{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:HXKG5UAH7CYF2C363LHHIC2FFH","short_pith_number":"pith:HXKG5UAH","canonical_record":{"source":{"id":"1908.00706","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-08-02T05:37:03Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"606c26bcc9282bf6510c89b075685274c81597907d764a8e031078a5f2b00fbf","abstract_canon_sha256":"0929ab5e706576f1152547f783aebf931595636bca150d1ca1f07dd5e81e9d01"},"schema_version":"1.0"},"canonical_sha256":"3dd46ed007f8b05d0b7edace740b4529e90662b5bc3617cc2ecb711aa017010d","source":{"kind":"arxiv","id":"1908.00706","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1908.00706","created_at":"2026-07-05T00:28:11Z"},{"alias_kind":"arxiv_version","alias_value":"1908.00706v2","created_at":"2026-07-05T00:28:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1908.00706","created_at":"2026-07-05T00:28:11Z"},{"alias_kind":"pith_short_12","alias_value":"HXKG5UAH7CYF","created_at":"2026-07-05T00:28:11Z"},{"alias_kind":"pith_short_16","alias_value":"HXKG5UAH7CYF2C36","created_at":"2026-07-05T00:28:11Z"},{"alias_kind":"pith_short_8","alias_value":"HXKG5UAH","created_at":"2026-07-05T00:28:11Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:HXKG5UAH7CYF2C363LHHIC2FFH","target":"record","payload":{"canonical_record":{"source":{"id":"1908.00706","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-08-02T05:37:03Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"606c26bcc9282bf6510c89b075685274c81597907d764a8e031078a5f2b00fbf","abstract_canon_sha256":"0929ab5e706576f1152547f783aebf931595636bca150d1ca1f07dd5e81e9d01"},"schema_version":"1.0"},"canonical_sha256":"3dd46ed007f8b05d0b7edace740b4529e90662b5bc3617cc2ecb711aa017010d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:28:11.304803Z","signature_b64":"FD/okFD+LDwChYrEdZuIyc/34NlM4GVgTMay69koIHEIhbAG7b50/BfSVBbLUF+W2mwnMhOS2grWuJ03DaCYCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3dd46ed007f8b05d0b7edace740b4529e90662b5bc3617cc2ecb711aa017010d","last_reissued_at":"2026-07-05T00:28:11.304215Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:28:11.304215Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1908.00706","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":"2026-07-05T00:28:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3I884JIFAIaKAsCgO83The1xCdDAm3YHHInwneeabhwafuckfSE3dg+y4Kg+f8LSOYXWOmGPSUb4VvoGtpKJAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-31T14:24:49.999892Z"},"content_sha256":"be26558534a9b7a194607cc3fdcb49927c0a00e76a275b21f8e2fd5943639b56","schema_version":"1.0","event_id":"sha256:be26558534a9b7a194607cc3fdcb49927c0a00e76a275b21f8e2fd5943639b56"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:HXKG5UAH7CYF2C363LHHIC2FFH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"AdvGAN++ : Harnessing latent layers for adversary generation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Puneet Mangla, Sakshi Varshney, Surgan Jandial, Vineeth N Balasubramanian","submitted_at":"2019-08-02T05:37:03Z","abstract_excerpt":"Adversarial examples are fabricated examples, indistinguishable from the original image that mislead neural networks and drastically lower their performance. Recently proposed AdvGAN, a GAN based approach, takes input image as a prior for generating adversaries to target a model. In this work, we show how latent features can serve as better priors than input images for adversary generation by proposing AdvGAN++, a version of AdvGAN that achieves higher attack rates than AdvGAN and at the same time generates perceptually realistic images on MNIST and CIFAR-10 datasets."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1908.00706","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/1908.00706/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":"2026-07-05T00:28:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"W9qY4p3LdySKi/lCEihUmU4e23AxCpH3qtIQ51c7TMDpamSHEv0QO1H5qp7KDNjyBufz1SvsbSE5GmlpzDeJDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-31T14:24:50.000418Z"},"content_sha256":"3cdb56f982ac3bed072259917259e01a9a16a1d6115fa5a735597063cf0a3825","schema_version":"1.0","event_id":"sha256:3cdb56f982ac3bed072259917259e01a9a16a1d6115fa5a735597063cf0a3825"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HXKG5UAH7CYF2C363LHHIC2FFH/bundle.json","state_url":"https://pith