{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:352Y2OCVXB5A2UXTVI42MJ72QY","short_pith_number":"pith:352Y2OCV","canonical_record":{"source":{"id":"2305.00374","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-04-30T03:12:21Z","cross_cats_sorted":["cs.CR"],"title_canon_sha256":"6d639f73ec6d86fe6815ea0c998e2886899192c5c50fb76ed4dfbfbf6dfc04c9","abstract_canon_sha256":"aa15da215324eea4e3fa79ada2358c8e7f02c299a1476650c1ec29d02e21b9cf"},"schema_version":"1.0"},"canonical_sha256":"df758d3855b87a0d52f3aa39a627fa862d7cb9d140f768a37d30210823c2c5ea","source":{"kind":"arxiv","id":"2305.00374","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.00374","created_at":"2026-07-05T07:03:58Z"},{"alias_kind":"arxiv_version","alias_value":"2305.00374v2","created_at":"2026-07-05T07:03:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.00374","created_at":"2026-07-05T07:03:58Z"},{"alias_kind":"pith_short_12","alias_value":"352Y2OCVXB5A","created_at":"2026-07-05T07:03:58Z"},{"alias_kind":"pith_short_16","alias_value":"352Y2OCVXB5A2UXT","created_at":"2026-07-05T07:03:58Z"},{"alias_kind":"pith_short_8","alias_value":"352Y2OCV","created_at":"2026-07-05T07:03:58Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:352Y2OCVXB5A2UXTVI42MJ72QY","target":"record","payload":{"canonical_record":{"source":{"id":"2305.00374","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-04-30T03:12:21Z","cross_cats_sorted":["cs.CR"],"title_canon_sha256":"6d639f73ec6d86fe6815ea0c998e2886899192c5c50fb76ed4dfbfbf6dfc04c9","abstract_canon_sha256":"aa15da215324eea4e3fa79ada2358c8e7f02c299a1476650c1ec29d02e21b9cf"},"schema_version":"1.0"},"canonical_sha256":"df758d3855b87a0d52f3aa39a627fa862d7cb9d140f768a37d30210823c2c5ea","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:03:58.505393Z","signature_b64":"HioRazmp6Dj3d66RFe3XVPLG8uk9RDBQqMEuzv/ietGUNY97If/4DDJWNiA5C091MoNbiJljOY0yqphEioKJCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"df758d3855b87a0d52f3aa39a627fa862d7cb9d140f768a37d30210823c2c5ea","last_reissued_at":"2026-07-05T07:03:58.504859Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:03:58.504859Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2305.00374","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":"2026-07-05T07:03:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PvOJFKELs+TSplsK8KQq1I9mK3UYqp6DMZeiTsd8JZSyaBVxudWYJ2Mkqa4ln7izHRjzCqa4LqDMwScfTKK0CQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T04:35:48.742183Z"},"content_sha256":"ab5f9fd98d672685af5f083c1147f712bd5acbfb9edd0331a4b07a8cf988e790","schema_version":"1.0","event_id":"sha256:ab5f9fd98d672685af5f083c1147f712bd5acbfb9edd0331a4b07a8cf988e790"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:352Y2OCVXB5A2UXTVI42MJ72QY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Enhancing Adversarial Contrastive Learning via Adversarial Invariant Regularization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CR"],"primary_cat":"cs.LG","authors_text":"Feng Liu, Jingfeng Zhang, Masashi Sugiyama, Mohan Kankanhalli, Xilie Xu","submitted_at":"2023-04-30T03:12:21Z","abstract_excerpt":"Adversarial contrastive learning (ACL) is a technique that enhances standard contrastive learning (SCL) by incorporating adversarial data to learn a robust representation that can withstand adversarial attacks and common corruptions without requiring costly annotations. To improve transferability, the existing work introduced the standard invariant regularization (SIR) to impose style-independence property to SCL, which can exempt the impact of nuisance style factors in the standard representation. However, it is unclear how the style-independence property benefits ACL-learned robust represent"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.00374","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/2305.00374/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":"2026-07-05T07:03:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QhRV4/cnAmi/BXFKXycKb9fc7trmvo1BkWR2UqFczwiZlzYaJrx3oaQG4AURS1bHoCUyF4j6S8h9iPdIWlwyDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T04:35:48.742587Z"},"content_sha256":"7d1ad4d1f0869590995c03ebc8f171eac7bb23f899cdd9942a207a693fc85811","schema_version":"1.0","event_id":"sha256:7d1ad4d1f0869590995c03ebc8f171eac7bb23f899cdd9942a207a693fc85811"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/352Y2OCVXB5A2UXTVI42MJ72QY/bundle.json","state_url":"https://pith.science/pith