{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:3PEHNHI7GWOP3H6RSQ7PIZGKVV","short_pith_number":"pith:3PEHNHI7","canonical_record":{"source":{"id":"2507.21992","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-07-29T16:43:54Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"a64e205fc923156fc8451d29f564ea1c104ad065cf4ad44facaa2e7cd6b99f40","abstract_canon_sha256":"e823c808c0ea597ab6b7651960e2a92d69d73ceff82c7eb3bfbeb2adcdfaeafa"},"schema_version":"1.0"},"canonical_sha256":"dbc8769d1f359cfd9fd1943ef464caad4ae96c81a98055413f98de65ee8d5b31","source":{"kind":"arxiv","id":"2507.21992","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.21992","created_at":"2026-07-05T11:45:11Z"},{"alias_kind":"arxiv_version","alias_value":"2507.21992v1","created_at":"2026-07-05T11:45:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.21992","created_at":"2026-07-05T11:45:11Z"},{"alias_kind":"pith_short_12","alias_value":"3PEHNHI7GWOP","created_at":"2026-07-05T11:45:11Z"},{"alias_kind":"pith_short_16","alias_value":"3PEHNHI7GWOP3H6R","created_at":"2026-07-05T11:45:11Z"},{"alias_kind":"pith_short_8","alias_value":"3PEHNHI7","created_at":"2026-07-05T11:45:11Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:3PEHNHI7GWOP3H6RSQ7PIZGKVV","target":"record","payload":{"canonical_record":{"source":{"id":"2507.21992","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-07-29T16:43:54Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"a64e205fc923156fc8451d29f564ea1c104ad065cf4ad44facaa2e7cd6b99f40","abstract_canon_sha256":"e823c808c0ea597ab6b7651960e2a92d69d73ceff82c7eb3bfbeb2adcdfaeafa"},"schema_version":"1.0"},"canonical_sha256":"dbc8769d1f359cfd9fd1943ef464caad4ae96c81a98055413f98de65ee8d5b31","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:45:11.112023Z","signature_b64":"3moBJxoprM6UehnutZ0cKSfpRKgYCNT/n+5S375rlwWAeQa4Df7Epi496s7wDy/LCPTLqI6F81mf7EqdZXECDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"dbc8769d1f359cfd9fd1943ef464caad4ae96c81a98055413f98de65ee8d5b31","last_reissued_at":"2026-07-05T11:45:11.111595Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:45:11.111595Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2507.21992","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":"2026-07-05T11:45:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zfuoTP/U14kwIGVJU0Cf5SISRXRRPH/lNioecPNxq0YWDrZuVgXzDZKRvu1/XCt15eJRbIdw/dYXYk8adou9Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T16:12:17.464825Z"},"content_sha256":"18a9880fecc8d01785839a0722d3c15a7ac66c988851f86ba0d6f27985051cf0","schema_version":"1.0","event_id":"sha256:18a9880fecc8d01785839a0722d3c15a7ac66c988851f86ba0d6f27985051cf0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:3PEHNHI7GWOP3H6RSQ7PIZGKVV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Teach Me to Trick: Exploring Adversarial Transferability via Knowledge Distillation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Neha Bathuri, Shikshya Shiwakoti, Siddhartha Pradhan","submitted_at":"2025-07-29T16:43:54Z","abstract_excerpt":"We investigate whether knowledge distillation (KD) from multiple heterogeneous teacher models can enhance the generation of transferable adversarial examples. A lightweight student model is trained using two KD strategies: curriculum-based switching and joint optimization, with ResNet50 and DenseNet-161 as teachers. The trained student is then used to generate adversarial examples using FG, FGS, and PGD attacks, which are evaluated against a black-box target model (GoogLeNet). Our results show that student models distilled from multiple teachers achieve attack success rates comparable to ensem"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.21992","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/2507.21992/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":"2026-07-05T11:45:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VeDOXCDs+rk4gkEGCs37TkGYo9Jv58nWYwd84v/iaOdumTvbukMceEDMoxwDAtPPVZvHttuyLJ6StONeyueUCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T16:12:17.465232Z"},"content_sha256":"28a43eab80080b1c3b969eb22552c9c82eaaabb713c9efebc6c313b9e906a27d","schema_version":"1.0","event_id":"sha256:28a43eab80080b1c3b969eb22552c9c82eaaabb713c9efebc6c313b9e906a27d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3PEHNHI7GWOP3H6RSQ7PIZGKVV/bundle.json","state_url":"https://pith