{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:DEKCTRO7IVFHZNRGB5GG4IWDY7","short_pith_number":"pith:DEKCTRO7","canonical_record":{"source":{"id":"2607.00012","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2026-05-08T10:35:13Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"23d0bf02a59892f297963808caa7e0d112d2d5ff3c8c8e6e2721c7ca03ee2abb","abstract_canon_sha256":"cfc94cca79799b3545918935eb6b0901e551fa1506c84faf198edc06fa8622f5"},"schema_version":"1.0"},"canonical_sha256":"191429c5df454a7cb6260f4c6e22c3c7d8cafb8e6ef475eca291b6cb225a027b","source":{"kind":"arxiv","id":"2607.00012","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.00012","created_at":"2026-07-02T00:18:04Z"},{"alias_kind":"arxiv_version","alias_value":"2607.00012v1","created_at":"2026-07-02T00:18:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.00012","created_at":"2026-07-02T00:18:04Z"},{"alias_kind":"pith_short_12","alias_value":"DEKCTRO7IVFH","created_at":"2026-07-02T00:18:04Z"},{"alias_kind":"pith_short_16","alias_value":"DEKCTRO7IVFHZNRG","created_at":"2026-07-02T00:18:04Z"},{"alias_kind":"pith_short_8","alias_value":"DEKCTRO7","created_at":"2026-07-02T00:18:04Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:DEKCTRO7IVFHZNRGB5GG4IWDY7","target":"record","payload":{"canonical_record":{"source":{"id":"2607.00012","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2026-05-08T10:35:13Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"23d0bf02a59892f297963808caa7e0d112d2d5ff3c8c8e6e2721c7ca03ee2abb","abstract_canon_sha256":"cfc94cca79799b3545918935eb6b0901e551fa1506c84faf198edc06fa8622f5"},"schema_version":"1.0"},"canonical_sha256":"191429c5df454a7cb6260f4c6e22c3c7d8cafb8e6ef475eca291b6cb225a027b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-02T00:18:04.615749Z","signature_b64":"5xV6YFJSVVgjmFe4RIaFwt1Fw4jt1amKEBxgmjqrTAZKcXSOU/6jy+Np7H5p9m3E74SEMxuFjaW0WmtLFiFiCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"191429c5df454a7cb6260f4c6e22c3c7d8cafb8e6ef475eca291b6cb225a027b","last_reissued_at":"2026-07-02T00:18:04.615021Z","signature_status":"signed_v1","first_computed_at":"2026-07-02T00:18:04.615021Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2607.00012","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":"2026-07-02T00:18:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jF1rEBBVl55aGI+x0nrdRX4azuHevarO2uoHaRFgVOJXPXvsDdhCEtj0FDsWVb+kGhKtzEx/hbetiXV+6C3oBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-03T11:08:49.989236Z"},"content_sha256":"2f68de4883069704b03c4f0b62c228906c5359b7a83763e8b9e0e15023ee1245","schema_version":"1.0","event_id":"sha256:2f68de4883069704b03c4f0b62c228906c5359b7a83763e8b9e0e15023ee1245"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:DEKCTRO7IVFHZNRGB5GG4IWDY7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"PRA-RAG: Provably Robust Aggregation in Retrieval-Augmented Generation against Retrieval Corruption","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.IR","authors_text":"Chang Huo, Hao Luan, Jun Dai, Ping Chen, Xiaoyan Sun, Xue Tan, Yi Zheng, Yu Liu, Yunruo Zhang, Zhuyang Yu","submitted_at":"2026-05-08T10:35:13Z","abstract_excerpt":"Retrieval-Augmented Generation (RAG) enhances Large Language Models (LLMs) by incorporating external knowledge, effectively mitigating their inherent knowledge limitations. However, RAG remains vulnerable to poisoning attacks that manipulate retrieved texts to mislead model outputs. Existing defense mechanisms often lack theoretical robustness guarantees and perform unreliably when the LLM has limited knowledge of the retrieved content. In this work, we propose PRA-RAG, a provably robust retrieval aggregation algorithm designed to defend against poisoning attacks on retrieved texts. PRA-RAG sa"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.00012","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/2607.00012/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":"2026-07-02T00:18:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gTdzdtStcZasAegyRuLUN7Ja5JbnbolkEKCmQuXFpal/WoVk+HCxvOkCYnAmCUWz8pm9QGWlBLNnFMuqveUmAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-03T11:08:49.989631Z"},"content_sha256":"7589b9004ce460c36df15a2214e5adcc94fdfdd660646be569c3d433203c3045","schema_version":"1.0","event_id":"sha256:7589b9004ce460c36df15a2214e5adcc94fdfdd660646be569c3d433203c3045"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/DEKCTRO7IVFHZNRGB5GG4IWDY7/bundle.json","state