{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:M5J7DLXXRP5BY7FPIQPCJW2KPB","short_pith_number":"pith:M5J7DLXX","canonical_record":{"source":{"id":"2412.17011","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-12-22T13:21:15Z","cross_cats_sorted":[],"title_canon_sha256":"dc52ebefa24241b8bc60aff50083a1400af42462fb4dd887e34effeb368f418c","abstract_canon_sha256":"134040ec10cc500b57e0bdfe38580a4e3c39c808d98303ef33e87f3344b34e16"},"schema_version":"1.0"},"canonical_sha256":"6753f1aef78bfa1c7caf441e24db4a7848483b5059d1e84dedb60cf3d4ec0d60","source":{"kind":"arxiv","id":"2412.17011","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.17011","created_at":"2026-07-05T09:53:16Z"},{"alias_kind":"arxiv_version","alias_value":"2412.17011v1","created_at":"2026-07-05T09:53:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.17011","created_at":"2026-07-05T09:53:16Z"},{"alias_kind":"pith_short_12","alias_value":"M5J7DLXXRP5B","created_at":"2026-07-05T09:53:16Z"},{"alias_kind":"pith_short_16","alias_value":"M5J7DLXXRP5BY7FP","created_at":"2026-07-05T09:53:16Z"},{"alias_kind":"pith_short_8","alias_value":"M5J7DLXX","created_at":"2026-07-05T09:53:16Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:M5J7DLXXRP5BY7FPIQPCJW2KPB","target":"record","payload":{"canonical_record":{"source":{"id":"2412.17011","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-12-22T13:21:15Z","cross_cats_sorted":[],"title_canon_sha256":"dc52ebefa24241b8bc60aff50083a1400af42462fb4dd887e34effeb368f418c","abstract_canon_sha256":"134040ec10cc500b57e0bdfe38580a4e3c39c808d98303ef33e87f3344b34e16"},"schema_version":"1.0"},"canonical_sha256":"6753f1aef78bfa1c7caf441e24db4a7848483b5059d1e84dedb60cf3d4ec0d60","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:53:16.508931Z","signature_b64":"5A+wFehORHyuZZ/4OAkcxrDrZCRdSGq2I4CQ+s8Vix2kEIDb4ZY4ORNmjZQdWZIU1SIrPejxZL1npURuB6fLDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6753f1aef78bfa1c7caf441e24db4a7848483b5059d1e84dedb60cf3d4ec0d60","last_reissued_at":"2026-07-05T09:53:16.508377Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:53:16.508377Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2412.17011","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":"2026-07-05T09:53:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Xnd8DFPukfhl57AF6EbW1vdOEgMcg9dnZBhwHDnHi9ObeTiZxpvz1pgCvjNesTLRyMBm7Ngaa8xfNnQCobxfAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T12:29:33.559334Z"},"content_sha256":"4fa6ae3daaf9e81586562dcc6bc1521c25eef61e9871712ac5003bb574571425","schema_version":"1.0","event_id":"sha256:4fa6ae3daaf9e81586562dcc6bc1521c25eef61e9871712ac5003bb574571425"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:M5J7DLXXRP5BY7FPIQPCJW2KPB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Robustness of Large Language Models Against Adversarial Attacks","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Chuanqi Shi, Hang Zhang, Lun Wang, Shaoshuai Du, Yanxin Shen, Yixian Shen, Yiyi Tao","submitted_at":"2024-12-22T13:21:15Z","abstract_excerpt":"The increasing deployment of Large Language Models (LLMs) in various applications necessitates a rigorous evaluation of their robustness against adversarial attacks. In this paper, we present a comprehensive study on the robustness of GPT LLM family. We employ two distinct evaluation methods to assess their resilience. The first method introduce character-level text attack in input prompts, testing the models on three sentiment classification datasets: StanfordNLP/IMDB, Yelp Reviews, and SST-2. The second method involves using jailbreak prompts to challenge the safety mechanisms of the LLMs. O"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.17011","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/2412.17011/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":"2026-07-05T09:53:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"U/qWpwVqarwRJm4GhSdOiiI9Z5Y+hRYeuijL3fGitQxpFM8pS0xUMZR/LTrO42MFcYSMdPY9npXyhdmagjoiCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T12:29:33.559868Z"},"content_sha256":"3ef3a18c338f5405100ed7c1753a149486e9cee72371f7317b0bb01a4445958e","schema_version":"1.0","event_id":"sha256:3ef3a18c338f5405100ed7c1753a149486e9cee72371f7317b0bb01a4445958e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/M5J7DLXXRP5BY7FPIQPCJW2KPB/bundle.json","state_url":"https://pith.science