{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:QUBVLCWE5L2F2KIZLSD363L4GV","short_pith_number":"pith:QUBVLCWE","canonical_record":{"source":{"id":"2406.04070","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-06-06T13:34:43Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"e02daf7201c50a879005db3c27817618b37b7249b82d6abd2fe2ce803c961b48","abstract_canon_sha256":"414b634d5318e45798672a7df8ba9e4a13dd33cb3e4bd4ea4e0b285b4f0a2015"},"schema_version":"1.0"},"canonical_sha256":"8503558ac4eaf45d29195c87bf6d7c35542bee46455b5c721273ebaa0b9dbb73","source":{"kind":"arxiv","id":"2406.04070","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.04070","created_at":"2026-07-05T08:28:20Z"},{"alias_kind":"arxiv_version","alias_value":"2406.04070v1","created_at":"2026-07-05T08:28:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.04070","created_at":"2026-07-05T08:28:20Z"},{"alias_kind":"pith_short_12","alias_value":"QUBVLCWE5L2F","created_at":"2026-07-05T08:28:20Z"},{"alias_kind":"pith_short_16","alias_value":"QUBVLCWE5L2F2KIZ","created_at":"2026-07-05T08:28:20Z"},{"alias_kind":"pith_short_8","alias_value":"QUBVLCWE","created_at":"2026-07-05T08:28:20Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:QUBVLCWE5L2F2KIZLSD363L4GV","target":"record","payload":{"canonical_record":{"source":{"id":"2406.04070","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-06-06T13:34:43Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"e02daf7201c50a879005db3c27817618b37b7249b82d6abd2fe2ce803c961b48","abstract_canon_sha256":"414b634d5318e45798672a7df8ba9e4a13dd33cb3e4bd4ea4e0b285b4f0a2015"},"schema_version":"1.0"},"canonical_sha256":"8503558ac4eaf45d29195c87bf6d7c35542bee46455b5c721273ebaa0b9dbb73","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:28:20.382964Z","signature_b64":"roiHo3J3JTYy/2XN51u4ll5Fu7jx+NsaJevuqNe3VZpWSqnzbmKPWBXtJtKOlO9PbGHZd3iewgmusDtsMNIrBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8503558ac4eaf45d29195c87bf6d7c35542bee46455b5c721273ebaa0b9dbb73","last_reissued_at":"2026-07-05T08:28:20.382513Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:28:20.382513Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2406.04070","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":"2026-07-05T08:28:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"24DUqdctXW9rIdX20WcqPBfF2pmJM7lN1te8IOX6USt9VZKkI3PIonUXgJeLdSdYc1VIVuDVZJo8pmsTWhRPBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-01T12:59:57.312632Z"},"content_sha256":"c5a3e96ace1950cbd41bdcfad3e72aef459f78d78dd1754d457ca464df65b6ea","schema_version":"1.0","event_id":"sha256:c5a3e96ace1950cbd41bdcfad3e72aef459f78d78dd1754d457ca464df65b6ea"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:QUBVLCWE5L2F2KIZLSD363L4GV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Batch-in-Batch: a new adversarial training framework for initial perturbation and sample selection","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"(2) School of Mathematics, (3) Key Laboratory of Aerospace Information Security, Bo Cai (3), Central China Normal University, Computer Science, Engineering, Jianghan University, Key Lab NAA--MOE, Le Li (1). ((1) School of Mathematics, Ministry of Education, Pai Peng (2), School of Cyber Science, Statistics, Trusted Computing, Wuhan University), Yinting Wu (1)","submitted_at":"2024-06-06T13:34:43Z","abstract_excerpt":"Adversarial training methods commonly generate independent initial perturbation for adversarial samples from a simple uniform distribution, and obtain the training batch for the classifier without selection. In this work, we propose a simple yet effective training framework called Batch-in-Batch (BB) to enhance models robustness. It involves specifically a joint construction of initial values that could simultaneously generates $m$ sets of perturbations from the original batch set to provide more diversity for adversarial samples; and also includes various sample selection strategies that enab"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.04070","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/2406.04070/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":"2026-07-05T08:28:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HRkuAOtyDHHesj/cNdJEy2tCgPLbYnCXM0gKg8+X6FKfHR3fOtI2vIQzdA8eFLOQthSRzEsq0mw8hVAyzBr/Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-01T12:59:57.313506Z"},"content_sha256":"ea612b670890e9cd71cea9a43a53f842a3962427bf3f45cfb43848ada9449458","schema_version":"1.0","event_id":"sha256:ea612b670890e9cd71cea9a43a53f842a3962427bf3f45cfb43848ada9449458"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/QUBVLCWE5L2F2KIZLSD363L4GV/bundle.json","state_url":"https://