{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:7IEWHSGXMINS6C7A4CJS5RKUCJ","short_pith_number":"pith:7IEWHSGX","canonical_record":{"source":{"id":"2307.07171","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-07-14T05:40:24Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"86635aa9cb531136354f556831fd3747d83205f978870ee665d2917a35b39dc3","abstract_canon_sha256":"21696e23377de45722ebc135163d74470fe8fcff349b80298135982058f14edc"},"schema_version":"1.0"},"canonical_sha256":"fa0963c8d7621b2f0be0e0932ec554127144174f70237db3550273957dab99f5","source":{"kind":"arxiv","id":"2307.07171","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2307.07171","created_at":"2026-07-05T06:30:52Z"},{"alias_kind":"arxiv_version","alias_value":"2307.07171v1","created_at":"2026-07-05T06:30:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2307.07171","created_at":"2026-07-05T06:30:52Z"},{"alias_kind":"pith_short_12","alias_value":"7IEWHSGXMINS","created_at":"2026-07-05T06:30:52Z"},{"alias_kind":"pith_short_16","alias_value":"7IEWHSGXMINS6C7A","created_at":"2026-07-05T06:30:52Z"},{"alias_kind":"pith_short_8","alias_value":"7IEWHSGX","created_at":"2026-07-05T06:30:52Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:7IEWHSGXMINS6C7A4CJS5RKUCJ","target":"record","payload":{"canonical_record":{"source":{"id":"2307.07171","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-07-14T05:40:24Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"86635aa9cb531136354f556831fd3747d83205f978870ee665d2917a35b39dc3","abstract_canon_sha256":"21696e23377de45722ebc135163d74470fe8fcff349b80298135982058f14edc"},"schema_version":"1.0"},"canonical_sha256":"fa0963c8d7621b2f0be0e0932ec554127144174f70237db3550273957dab99f5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:30:52.258645Z","signature_b64":"CBcYuSS+XC9gmRlgGXBGZgVicTlLszqTqUv7jeML//xWgB8K4wnzTTPIp6B06uQ12L2abPBScasOCUB+YLVfAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fa0963c8d7621b2f0be0e0932ec554127144174f70237db3550273957dab99f5","last_reissued_at":"2026-07-05T06:30:52.258132Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:30:52.258132Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2307.07171","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":"2026-07-05T06:30:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WEWUVzR4fgjMLr9dBm5/4PLJ4OHv4Fn5FveMaCWXQgTV5EQLGN9W7+q4vvJrNo5H6ejEWE2d4X3XDWisYYRnDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-09T05:56:57.247499Z"},"content_sha256":"44bbde5a03d121e5c042d03e08e2cee4050f80082889cfe215153388256827e0","schema_version":"1.0","event_id":"sha256:44bbde5a03d121e5c042d03e08e2cee4050f80082889cfe215153388256827e0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:7IEWHSGXMINS6C7A4CJS5RKUCJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Certified Robustness for Large Language Models with Self-Denoising","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CL","authors_text":"Bairu Hou, Guanhua Zhang, Qing Li, Shiyu Chang, Sijia Liu, Wenqi Fan, Yang Zhang, Zhen Zhang","submitted_at":"2023-07-14T05:40:24Z","abstract_excerpt":"Although large language models (LLMs) have achieved great success in vast real-world applications, their vulnerabilities towards noisy inputs have significantly limited their uses, especially in high-stake environments. In these contexts, it is crucial to ensure that every prediction made by large language models is stable, i.e., LLM predictions should be consistent given minor differences in the input. This largely falls into the study of certified robust LLMs, i.e., all predictions of LLM are certified to be correct in a local region around the input. Randomized smoothing has demonstrated gr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2307.07171","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/2307.07171/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":"2026-07-05T06:30:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AroyNuQzJ//EmLmuufX3ls9UJefYcvH+EgCw8XwW49oaK7s5na2jH/02VqJcwuiYWC3r/5zpF0Is4CqQrLUbBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-09T05:56:57.248384Z"},"content_sha256":"2bae2390557a31dba8dd3ab5f828e0bf3e09570aeb57ba51ec305d74f8df7fca","schema_version":"1.0","event_id":"sha256:2bae2390557a31dba8dd3ab5f828e0bf3e09570aeb57ba51ec305d74f8df7fca"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7IEWHSGXMINS6C7A4CJS5RKUCJ/bundle.json","state_url":"https://