{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:OC3KEQSTBNJRUQDVDMSCDSA4FJ","short_pith_number":"pith:OC3KEQST","schema_version":"1.0","canonical_sha256":"70b6a242530b531a40751b2421c81c2a5fd1222091519949a931e3d15a6e687c","source":{"kind":"arxiv","id":"2302.12351","version":1},"attestation_state":"computed","paper":{"title":"On the Hardness of Robustness Transfer: A Perspective from Rademacher Complexity over Symmetric Difference Hypothesis Space","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Junyuan Hong, Lingjuan Lyu, Mehrdad Mahdavi, Nidham Gazagnadou, Yuyang Deng","submitted_at":"2023-02-23T22:15:20Z","abstract_excerpt":"Recent studies demonstrated that the adversarially robust learning under $\\ell_\\infty$ attack is harder to generalize to different domains than standard domain adaptation. How to transfer robustness across different domains has been a key question in domain adaptation field. To investigate the fundamental difficulty behind adversarially robust domain adaptation (or robustness transfer), we propose to analyze a key complexity measure that controls the cross-domain generalization: the adversarial Rademacher complexity over {\\em symmetric difference hypothesis space} $\\mathcal{H} \\Delta \\mathcal{"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2302.12351","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-02-23T22:15:20Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"ccd56a8e8b37e476e120cbe5f2d1336efc6faa87a95858f1738b865bd9161f30","abstract_canon_sha256":"e2120bae4e3d23191a560b3374ee1da14361825de8b25081f196a6ceecefa911"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:45:08.690364Z","signature_b64":"SPaBt8i2VV25ZIsxGX6ZdhwFBcmVXJPBAVrHvuEMg9mQiM2mZuXg0OgC6wlrXJVICh6bzJHUcECMy7YxLsrsDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"70b6a242530b531a40751b2421c81c2a5fd1222091519949a931e3d15a6e687c","last_reissued_at":"2026-07-05T05:45:08.689957Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:45:08.689957Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"On the Hardness of Robustness Transfer: A Perspective from Rademacher Complexity over Symmetric Difference Hypothesis Space","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Junyuan Hong, Lingjuan Lyu, Mehrdad Mahdavi, Nidham Gazagnadou, Yuyang Deng","submitted_at":"2023-02-23T22:15:20Z","abstract_excerpt":"Recent studies demonstrated that the adversarially robust learning under $\\ell_\\infty$ attack is harder to generalize to different domains than standard domain adaptation. How to transfer robustness across different domains has been a key question in domain adaptation field. To investigate the fundamental difficulty behind adversarially robust domain adaptation (or robustness transfer), we propose to analyze a key complexity measure that controls the cross-domain generalization: the adversarial Rademacher complexity over {\\em symmetric difference hypothesis space} $\\mathcal{H} \\Delta \\mathcal{"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2302.12351","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/2302.12351/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2302.12351","created_at":"2026-07-05T05:45:08.690012+00:00"},{"alias_kind":"arxiv_version","alias_value":"2302.12351v1","created_at":"2026-07-05T05:45:08.690012+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2302.12351","created_at":"2026-07-05T05:45:08.690012+00:00"},{"alias_kind":"pith_short_12","alias_value":"OC3KEQSTBNJR","created_at":"2026-07-05T05:45:08.690012+00:00"},{"alias_kind":"pith_short_16","alias_value":"OC3KEQSTBNJRUQDV","created_at":"2026-07-05T05:45:08.690012+00:00"},{"alias_kind":"pith_short_8","alias_value":"OC3KEQST","created_at":"2026-07-05T05:45:08.690012+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/OC3KEQSTBNJRUQDVDMSCDSA4FJ","json":"https://pith.science/pith/OC3KEQSTBNJRUQDVDMSCDSA4FJ.json","graph_json":"https://pith.science/api/pith-number/OC3KEQSTBNJRUQDVDMSCDSA4FJ/graph.json","events_json":"https://pith.science/api/pith-number/OC3KEQSTBNJRUQDVDMSCDSA4FJ/events.json","paper":"https://pith.science/paper/OC3KEQST"},"agent_actions":{"view_html":"https://pith.science/pith/OC3KEQSTBNJRUQDVDMSCDSA4FJ","download_json":"https://pith.science/pith/OC3KEQSTBNJRUQDVDMSCDSA4FJ.json","view_paper":"https://pith.science/paper/OC3KEQST","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2302.12351&json=true","fetch_graph":"https://pith.science/api/pith-number/OC3KEQSTBNJRUQDVDMSCDSA4FJ/graph.json","fetch_events":"https://pith.science/api/pith-number/OC3KEQSTBNJRUQDVDMSCDSA4FJ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/OC3KEQSTBNJRUQDVDMSCDSA4FJ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/OC3KEQSTBNJRUQDVDMSCDSA4FJ/action/storage_attestation","attest_author":"https://pith.science/pith/OC3KEQSTBNJRUQDVDMSCDSA4FJ/action/author_attestation","sign_citation":"https://pith.science/pith/OC3KEQSTBNJRUQDVDMSCDSA4FJ/action/citation_signature","submit_replication":"https://pith.science/pith/OC3KEQSTBNJRUQDVDMSCDSA4FJ/action/replication_record"}},"created_at":"2026-07-05T05:45:08.690012+00:00","updated_at":"2026-07-05T05:45:08.690012+00:00"}