{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:PS2R3WOEZMTSPFBTEML7AGQMDA","short_pith_number":"pith:PS2R3WOE","canonical_record":{"source":{"id":"2506.03627","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-06-04T07:13:27Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"31231983b18aa209898fc95f4975eb175f8fce780e81f2453137dc7439e14e5c","abstract_canon_sha256":"562effe19d1f100dbc0af2d669b19afaedfc8b56c0a3af24d99e0afdfa3791a3"},"schema_version":"1.0"},"canonical_sha256":"7cb51dd9c4cb272794332317f01a0c1821ccd27681f8c746cb72e4d093cea0df","source":{"kind":"arxiv","id":"2506.03627","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.03627","created_at":"2026-05-27T01:04:48Z"},{"alias_kind":"arxiv_version","alias_value":"2506.03627v2","created_at":"2026-05-27T01:04:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.03627","created_at":"2026-05-27T01:04:48Z"},{"alias_kind":"pith_short_12","alias_value":"PS2R3WOEZMTS","created_at":"2026-05-27T01:04:48Z"},{"alias_kind":"pith_short_16","alias_value":"PS2R3WOEZMTSPFBT","created_at":"2026-05-27T01:04:48Z"},{"alias_kind":"pith_short_8","alias_value":"PS2R3WOE","created_at":"2026-05-27T01:04:48Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:PS2R3WOEZMTSPFBTEML7AGQMDA","target":"record","payload":{"canonical_record":{"source":{"id":"2506.03627","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-06-04T07:13:27Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"31231983b18aa209898fc95f4975eb175f8fce780e81f2453137dc7439e14e5c","abstract_canon_sha256":"562effe19d1f100dbc0af2d669b19afaedfc8b56c0a3af24d99e0afdfa3791a3"},"schema_version":"1.0"},"canonical_sha256":"7cb51dd9c4cb272794332317f01a0c1821ccd27681f8c746cb72e4d093cea0df","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-27T01:04:48.596238Z","signature_b64":"BCvuvSx7RAkYmpHncSrUFRJhhnCcW8PTXoum/FsQK0fPqJNrr5YMeD42rKBwQ60RC6xx3B6QFjvR7sO2V0dFCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7cb51dd9c4cb272794332317f01a0c1821ccd27681f8c746cb72e4d093cea0df","last_reissued_at":"2026-05-27T01:04:48.595412Z","signature_status":"signed_v1","first_computed_at":"2026-05-27T01:04:48.595412Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2506.03627","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-27T01:04:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ybpurQRM1Bcy4eB4bZ8Cs01S05AYLXChQ2XXd7JjpTg+zY1V6cvlmnv4BSuZj1gWJhSC9aRtLl6skXKasNk9Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-11T06:02:12.734221Z"},"content_sha256":"98132465b89bf363df300bf120d79c6efa59e23acb7eba3752581b159a29c8d2","schema_version":"1.0","event_id":"sha256:98132465b89bf363df300bf120d79c6efa59e23acb7eba3752581b159a29c8d2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:PS2R3WOEZMTSPFBTEML7AGQMDA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Robustness of Prompting: Enhancing Robustness of Large Language Models Against Prompting Attacks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Guowei Chu, Lei Sang, Li Ni, Lin Mu, Yiwen Zhang","submitted_at":"2025-06-04T07:13:27Z","abstract_excerpt":"Large Language Models (LLMs) have demonstrated remarkable performance across various tasks by effectively utilizing a prompting strategy. However, they are highly sensitive to input perturbations, such as typographical errors or slight character order errors, which can significantly impair their performance. Despite advances in prompting techniques such as Chain-of-Thought and automatic prompt generation, developing a prompting strategy that explicitly mitigates the negative impact of such perturbations remains an open challenge. To bridge this gap, we propose Robustness of Prompting (RoP), a "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.03627","kind":"arxiv","version":2},"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/2506.03627/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":"2026-05-27T01:04:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Uadajh9Z0C8oJRQzqQ6cvruySWDti++hZE0XX5+qMOcfIkmu80f3gIjv8V7v9rjblrt4EWnYhmCz9D3UZ8x3CQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-11T06:02:12.735047Z"},"content_sha256":"984bf6c3cac13ab8aef982feb113c3c71cd2575ce910c4d2ddc75c080f4f81b1","schema_version":"1.0","event_id":"sha256:984bf6c3cac13ab8aef982feb113c3c71cd2575ce910c4d2ddc75c080f4f81b1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/PS2R3WOEZMTSPFBTEML7AGQMDA/bundle.json","state_url":"https://pith