.science/pith/HXKG5UAH7CYF2C363LHHIC2FFH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HXKG5UAH7CYF2C363LHHIC2FFH/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":"2026-07-31T14:24:50Z","links":{"resolver":"https://pith.science/pith/HXKG5UAH7CYF2C363LHHIC2FFH","bundle":"https://pith.science/pith/HXKG5UAH7CYF2C363LHHIC2FFH/bundle.json","state":"https://pith.science/pith/HXKG5UAH7CYF2C363LHHIC2FFH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HXKG5UAH7CYF2C363LHHIC2FFH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:HXKG5UAH7CYF2C363LHHIC2FFH","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":"0929ab5e706576f1152547f783aebf931595636bca150d1ca1f07dd5e81e9d01","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-08-02T05:37:03Z","title_canon_sha256":"606c26bcc9282bf6510c89b075685274c81597907d764a8e031078a5f2b00fbf"},"schema_version":"1.0","source":{"id":"1908.00706","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1908.00706","created_at":"2026-07-05T00:28:11Z"},{"alias_kind":"arxiv_version","alias_value":"1908.00706v2","created_at":"2026-07-05T00:28:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1908.00706","created_at":"2026-07-05T00:28:11Z"},{"alias_kind":"pith_short_12","alias_value":"HXKG5UAH7CYF","created_at":"2026-07-05T00:28:11Z"},{"alias_kind":"pith_short_16","alias_value":"HXKG5UAH7CYF2C36","created_at":"2026-07-05T00:28:11Z"},{"alias_kind":"pith_short_8","alias_value":"HXKG5UAH","created_at":"2026-07-05T00:28:11Z"}],"graph_snapshots":[{"event_id":"sha256:3cdb56f982ac3bed072259917259e01a9a16a1d6115fa5a735597063cf0a3825","target":"graph","created_at":"2026-07-05T00:28:11Z","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/1908.00706/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Adversarial examples are fabricated examples, indistinguishable from the original image that mislead neural networks and drastically lower their performance. Recently proposed AdvGAN, a GAN based approach, takes input image as a prior for generating adversaries to target a model. In this work, we show how latent features can serve as better priors than input images for adversary generation by proposing AdvGAN++, a version of AdvGAN that achieves higher attack rates than AdvGAN and at the same time generates perceptually realistic images on MNIST and CIFAR-10 datasets.","authors_text":"Puneet Mangla, Sakshi Varshney, Surgan Jandial, Vineeth N Balasubramanian","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-08-02T05:37:03Z","title":"AdvGAN++ : Harnessing latent layers for adversary generation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1908.00706","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:be26558534a9b7a194607cc3fdcb49927c0a00e76a275b21f8e2fd5943639b56","target":"record","created_at":"2026-07-05T00:28:11Z","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":"0929ab5e706576f1152547f783aebf931595636bca150d1ca1f07dd5e81e9d01","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-08-02T05:37:03Z","title_canon_sha256":"606c26bcc9282bf6510c89b075685274c81597907d764a8e031078a5f2b00fbf"},"schema_version":"1.0","source":{"id":"1908.00706","kind":"arxiv","version":2}},"canonical_sha256":"3dd46ed007f8b05d0b7edace740b4529e90662b5bc3617cc2ecb711aa017010d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3dd46ed007f8b05d0b7edace740b4529e90662b5bc3617cc2ecb711aa017010d","first_computed_at":"2026-07-05T00:28:11.304215Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:28:11.304215Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"FD/okFD+LDwChYrEdZuIyc/34NlM4GVgTMay69koIHEIhbAG7b50/BfSVBbLUF+W2mwnMhOS2grWuJ03DaCYCw==","signature_status":"signed_v1","signed_at":"2026-07-05T00:28:11.304803Z","signed_message":"canonical_sha256_bytes"},"source_id":"1908.00706","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:be26558534a9b7a194607cc3fdcb49927c0a00e76a275b21f8e2fd5943639b56","sha256:3cdb56f982ac3bed072259917259e01a9a16a1d6115fa5a735597063cf0a3825"],"state_sha256":"56abcd8831a41ebc32075d6d0e5db61f26aa9ede0f38e877c13ecdbecb678139"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gxXdrtAXbZZjzsRJhnhS23N/Lr4FD10NIavKzz5P23dPlnR1dd18pfHl+hPUYQLHGEnnO7znPX5NmaDcgrYQBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-31T14:24:50.005519Z","bundle_sha256":"6d279cf80328efee09cb47ad49502049546e2ab3fd58a0efe5e3fd5a7ee1cd44"}}