pith.science/pith/QUBVLCWE5L2F2KIZLSD363L4GV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/QUBVLCWE5L2F2KIZLSD363L4GV/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":"2026-08-01T12:59:57Z","links":{"resolver":"https://pith.science/pith/QUBVLCWE5L2F2KIZLSD363L4GV","bundle":"https://pith.science/pith/QUBVLCWE5L2F2KIZLSD363L4GV/bundle.json","state":"https://pith.science/pith/QUBVLCWE5L2F2KIZLSD363L4GV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/QUBVLCWE5L2F2KIZLSD363L4GV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:QUBVLCWE5L2F2KIZLSD363L4GV","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":"414b634d5318e45798672a7df8ba9e4a13dd33cb3e4bd4ea4e0b285b4f0a2015","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-06-06T13:34:43Z","title_canon_sha256":"e02daf7201c50a879005db3c27817618b37b7249b82d6abd2fe2ce803c961b48"},"schema_version":"1.0","source":{"id":"2406.04070","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.04070","created_at":"2026-07-05T08:28:20Z"},{"alias_kind":"arxiv_version","alias_value":"2406.04070v1","created_at":"2026-07-05T08:28:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.04070","created_at":"2026-07-05T08:28:20Z"},{"alias_kind":"pith_short_12","alias_value":"QUBVLCWE5L2F","created_at":"2026-07-05T08:28:20Z"},{"alias_kind":"pith_short_16","alias_value":"QUBVLCWE5L2F2KIZ","created_at":"2026-07-05T08:28:20Z"},{"alias_kind":"pith_short_8","alias_value":"QUBVLCWE","created_at":"2026-07-05T08:28:20Z"}],"graph_snapshots":[{"event_id":"sha256:ea612b670890e9cd71cea9a43a53f842a3962427bf3f45cfb43848ada9449458","target":"graph","created_at":"2026-07-05T08:28:20Z","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/2406.04070/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Adversarial training methods commonly generate independent initial perturbation for adversarial samples from a simple uniform distribution, and obtain the training batch for the classifier without selection. In this work, we propose a simple yet effective training framework called Batch-in-Batch (BB) to enhance models robustness. It involves specifically a joint construction of initial values that could simultaneously generates $m$ sets of perturbations from the original batch set to provide more diversity for adversarial samples; and also includes various sample selection strategies that enab","authors_text":"(2) School of Mathematics, (3) Key Laboratory of Aerospace Information Security, Bo Cai (3), Central China Normal University, Computer Science, Engineering, Jianghan University, Key Lab NAA--MOE, Le Li (1). ((1) School of Mathematics, Ministry of Education, Pai Peng (2), School of Cyber Science, Statistics, Trusted Computing, Wuhan University), Yinting Wu (1)","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-06-06T13:34:43Z","title":"Batch-in-Batch: a new adversarial training framework for initial perturbation and sample selection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.04070","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:c5a3e96ace1950cbd41bdcfad3e72aef459f78d78dd1754d457ca464df65b6ea","target":"record","created_at":"2026-07-05T08:28:20Z","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":"414b634d5318e45798672a7df8ba9e4a13dd33cb3e4bd4ea4e0b285b4f0a2015","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-06-06T13:34:43Z","title_canon_sha256":"e02daf7201c50a879005db3c27817618b37b7249b82d6abd2fe2ce803c961b48"},"schema_version":"1.0","source":{"id":"2406.04070","kind":"arxiv","version":1}},"canonical_sha256":"8503558ac4eaf45d29195c87bf6d7c35542bee46455b5c721273ebaa0b9dbb73","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8503558ac4eaf45d29195c87bf6d7c35542bee46455b5c721273ebaa0b9dbb73","first_computed_at":"2026-07-05T08:28:20.382513Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:28:20.382513Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"roiHo3J3JTYy/2XN51u4ll5Fu7jx+NsaJevuqNe3VZpWSqnzbmKPWBXtJtKOlO9PbGHZd3iewgmusDtsMNIrBA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:28:20.382964Z","signed_message":"canonical_sha256_bytes"},"source_id":"2406.04070","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c5a3e96ace1950cbd41bdcfad3e72aef459f78d78dd1754d457ca464df65b6ea","sha256:ea612b670890e9cd71cea9a43a53f842a3962427bf3f45cfb43848ada9449458"],"state_sha256":"30e304efcb57c6ae277d665c02e95b3fabd85e355e5b11924ab1bc9b06d271a3"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OV4M5yKvu5rrqELnn2rhMt0p0CAM+4larS3OhEJdnIfHCkYl1sEhEwjK7yw9nWPzlu2s50fBYp4QbpZmwOrLBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-01T12:59:57.318244Z","bundle_sha256":"c40a539e585b9181df88db088528495b9404e8a908cee1bc1ede3e2a4dea9411"}}