pith.science/pith/7IEWHSGXMINS6C7A4CJS5RKUCJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7IEWHSGXMINS6C7A4CJS5RKUCJ/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":"2026-07-09T05:56:57Z","links":{"resolver":"https://pith.science/pith/7IEWHSGXMINS6C7A4CJS5RKUCJ","bundle":"https://pith.science/pith/7IEWHSGXMINS6C7A4CJS5RKUCJ/bundle.json","state":"https://pith.science/pith/7IEWHSGXMINS6C7A4CJS5RKUCJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7IEWHSGXMINS6C7A4CJS5RKUCJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:7IEWHSGXMINS6C7A4CJS5RKUCJ","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":"21696e23377de45722ebc135163d74470fe8fcff349b80298135982058f14edc","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-07-14T05:40:24Z","title_canon_sha256":"86635aa9cb531136354f556831fd3747d83205f978870ee665d2917a35b39dc3"},"schema_version":"1.0","source":{"id":"2307.07171","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2307.07171","created_at":"2026-07-05T06:30:52Z"},{"alias_kind":"arxiv_version","alias_value":"2307.07171v1","created_at":"2026-07-05T06:30:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2307.07171","created_at":"2026-07-05T06:30:52Z"},{"alias_kind":"pith_short_12","alias_value":"7IEWHSGXMINS","created_at":"2026-07-05T06:30:52Z"},{"alias_kind":"pith_short_16","alias_value":"7IEWHSGXMINS6C7A","created_at":"2026-07-05T06:30:52Z"},{"alias_kind":"pith_short_8","alias_value":"7IEWHSGX","created_at":"2026-07-05T06:30:52Z"}],"graph_snapshots":[{"event_id":"sha256:2bae2390557a31dba8dd3ab5f828e0bf3e09570aeb57ba51ec305d74f8df7fca","target":"graph","created_at":"2026-07-05T06:30:52Z","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/2307.07171/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Although large language models (LLMs) have achieved great success in vast real-world applications, their vulnerabilities towards noisy inputs have significantly limited their uses, especially in high-stake environments. In these contexts, it is crucial to ensure that every prediction made by large language models is stable, i.e., LLM predictions should be consistent given minor differences in the input. This largely falls into the study of certified robust LLMs, i.e., all predictions of LLM are certified to be correct in a local region around the input. Randomized smoothing has demonstrated gr","authors_text":"Bairu Hou, Guanhua Zhang, Qing Li, Shiyu Chang, Sijia Liu, Wenqi Fan, Yang Zhang, Zhen Zhang","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-07-14T05:40:24Z","title":"Certified Robustness for Large Language Models with Self-Denoising"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2307.07171","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":"sha256:44bbde5a03d121e5c042d03e08e2cee4050f80082889cfe215153388256827e0","target":"record","created_at":"2026-07-05T06:30:52Z","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":"21696e23377de45722ebc135163d74470fe8fcff349b80298135982058f14edc","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-07-14T05:40:24Z","title_canon_sha256":"86635aa9cb531136354f556831fd3747d83205f978870ee665d2917a35b39dc3"},"schema_version":"1.0","source":{"id":"2307.07171","kind":"arxiv","version":1}},"canonical_sha256":"fa0963c8d7621b2f0be0e0932ec554127144174f70237db3550273957dab99f5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fa0963c8d7621b2f0be0e0932ec554127144174f70237db3550273957dab99f5","first_computed_at":"2026-07-05T06:30:52.258132Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:30:52.258132Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"CBcYuSS+XC9gmRlgGXBGZgVicTlLszqTqUv7jeML//xWgB8K4wnzTTPIp6B06uQ12L2abPBScasOCUB+YLVfAw==","signature_status":"signed_v1","signed_at":"2026-07-05T06:30:52.258645Z","signed_message":"canonical_sha256_bytes"},"source_id":"2307.07171","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:44bbde5a03d121e5c042d03e08e2cee4050f80082889cfe215153388256827e0","sha256:2bae2390557a31dba8dd3ab5f828e0bf3e09570aeb57ba51ec305d74f8df7fca"],"state_sha256":"03ac80b1a6dc7d2bd716c9a571886c544a911d379d09be50aff7d204074584ea"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jKfr3GpFN8/8zGRtVruBRD45+e5TJSIsf2RlyO/sTnAwiQx4PDRGbvTH0xndzdOKIxLersNkoeNjuGWv8iW1Bw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-09T05:56:57.251946Z","bundle_sha256":"d3062d72a85249e7af8e34efc3e9652f1e41039edc19a48fbc569d22c5901115"}}