{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:EQWKHGHV4HYUNFO3JOA53UYRTQ","short_pith_number":"pith:EQWKHGHV","canonical_record":{"source":{"id":"2102.11584","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-02-23T09:47:45Z","cross_cats_sorted":[],"title_canon_sha256":"4e2c8d59cafe372926c4e675a2c6c5b8cb8ea731b288ec993af173ee38d389bb","abstract_canon_sha256":"08eca2564c3ecfca75064749bd57b512cb3af91f70099034c61019cdd2585e10"},"schema_version":"1.0"},"canonical_sha256":"242ca398f5e1f14695db4b81ddd3119c126d578e5e6dfaa144f5b2d04608ba0c","source":{"kind":"arxiv","id":"2102.11584","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2102.11584","created_at":"2026-07-05T02:17:52Z"},{"alias_kind":"arxiv_version","alias_value":"2102.11584v1","created_at":"2026-07-05T02:17:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2102.11584","created_at":"2026-07-05T02:17:52Z"},{"alias_kind":"pith_short_12","alias_value":"EQWKHGHV4HYU","created_at":"2026-07-05T02:17:52Z"},{"alias_kind":"pith_short_16","alias_value":"EQWKHGHV4HYUNFO3","created_at":"2026-07-05T02:17:52Z"},{"alias_kind":"pith_short_8","alias_value":"EQWKHGHV","created_at":"2026-07-05T02:17:52Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:EQWKHGHV4HYUNFO3JOA53UYRTQ","target":"record","payload":{"canonical_record":{"source":{"id":"2102.11584","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-02-23T09:47:45Z","cross_cats_sorted":[],"title_canon_sha256":"4e2c8d59cafe372926c4e675a2c6c5b8cb8ea731b288ec993af173ee38d389bb","abstract_canon_sha256":"08eca2564c3ecfca75064749bd57b512cb3af91f70099034c61019cdd2585e10"},"schema_version":"1.0"},"canonical_sha256":"242ca398f5e1f14695db4b81ddd3119c126d578e5e6dfaa144f5b2d04608ba0c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:17:52.429104Z","signature_b64":"UiUSCarBM7N4HaO70uHkAdz5HCEd6kczz3KvffIrS9WGJw59zEDaYQlTGmhJIRyEZvvL+hSslyxUfraP2vIbDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"242ca398f5e1f14695db4b81ddd3119c126d578e5e6dfaa144f5b2d04608ba0c","last_reissued_at":"2026-07-05T02:17:52.428691Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:17:52.428691Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2102.11584","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":"2026-07-05T02:17:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nzj7vCU17EF5HLal9X3lObW/f0N7yWkqIrpQiQWFscyOpGP2oX23/eNpy9F4aTQfMg2YwXBlrybN4E/4xuByBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T19:19:11.705018Z"},"content_sha256":"8d449773520e8fba27249a5ce9933a938240ceb37f947190408f879925b79543","schema_version":"1.0","event_id":"sha256:8d449773520e8fba27249a5ce9933a938240ceb37f947190408f879925b79543"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:EQWKHGHV4HYUNFO3JOA53UYRTQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Enhancing Model Robustness By Incorporating Adversarial Knowledge Into Semantic Representation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Hui Xue, Jinfeng Li, Rong Zhang, Shouling Ji, Tianyu Du, Xiangyu Liu","submitted_at":"2021-02-23T09:47:45Z","abstract_excerpt":"Despite that deep neural networks (DNNs) have achieved enormous success in many domains like natural language processing (NLP), they have also been proven to be vulnerable to maliciously generated adversarial examples. Such inherent vulnerability has threatened various real-world deployed DNNs-based applications. To strength the model robustness, several countermeasures have been proposed in the English NLP domain and obtained satisfactory performance. However, due to the unique language properties of Chinese, it is not trivial to extend existing defenses to the Chinese domain. Therefore, we p"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2102.11584","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/2102.11584/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":"2026-07-05T02:17:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8yvn63VN0IPUZ0B+LgqyEVywx+hwbitNN/yg2awQstmMy/TLdwEGAbiE/mUKlFGXmHBm+PonSzZVO9mSdruRDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T19:19:11.710102Z"},"content_sha256":"705479333920a8a39424d19505c64fabbe1abdf4f5997cb3a60f14dba46d9071","schema_version":"1.0","event_id":"sha256:705479333920a8a39424d19505c64fabbe1abdf4f5997cb3a60f14dba46d9071"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/EQWKHGHV4HYUNFO3JOA53UYRTQ/bundle.json","state_url":"https://pith.science/pith