_url":"https://pith.science/pith/DEKCTRO7IVFHZNRGB5GG4IWDY7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/DEKCTRO7IVFHZNRGB5GG4IWDY7/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":"2026-07-03T11:08:49Z","links":{"resolver":"https://pith.science/pith/DEKCTRO7IVFHZNRGB5GG4IWDY7","bundle":"https://pith.science/pith/DEKCTRO7IVFHZNRGB5GG4IWDY7/bundle.json","state":"https://pith.science/pith/DEKCTRO7IVFHZNRGB5GG4IWDY7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/DEKCTRO7IVFHZNRGB5GG4IWDY7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:DEKCTRO7IVFHZNRGB5GG4IWDY7","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":"cfc94cca79799b3545918935eb6b0901e551fa1506c84faf198edc06fa8622f5","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2026-05-08T10:35:13Z","title_canon_sha256":"23d0bf02a59892f297963808caa7e0d112d2d5ff3c8c8e6e2721c7ca03ee2abb"},"schema_version":"1.0","source":{"id":"2607.00012","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.00012","created_at":"2026-07-02T00:18:04Z"},{"alias_kind":"arxiv_version","alias_value":"2607.00012v1","created_at":"2026-07-02T00:18:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.00012","created_at":"2026-07-02T00:18:04Z"},{"alias_kind":"pith_short_12","alias_value":"DEKCTRO7IVFH","created_at":"2026-07-02T00:18:04Z"},{"alias_kind":"pith_short_16","alias_value":"DEKCTRO7IVFHZNRG","created_at":"2026-07-02T00:18:04Z"},{"alias_kind":"pith_short_8","alias_value":"DEKCTRO7","created_at":"2026-07-02T00:18:04Z"}],"graph_snapshots":[{"event_id":"sha256:7589b9004ce460c36df15a2214e5adcc94fdfdd660646be569c3d433203c3045","target":"graph","created_at":"2026-07-02T00:18:04Z","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/2607.00012/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Retrieval-Augmented Generation (RAG) enhances Large Language Models (LLMs) by incorporating external knowledge, effectively mitigating their inherent knowledge limitations. However, RAG remains vulnerable to poisoning attacks that manipulate retrieved texts to mislead model outputs. Existing defense mechanisms often lack theoretical robustness guarantees and perform unreliably when the LLM has limited knowledge of the retrieved content. In this work, we propose PRA-RAG, a provably robust retrieval aggregation algorithm designed to defend against poisoning attacks on retrieved texts. PRA-RAG sa","authors_text":"Chang Huo, Hao Luan, Jun Dai, Ping Chen, Xiaoyan Sun, Xue Tan, Yi Zheng, Yu Liu, Yunruo Zhang, Zhuyang Yu","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2026-05-08T10:35:13Z","title":"PRA-RAG: Provably Robust Aggregation in Retrieval-Augmented Generation against Retrieval Corruption"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.00012","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":"sha256:2f68de4883069704b03c4f0b62c228906c5359b7a83763e8b9e0e15023ee1245","target":"record","created_at":"2026-07-02T00:18:04Z","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":"cfc94cca79799b3545918935eb6b0901e551fa1506c84faf198edc06fa8622f5","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2026-05-08T10:35:13Z","title_canon_sha256":"23d0bf02a59892f297963808caa7e0d112d2d5ff3c8c8e6e2721c7ca03ee2abb"},"schema_version":"1.0","source":{"id":"2607.00012","kind":"arxiv","version":1}},"canonical_sha256":"191429c5df454a7cb6260f4c6e22c3c7d8cafb8e6ef475eca291b6cb225a027b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"191429c5df454a7cb6260f4c6e22c3c7d8cafb8e6ef475eca291b6cb225a027b","first_computed_at":"2026-07-02T00:18:04.615021Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-02T00:18:04.615021Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"5xV6YFJSVVgjmFe4RIaFwt1Fw4jt1amKEBxgmjqrTAZKcXSOU/6jy+Np7H5p9m3E74SEMxuFjaW0WmtLFiFiCg==","signature_status":"signed_v1","signed_at":"2026-07-02T00:18:04.615749Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.00012","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2f68de4883069704b03c4f0b62c228906c5359b7a83763e8b9e0e15023ee1245","sha256:7589b9004ce460c36df15a2214e5adcc94fdfdd660646be569c3d433203c3045"],"state_sha256":"650a22c3bd2ef8344cf5e4b8fabc65aa5baed0a6148046652ff3064cfcf276e9"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MIp7FNSN2ZEJ8i+P+CGa+HT0LVxp/OkhyrRuuXZYnOXs55ZawEv1CwCdfvl90Gz8A6ofqqhfk4kWmanmbKqfDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-03T11:08:49.991795Z","bundle_sha256":"179f215760ccbc71e28ec888ef5f485effb23b52d84aa127064a0deb24c02cea"}}