.science/pith/3PEHNHI7GWOP3H6RSQ7PIZGKVV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3PEHNHI7GWOP3H6RSQ7PIZGKVV/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":"2026-08-17T16:12:17Z","links":{"resolver":"https://pith.science/pith/3PEHNHI7GWOP3H6RSQ7PIZGKVV","bundle":"https://pith.science/pith/3PEHNHI7GWOP3H6RSQ7PIZGKVV/bundle.json","state":"https://pith.science/pith/3PEHNHI7GWOP3H6RSQ7PIZGKVV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3PEHNHI7GWOP3H6RSQ7PIZGKVV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:3PEHNHI7GWOP3H6RSQ7PIZGKVV","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":"e823c808c0ea597ab6b7651960e2a92d69d73ceff82c7eb3bfbeb2adcdfaeafa","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-07-29T16:43:54Z","title_canon_sha256":"a64e205fc923156fc8451d29f564ea1c104ad065cf4ad44facaa2e7cd6b99f40"},"schema_version":"1.0","source":{"id":"2507.21992","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.21992","created_at":"2026-07-05T11:45:11Z"},{"alias_kind":"arxiv_version","alias_value":"2507.21992v1","created_at":"2026-07-05T11:45:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.21992","created_at":"2026-07-05T11:45:11Z"},{"alias_kind":"pith_short_12","alias_value":"3PEHNHI7GWOP","created_at":"2026-07-05T11:45:11Z"},{"alias_kind":"pith_short_16","alias_value":"3PEHNHI7GWOP3H6R","created_at":"2026-07-05T11:45:11Z"},{"alias_kind":"pith_short_8","alias_value":"3PEHNHI7","created_at":"2026-07-05T11:45:11Z"}],"graph_snapshots":[{"event_id":"sha256:28a43eab80080b1c3b969eb22552c9c82eaaabb713c9efebc6c313b9e906a27d","target":"graph","created_at":"2026-07-05T11:45:11Z","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/2507.21992/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We investigate whether knowledge distillation (KD) from multiple heterogeneous teacher models can enhance the generation of transferable adversarial examples. A lightweight student model is trained using two KD strategies: curriculum-based switching and joint optimization, with ResNet50 and DenseNet-161 as teachers. The trained student is then used to generate adversarial examples using FG, FGS, and PGD attacks, which are evaluated against a black-box target model (GoogLeNet). Our results show that student models distilled from multiple teachers achieve attack success rates comparable to ensem","authors_text":"Neha Bathuri, Shikshya Shiwakoti, Siddhartha Pradhan","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-07-29T16:43:54Z","title":"Teach Me to Trick: Exploring Adversarial Transferability via Knowledge Distillation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.21992","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":"sha256:18a9880fecc8d01785839a0722d3c15a7ac66c988851f86ba0d6f27985051cf0","target":"record","created_at":"2026-07-05T11:45:11Z","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":"e823c808c0ea597ab6b7651960e2a92d69d73ceff82c7eb3bfbeb2adcdfaeafa","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-07-29T16:43:54Z","title_canon_sha256":"a64e205fc923156fc8451d29f564ea1c104ad065cf4ad44facaa2e7cd6b99f40"},"schema_version":"1.0","source":{"id":"2507.21992","kind":"arxiv","version":1}},"canonical_sha256":"dbc8769d1f359cfd9fd1943ef464caad4ae96c81a98055413f98de65ee8d5b31","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"dbc8769d1f359cfd9fd1943ef464caad4ae96c81a98055413f98de65ee8d5b31","first_computed_at":"2026-07-05T11:45:11.111595Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:45:11.111595Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"3moBJxoprM6UehnutZ0cKSfpRKgYCNT/n+5S375rlwWAeQa4Df7Epi496s7wDy/LCPTLqI6F81mf7EqdZXECDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:45:11.112023Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.21992","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:18a9880fecc8d01785839a0722d3c15a7ac66c988851f86ba0d6f27985051cf0","sha256:28a43eab80080b1c3b969eb22552c9c82eaaabb713c9efebc6c313b9e906a27d"],"state_sha256":"4ac5ea0bcfc637075413fb1f4c3799de0d860e4b6889831f61af6a25a87ef07c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"snU56M7+QsNQ5RgQF0tJOIP2aSAmSbKcwdD9+HDBq8bDZbFdsCxRbQEAsr4jp+7Xvuy8Grc3N8/X9nJlSNHlDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-17T16:12:17.467777Z","bundle_sha256":"1d2169abb2a0a93e138b78476791f63f927d1901464cc367a7ce7729c702e173"}}