/352Y2OCVXB5A2UXTVI42MJ72QY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/352Y2OCVXB5A2UXTVI42MJ72QY/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":"2026-07-07T04:35:48Z","links":{"resolver":"https://pith.science/pith/352Y2OCVXB5A2UXTVI42MJ72QY","bundle":"https://pith.science/pith/352Y2OCVXB5A2UXTVI42MJ72QY/bundle.json","state":"https://pith.science/pith/352Y2OCVXB5A2UXTVI42MJ72QY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/352Y2OCVXB5A2UXTVI42MJ72QY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:352Y2OCVXB5A2UXTVI42MJ72QY","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":"aa15da215324eea4e3fa79ada2358c8e7f02c299a1476650c1ec29d02e21b9cf","cross_cats_sorted":["cs.CR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-04-30T03:12:21Z","title_canon_sha256":"6d639f73ec6d86fe6815ea0c998e2886899192c5c50fb76ed4dfbfbf6dfc04c9"},"schema_version":"1.0","source":{"id":"2305.00374","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.00374","created_at":"2026-07-05T07:03:58Z"},{"alias_kind":"arxiv_version","alias_value":"2305.00374v2","created_at":"2026-07-05T07:03:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.00374","created_at":"2026-07-05T07:03:58Z"},{"alias_kind":"pith_short_12","alias_value":"352Y2OCVXB5A","created_at":"2026-07-05T07:03:58Z"},{"alias_kind":"pith_short_16","alias_value":"352Y2OCVXB5A2UXT","created_at":"2026-07-05T07:03:58Z"},{"alias_kind":"pith_short_8","alias_value":"352Y2OCV","created_at":"2026-07-05T07:03:58Z"}],"graph_snapshots":[{"event_id":"sha256:7d1ad4d1f0869590995c03ebc8f171eac7bb23f899cdd9942a207a693fc85811","target":"graph","created_at":"2026-07-05T07:03:58Z","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/2305.00374/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Adversarial contrastive learning (ACL) is a technique that enhances standard contrastive learning (SCL) by incorporating adversarial data to learn a robust representation that can withstand adversarial attacks and common corruptions without requiring costly annotations. To improve transferability, the existing work introduced the standard invariant regularization (SIR) to impose style-independence property to SCL, which can exempt the impact of nuisance style factors in the standard representation. However, it is unclear how the style-independence property benefits ACL-learned robust represent","authors_text":"Feng Liu, Jingfeng Zhang, Masashi Sugiyama, Mohan Kankanhalli, Xilie Xu","cross_cats":["cs.CR"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-04-30T03:12:21Z","title":"Enhancing Adversarial Contrastive Learning via Adversarial Invariant Regularization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.00374","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:ab5f9fd98d672685af5f083c1147f712bd5acbfb9edd0331a4b07a8cf988e790","target":"record","created_at":"2026-07-05T07:03:58Z","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":"aa15da215324eea4e3fa79ada2358c8e7f02c299a1476650c1ec29d02e21b9cf","cross_cats_sorted":["cs.CR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-04-30T03:12:21Z","title_canon_sha256":"6d639f73ec6d86fe6815ea0c998e2886899192c5c50fb76ed4dfbfbf6dfc04c9"},"schema_version":"1.0","source":{"id":"2305.00374","kind":"arxiv","version":2}},"canonical_sha256":"df758d3855b87a0d52f3aa39a627fa862d7cb9d140f768a37d30210823c2c5ea","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"df758d3855b87a0d52f3aa39a627fa862d7cb9d140f768a37d30210823c2c5ea","first_computed_at":"2026-07-05T07:03:58.504859Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:03:58.504859Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"HioRazmp6Dj3d66RFe3XVPLG8uk9RDBQqMEuzv/ietGUNY97If/4DDJWNiA5C091MoNbiJljOY0yqphEioKJCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T07:03:58.505393Z","signed_message":"canonical_sha256_bytes"},"source_id":"2305.00374","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ab5f9fd98d672685af5f083c1147f712bd5acbfb9edd0331a4b07a8cf988e790","sha256:7d1ad4d1f0869590995c03ebc8f171eac7bb23f899cdd9942a207a693fc85811"],"state_sha256":"216999cb2bedde808f283eee835ff61514a0c5cc9fe1e0081671fa7397ab1cf3"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fPncndAEQk0UVwOreSvMDGQ63bhOavjftsHtfPeuQfGXySGW88DEvx5AePqePHn19mvFIlwuhKc/kwLINHhMAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T04:35:48.744585Z","bundle_sha256":"d2b5f8c0e750c3c861638dd6835a8ebba71d238c83b5c4ab37009f7de0370a6e"}}