/EQWKHGHV4HYUNFO3JOA53UYRTQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/EQWKHGHV4HYUNFO3JOA53UYRTQ/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":"2026-08-13T19:19:11Z","links":{"resolver":"https://pith.science/pith/EQWKHGHV4HYUNFO3JOA53UYRTQ","bundle":"https://pith.science/pith/EQWKHGHV4HYUNFO3JOA53UYRTQ/bundle.json","state":"https://pith.science/pith/EQWKHGHV4HYUNFO3JOA53UYRTQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/EQWKHGHV4HYUNFO3JOA53UYRTQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:EQWKHGHV4HYUNFO3JOA53UYRTQ","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":"08eca2564c3ecfca75064749bd57b512cb3af91f70099034c61019cdd2585e10","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-02-23T09:47:45Z","title_canon_sha256":"4e2c8d59cafe372926c4e675a2c6c5b8cb8ea731b288ec993af173ee38d389bb"},"schema_version":"1.0","source":{"id":"2102.11584","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2102.11584","created_at":"2026-07-05T02:17:52Z"},{"alias_kind":"arxiv_version","alias_value":"2102.11584v1","created_at":"2026-07-05T02:17:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2102.11584","created_at":"2026-07-05T02:17:52Z"},{"alias_kind":"pith_short_12","alias_value":"EQWKHGHV4HYU","created_at":"2026-07-05T02:17:52Z"},{"alias_kind":"pith_short_16","alias_value":"EQWKHGHV4HYUNFO3","created_at":"2026-07-05T02:17:52Z"},{"alias_kind":"pith_short_8","alias_value":"EQWKHGHV","created_at":"2026-07-05T02:17:52Z"}],"graph_snapshots":[{"event_id":"sha256:705479333920a8a39424d19505c64fabbe1abdf4f5997cb3a60f14dba46d9071","target":"graph","created_at":"2026-07-05T02:17:52Z","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/2102.11584/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Despite that deep neural networks (DNNs) have achieved enormous success in many domains like natural language processing (NLP), they have also been proven to be vulnerable to maliciously generated adversarial examples. Such inherent vulnerability has threatened various real-world deployed DNNs-based applications. To strength the model robustness, several countermeasures have been proposed in the English NLP domain and obtained satisfactory performance. However, due to the unique language properties of Chinese, it is not trivial to extend existing defenses to the Chinese domain. Therefore, we p","authors_text":"Hui Xue, Jinfeng Li, Rong Zhang, Shouling Ji, Tianyu Du, Xiangyu Liu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-02-23T09:47:45Z","title":"Enhancing Model Robustness By Incorporating Adversarial Knowledge Into Semantic Representation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2102.11584","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":"sha256:8d449773520e8fba27249a5ce9933a938240ceb37f947190408f879925b79543","target":"record","created_at":"2026-07-05T02:17:52Z","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":"08eca2564c3ecfca75064749bd57b512cb3af91f70099034c61019cdd2585e10","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-02-23T09:47:45Z","title_canon_sha256":"4e2c8d59cafe372926c4e675a2c6c5b8cb8ea731b288ec993af173ee38d389bb"},"schema_version":"1.0","source":{"id":"2102.11584","kind":"arxiv","version":1}},"canonical_sha256":"242ca398f5e1f14695db4b81ddd3119c126d578e5e6dfaa144f5b2d04608ba0c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"242ca398f5e1f14695db4b81ddd3119c126d578e5e6dfaa144f5b2d04608ba0c","first_computed_at":"2026-07-05T02:17:52.428691Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:17:52.428691Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"UiUSCarBM7N4HaO70uHkAdz5HCEd6kczz3KvffIrS9WGJw59zEDaYQlTGmhJIRyEZvvL+hSslyxUfraP2vIbDA==","signature_status":"signed_v1","signed_at":"2026-07-05T02:17:52.429104Z","signed_message":"canonical_sha256_bytes"},"source_id":"2102.11584","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8d449773520e8fba27249a5ce9933a938240ceb37f947190408f879925b79543","sha256:705479333920a8a39424d19505c64fabbe1abdf4f5997cb3a60f14dba46d9071"],"state_sha256":"d7dc58db3dca95c3608eff285cfdcebb765add5ac91b025f0b9bb74492fd5755"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RW58cc1H2KlVS1Xe899kgVTU01qWRQz2mqYkyACDWXeQx+jLjcBjN40xYRY5pmhcRqtckKheS28FfzBWAAv3CA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-13T19:19:11.798615Z","bundle_sha256":"8b2b119f1d1b2a9643f2fe68ccaea2b58c0c9ad696ba59ba33fa7b6942ebe58f"}}