.science/pith/PS2R3WOEZMTSPFBTEML7AGQMDA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/PS2R3WOEZMTSPFBTEML7AGQMDA/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":"2026-06-11T06:02:12Z","links":{"resolver":"https://pith.science/pith/PS2R3WOEZMTSPFBTEML7AGQMDA","bundle":"https://pith.science/pith/PS2R3WOEZMTSPFBTEML7AGQMDA/bundle.json","state":"https://pith.science/pith/PS2R3WOEZMTSPFBTEML7AGQMDA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/PS2R3WOEZMTSPFBTEML7AGQMDA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:PS2R3WOEZMTSPFBTEML7AGQMDA","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":"562effe19d1f100dbc0af2d669b19afaedfc8b56c0a3af24d99e0afdfa3791a3","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-06-04T07:13:27Z","title_canon_sha256":"31231983b18aa209898fc95f4975eb175f8fce780e81f2453137dc7439e14e5c"},"schema_version":"1.0","source":{"id":"2506.03627","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.03627","created_at":"2026-05-27T01:04:48Z"},{"alias_kind":"arxiv_version","alias_value":"2506.03627v2","created_at":"2026-05-27T01:04:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.03627","created_at":"2026-05-27T01:04:48Z"},{"alias_kind":"pith_short_12","alias_value":"PS2R3WOEZMTS","created_at":"2026-05-27T01:04:48Z"},{"alias_kind":"pith_short_16","alias_value":"PS2R3WOEZMTSPFBT","created_at":"2026-05-27T01:04:48Z"},{"alias_kind":"pith_short_8","alias_value":"PS2R3WOE","created_at":"2026-05-27T01:04:48Z"}],"graph_snapshots":[{"event_id":"sha256:984bf6c3cac13ab8aef982feb113c3c71cd2575ce910c4d2ddc75c080f4f81b1","target":"graph","created_at":"2026-05-27T01:04:48Z","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/2506.03627/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large Language Models (LLMs) have demonstrated remarkable performance across various tasks by effectively utilizing a prompting strategy. However, they are highly sensitive to input perturbations, such as typographical errors or slight character order errors, which can significantly impair their performance. Despite advances in prompting techniques such as Chain-of-Thought and automatic prompt generation, developing a prompting strategy that explicitly mitigates the negative impact of such perturbations remains an open challenge. To bridge this gap, we propose Robustness of Prompting (RoP), a ","authors_text":"Guowei Chu, Lei Sang, Li Ni, Lin Mu, Yiwen Zhang","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-06-04T07:13:27Z","title":"Robustness of Prompting: Enhancing Robustness of Large Language Models Against Prompting Attacks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.03627","kind":"arxiv","version":2},"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":"sha256:98132465b89bf363df300bf120d79c6efa59e23acb7eba3752581b159a29c8d2","target":"record","created_at":"2026-05-27T01:04:48Z","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":"562effe19d1f100dbc0af2d669b19afaedfc8b56c0a3af24d99e0afdfa3791a3","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-06-04T07:13:27Z","title_canon_sha256":"31231983b18aa209898fc95f4975eb175f8fce780e81f2453137dc7439e14e5c"},"schema_version":"1.0","source":{"id":"2506.03627","kind":"arxiv","version":2}},"canonical_sha256":"7cb51dd9c4cb272794332317f01a0c1821ccd27681f8c746cb72e4d093cea0df","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7cb51dd9c4cb272794332317f01a0c1821ccd27681f8c746cb72e4d093cea0df","first_computed_at":"2026-05-27T01:04:48.595412Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-27T01:04:48.595412Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"BCvuvSx7RAkYmpHncSrUFRJhhnCcW8PTXoum/FsQK0fPqJNrr5YMeD42rKBwQ60RC6xx3B6QFjvR7sO2V0dFCw==","signature_status":"signed_v1","signed_at":"2026-05-27T01:04:48.596238Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.03627","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:98132465b89bf363df300bf120d79c6efa59e23acb7eba3752581b159a29c8d2","sha256:984bf6c3cac13ab8aef982feb113c3c71cd2575ce910c4d2ddc75c080f4f81b1"],"state_sha256":"d0872bc4359cb9fad1b822f2b51064ff23f9d2d6f5aabad73b241248e25b9836"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"D9YZ/Iz2m3z5UHddfo9i7p1m1DY/4DLslV857by9ZOCR3ij+fSattoimG5iPOWO9PA5Ak+bpNGWOjUxJXoCLCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-11T06:02:12.739512Z","bundle_sha256":"fd7cda04cc5fa1218c86a6f66d7bfbbaaeb8f7135316b3a5b5d7807dfc3f10e5"}}