{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:DHA4TDJ7NO65Z2KWWF6Z7SSNUY","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":"cd68adc0f293a6c59ff16d2b81226e28d7f2b9f8b767ca84089d06c2e985c0e4","cross_cats_sorted":["cs.CR","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-06-07T15:37:00Z","title_canon_sha256":"e822ca7997975f697e764af09fa5684f2331a852d213b99bb9f6d785f7f14fdc"},"schema_version":"1.0","source":{"id":"2306.04528","kind":"arxiv","version":5}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2306.04528","created_at":"2026-07-05T08:44:09Z"},{"alias_kind":"arxiv_version","alias_value":"2306.04528v5","created_at":"2026-07-05T08:44:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2306.04528","created_at":"2026-07-05T08:44:09Z"},{"alias_kind":"pith_short_12","alias_value":"DHA4TDJ7NO65","created_at":"2026-07-05T08:44:09Z"},{"alias_kind":"pith_short_16","alias_value":"DHA4TDJ7NO65Z2KW","created_at":"2026-07-05T08:44:09Z"},{"alias_kind":"pith_short_8","alias_value":"DHA4TDJ7","created_at":"2026-07-05T08:44:09Z"}],"graph_snapshots":[{"event_id":"sha256:3921a1448a6a774de27f1fc271a0d2ba3da3ecc44e4f44bcb909c2bc4bcd3636","target":"graph","created_at":"2026-07-05T08:44:09Z","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/2306.04528/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The increasing reliance on Large Language Models (LLMs) across academia and industry necessitates a comprehensive understanding of their robustness to prompts. In response to this vital need, we introduce PromptRobust, a robustness benchmark designed to measure LLMs' resilience to adversarial prompts. This study uses a plethora of adversarial textual attacks targeting prompts across multiple levels: character, word, sentence, and semantic. The adversarial prompts, crafted to mimic plausible user errors like typos or synonyms, aim to evaluate how slight deviations can affect LLM outcomes while ","authors_text":"Hao Chen, Jiaheng Zhou, Jindong Wang, Kaijie Zhu, Linyi Yang, Neil Zhenqiang Gong, Wei Ye, Xing Xie, Yidong Wang, Yue Zhang, Zichen Wang","cross_cats":["cs.CR","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-06-07T15:37:00Z","title":"PromptRobust: Towards Evaluating the Robustness of Large Language Models on Adversarial Prompts"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2306.04528","kind":"arxiv","version":5},"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:d92350345680ea6b39b0088ff76712246a2997fbafd639ed1496fb52628fe02e","target":"record","created_at":"2026-07-05T08:44:09Z","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":"cd68adc0f293a6c59ff16d2b81226e28d7f2b9f8b767ca84089d06c2e985c0e4","cross_cats_sorted":["cs.CR","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-06-07T15:37:00Z","title_canon_sha256":"e822ca7997975f697e764af09fa5684f2331a852d213b99bb9f6d785f7f14fdc"},"schema_version":"1.0","source":{"id":"2306.04528","kind":"arxiv","version":5}},"canonical_sha256":"19c1c98d3f6bbddce956b17d9fca4da6201aca5f9516fa6bef9f2ebe4ae88713","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"19c1c98d3f6bbddce956b17d9fca4da6201aca5f9516fa6bef9f2ebe4ae88713","first_computed_at":"2026-07-05T08:44:09.080457Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:44:09.080457Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"T3swW72iFMg7ZcoJGwnHs/iomprZAwgqUHcrcpiIrz2E5p8XWYdiDIDsT4PRUenBcUpQZMZeRP1stFVEgCsCDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T08:44:09.080869Z","signed_message":"canonical_sha256_bytes"},"source_id":"2306.04528","source_kind":"arxiv","source_version":5}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d92350345680ea6b39b0088ff76712246a2997fbafd639ed1496fb52628fe02e","sha256:3921a1448a6a774de27f1fc271a0d2ba3da3ecc44e4f44bcb909c2bc4bcd3636"],"state_sha256":"4f0a0af17780876a6b8b1a5be896c369be1da6a09d2326f06f2b2a7dca1df494"}