/pith/M5J7DLXXRP5BY7FPIQPCJW2KPB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/M5J7DLXXRP5BY7FPIQPCJW2KPB/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":"2026-08-22T12:29:33Z","links":{"resolver":"https://pith.science/pith/M5J7DLXXRP5BY7FPIQPCJW2KPB","bundle":"https://pith.science/pith/M5J7DLXXRP5BY7FPIQPCJW2KPB/bundle.json","state":"https://pith.science/pith/M5J7DLXXRP5BY7FPIQPCJW2KPB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/M5J7DLXXRP5BY7FPIQPCJW2KPB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:M5J7DLXXRP5BY7FPIQPCJW2KPB","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":"134040ec10cc500b57e0bdfe38580a4e3c39c808d98303ef33e87f3344b34e16","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-12-22T13:21:15Z","title_canon_sha256":"dc52ebefa24241b8bc60aff50083a1400af42462fb4dd887e34effeb368f418c"},"schema_version":"1.0","source":{"id":"2412.17011","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.17011","created_at":"2026-07-05T09:53:16Z"},{"alias_kind":"arxiv_version","alias_value":"2412.17011v1","created_at":"2026-07-05T09:53:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.17011","created_at":"2026-07-05T09:53:16Z"},{"alias_kind":"pith_short_12","alias_value":"M5J7DLXXRP5B","created_at":"2026-07-05T09:53:16Z"},{"alias_kind":"pith_short_16","alias_value":"M5J7DLXXRP5BY7FP","created_at":"2026-07-05T09:53:16Z"},{"alias_kind":"pith_short_8","alias_value":"M5J7DLXX","created_at":"2026-07-05T09:53:16Z"}],"graph_snapshots":[{"event_id":"sha256:3ef3a18c338f5405100ed7c1753a149486e9cee72371f7317b0bb01a4445958e","target":"graph","created_at":"2026-07-05T09:53:16Z","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/2412.17011/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The increasing deployment of Large Language Models (LLMs) in various applications necessitates a rigorous evaluation of their robustness against adversarial attacks. In this paper, we present a comprehensive study on the robustness of GPT LLM family. We employ two distinct evaluation methods to assess their resilience. The first method introduce character-level text attack in input prompts, testing the models on three sentiment classification datasets: StanfordNLP/IMDB, Yelp Reviews, and SST-2. The second method involves using jailbreak prompts to challenge the safety mechanisms of the LLMs. O","authors_text":"Chuanqi Shi, Hang Zhang, Lun Wang, Shaoshuai Du, Yanxin Shen, Yixian Shen, Yiyi Tao","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-12-22T13:21:15Z","title":"Robustness of Large Language Models Against Adversarial Attacks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.17011","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":"sha256:4fa6ae3daaf9e81586562dcc6bc1521c25eef61e9871712ac5003bb574571425","target":"record","created_at":"2026-07-05T09:53:16Z","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":"134040ec10cc500b57e0bdfe38580a4e3c39c808d98303ef33e87f3344b34e16","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-12-22T13:21:15Z","title_canon_sha256":"dc52ebefa24241b8bc60aff50083a1400af42462fb4dd887e34effeb368f418c"},"schema_version":"1.0","source":{"id":"2412.17011","kind":"arxiv","version":1}},"canonical_sha256":"6753f1aef78bfa1c7caf441e24db4a7848483b5059d1e84dedb60cf3d4ec0d60","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6753f1aef78bfa1c7caf441e24db4a7848483b5059d1e84dedb60cf3d4ec0d60","first_computed_at":"2026-07-05T09:53:16.508377Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:53:16.508377Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"5A+wFehORHyuZZ/4OAkcxrDrZCRdSGq2I4CQ+s8Vix2kEIDb4ZY4ORNmjZQdWZIU1SIrPejxZL1npURuB6fLDA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:53:16.508931Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.17011","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4fa6ae3daaf9e81586562dcc6bc1521c25eef61e9871712ac5003bb574571425","sha256:3ef3a18c338f5405100ed7c1753a149486e9cee72371f7317b0bb01a4445958e"],"state_sha256":"9f5acbcac0744f052c822dd75a68688d9f29cdaa3b82f50da71323393d737b9c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FQvYmr30bZDi+h+St05To6aERfOBMVkgN3bF+2Owx0kL4I3F1yG/RR7nWykAQvklR0Pm2kCBI4ReDA4lstVSAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-22T12:29:33.564741Z","bundle_sha256":"5fcce43a7d0eee8a9006cb3af60f2d4721e9cde1a822e8735b6f9a16fe959a65"}}