labels. Given an example, the objective aims at creating a distant \"h"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.00824","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/2211.00824/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":"2026-07-05T05:12:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nUccqErGxaUWSQ9w+mOxokicsWEg6cDcChYHnzIwMb1Sh1U/1C/aJGIN3Jbg+bf/5JtMn6Dcew02hUYqLeKlDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T10:11:24.307900Z"},"content_sha256":"ffed098efcc9614524abffbd9fc7995d9a2238100d9defb4801a1869a673ee3b","schema_version":"1.0","event_id":"sha256:ffed098efcc9614524abffbd9fc7995d9a2238100d9defb4801a1869a673ee3b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/A2HTKZHVFAXAAD3IXZXOZUT6VD/bundle.json","state_url":"https://pith.science/pith/A2HTKZHVFAXAAD3IXZXOZUT6VD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/A2HTKZHVFAXAAD3IXZXOZUT6VD/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":"2026-08-05T10:11:24Z","links":{"resolver":"https://pith.science/pith/A2HTKZHVFAXAAD3IXZXOZUT6VD","bundle":"https://pith.science/pith/A2HTKZHVFAXAAD3IXZXOZUT6VD/bundle.json","state":"https://pith.science/pith/A2HTKZHVFAXAAD3IXZXOZUT6VD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/A2HTKZHVFAXAAD3IXZXOZUT6VD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:A2HTKZHVFAXAAD3IXZXOZUT6VD","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":"b8f2a2c64bbf041a68328ced784cfa1fa6d0a2355173d733ff03fc219755dad1","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-11-02T02:02:51Z","title_canon_sha256":"35959fc9eece4f67d02085d582f7860326038dfc0029d06d85a9378fb1a117f3"},"schema_version":"1.0","source":{"id":"2211.00824","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.00824","created_at":"2026-07-05T05:12:35Z"},{"alias_kind":"arxiv_version","alias_value":"2211.00824v1","created_at":"2026-07-05T05:12:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.00824","created_at":"2026-07-05T05:12:35Z"},{"alias_kind":"pith_short_12","alias_value":"A2HTKZHVFAXA","created_at":"2026-07-05T05:12:35Z"},{"alias_kind":"pith_short_16","alias_value":"A2HTKZHVFAXAAD3I","created_at":"2026-07-05T05:12:35Z"},{"alias_kind":"pith_short_8","alias_value":"A2HTKZHV","created_at":"2026-07-05T05:12:35Z"}],"graph_snapshots":[{"event_id":"sha256:ffed098efcc9614524abffbd9fc7995d9a2238100d9defb4801a1869a673ee3b","target":"graph","created_at":"2026-07-05T05:12:35Z","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/2211.00824/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Data augmentation is a critical contributing factor to the success of deep learning but heavily relies on prior domain knowledge which is not always available. Recent works on automatic data augmentation learn a policy to form a sequence of augmentation operations, which are still pre-defined and restricted to limited options. In this paper, we show that a prior-free autonomous data augmentation's objective can be derived from a representation learning principle that aims to preserve the minimum sufficient information of the labels. Given an example, the objective aims at creating a distant \"h","authors_text":"Dacheng Tao, Fengxiang He, Furong Huang, Jiahao Su, Kaiwen Yang, Tianyi Zhou, Xinmei Tian, Yanchao Sun","cross_cats":["cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-11-02T02:02:51Z","title":"Adversarial Auto-Augment with Label Preservation: A Representation Learning Principle Guided Approach"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.00824","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":"sha256:6b69b6151173a42267c7e9e0cf7bf78f60a536c39bbb9512c8f7fb7b60bcbd0d","target":"record","created_at":"2026-07-05T05:12:35Z","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":"b8f2a2c64bbf041a68328ced784cfa1fa6d0a2355173d733ff03fc219755dad1","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-11-02T02:02:51Z","title_canon_sha256":"35959fc9eece4f67d02085d582f7860326038dfc0029d06d85a9378fb1a117f3"},"schema_version":"1.0","source":{"id":"2211.00824","kind":"arxiv","version":1}},"canonical_sha256":"068f3564f5282e000f68be6eecd27ea8fc8009687b9a594603a1250de1947f84","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"068f3564f5282e000f68be6eecd27ea8fc8009687b9a594603a1250de1947f84","first_computed_at":"2026-07-05T05:12:35.326013Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:12:35.326013Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"0+MuXLU90SRIKzV40frWQP9nGFzGSrhOSdKQFtv/CIBJE1zJqitVs93WOvHsJ12iZZP1h0d4S0mJIlUh5Be+Ag==","signature_status":"signed_v1","signed_at":"2026-07-05T05:12:35.326451Z","signed_message":"canonical_sha256_bytes"},"source_id":"2211.00824","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6b69b6151173a42267c7e9e0cf7bf78f60a536c39bbb9512c8f7fb7b60bcbd0d","sha256:ffed098efcc9614524abffbd9fc7995d9a2238100d9defb4801a1869a673ee3b"],"state_sha256":"1e3fc8d39610df822d76f35e56c361f050522df8f32443d0d15346a17304fc7f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HRm2kLRc4z0oIxIDukiFvTi3Gd4hoZNky6n5vfU7AHWABZCdbInU3rFV5fLve5Y+VG749WaGlhlTW8PZX0M4DA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T10:11:24.311484Z","bundle_sha256":"a01f9393e6c7f89392a8c0b60895cd64c8088eaf447566c5b4acd4bd789e9423"}}