{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:23CQA3ZOWI4E3IKTOUPK6VDERT","short_pith_number":"pith:23CQA3ZO","canonical_record":{"source":{"id":"2412.02563","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-12-03T16:52:06Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"fabbc524089178ac4c2017af7e1b44782c7b77ec98b44d7ba821933209263a0e","abstract_canon_sha256":"b87c67759f0d268283cfae0abbd3386172816c3741da03cd42425ac4c2546b2a"},"schema_version":"1.0"},"canonical_sha256":"d6c5006f2eb2384da153751eaf54648cde7a3deb42d19ff190dc907f8a641d1e","source":{"kind":"arxiv","id":"2412.02563","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.02563","created_at":"2026-07-05T09:43:51Z"},{"alias_kind":"arxiv_version","alias_value":"2412.02563v1","created_at":"2026-07-05T09:43:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.02563","created_at":"2026-07-05T09:43:51Z"},{"alias_kind":"pith_short_12","alias_value":"23CQA3ZOWI4E","created_at":"2026-07-05T09:43:51Z"},{"alias_kind":"pith_short_16","alias_value":"23CQA3ZOWI4E3IKT","created_at":"2026-07-05T09:43:51Z"},{"alias_kind":"pith_short_8","alias_value":"23CQA3ZO","created_at":"2026-07-05T09:43:51Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:23CQA3ZOWI4E3IKTOUPK6VDERT","target":"record","payload":{"canonical_record":{"source":{"id":"2412.02563","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-12-03T16:52:06Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"fabbc524089178ac4c2017af7e1b44782c7b77ec98b44d7ba821933209263a0e","abstract_canon_sha256":"b87c67759f0d268283cfae0abbd3386172816c3741da03cd42425ac4c2546b2a"},"schema_version":"1.0"},"canonical_sha256":"d6c5006f2eb2384da153751eaf54648cde7a3deb42d19ff190dc907f8a641d1e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:43:51.736218Z","signature_b64":"qmGz1vwTflLCAUUy1DQJ2dCtERXGxRp1VRvbz1ygOquDZZugR2zAn1u6VeohJv1e0tBBBWEW4x23QLqOC41uAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d6c5006f2eb2384da153751eaf54648cde7a3deb42d19ff190dc907f8a641d1e","last_reissued_at":"2026-07-05T09:43:51.735734Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:43:51.735734Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2412.02563","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":"2026-07-05T09:43:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rmhp0YayWr7JTTTCmtqEsrm+7x7+sLQRHzdX0tgts+uEJ7knB/e5bpg7DrAZtCdf5uni42aLcUOXd+VPKtOdAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T11:07:59.025237Z"},"content_sha256":"9503d4482544db0f88ea76a681dbfd5b3a14b50120d28aa607670ef840a77298","schema_version":"1.0","event_id":"sha256:9503d4482544db0f88ea76a681dbfd5b3a14b50120d28aa607670ef840a77298"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:23CQA3ZOWI4E3IKTOUPK6VDERT","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Semantic Tokens in Retrieval Augmented Generation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Joel Suro","submitted_at":"2024-12-03T16:52:06Z","abstract_excerpt":"Retrieval-Augmented Generation (RAG) architectures have recently garnered significant attention for their ability to improve truth grounding and coherence in natural language processing tasks. However, the reliability of RAG systems in producing accurate answers diminishes as the volume of data they access increases. Even with smaller datasets, these systems occasionally fail to address simple queries. This issue arises from their dependence on state-of-the-art large language models (LLMs), which can introduce uncertainty into the system's outputs. In this work, I propose a novel Comparative R"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.02563","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/2412.02563/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":"2026-07-05T09:43:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3OY/7I6gvHJyLKJrFWOuwD3DDY4HR/Z0yk910hwbNqyYEfY0H49t21yPXtIORUIMjq21nYdgMACtBLg1/9OaBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T11:07:59.025610Z"},"content_sha256":"08262dd9e03cac524b85594f2886071bad8c9f642fe2f9f37eaf2b0c00fa0d14","schema_version":"1.0","event_id":"sha256:08262dd9e03cac524b85594f2886071bad8c9f642fe2f9f37eaf2b0c00fa0d14"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/23CQA3ZOWI4E3IKTOUPK6VDERT/bundle.json","state_url":"https://pith.science/pith/23CQA3ZOWI4E3IKTOUPK6VDERT/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/23CQA3ZOWI4E3IKTOUPK6VDERT/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":"2026-08-18T11:07:59Z","links":{"resolver":"https://pith.science/pith/23CQA3ZOWI4E3IKTOUPK6VDERT","bundle":"https://pith.science/pith/23CQA3ZOWI4E3IKTOUPK6VDERT/bundle.json","state":"https://pith.science/pith/23CQA3ZOWI4E3IKTOUPK6VDERT/state.json","well_known_bundle":"https://pith.science/.well-known/pith/23CQA3ZOWI4E3IKTOUPK6VDERT/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:23CQA3ZOWI4E3IKTOUPK6VDERT","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":"b87c67759f0d268283cfae0abbd3386172816c3741da03cd42425ac4c2546b2a","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-12-03T16:52:06Z","title_canon_sha256":"fabbc524089178ac4c2017af7e1b44782c7b77ec98b44d7ba821933209263a0e"},"schema_version":"1.0","source":{"id":"2412.02563","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.02563","created_at":"2026-07-05T09:43:51Z"},{"alias_kind":"arxiv_version","alias_value":"2412.02563v1","created_at":"2026-07-05T09:43:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.02563","created_at":"2026-07-05T09:43:51Z"},{"alias_kind":"pith_short_12","alias_value":"23CQA3ZOWI4E","created_at":"2026-07-05T09:43:51Z"},{"alias_kind":"pith_short_16","alias_value":"23CQA3ZOWI4E3IKT","created_at":"2026-07-05T09:43:51Z"},{"alias_kind":"pith_short_8","alias_value":"23CQA3ZO","created_at":"2026-07-05T09:43:51Z"}],"graph_snapshots":[{"event_id":"sha256:08262dd9e03cac524b85594f2886071bad8c9f642fe2f9f37eaf2b0c00fa0d14","target":"graph","created_at":"2026-07-05T09:43:51Z","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/2412.02563/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Retrieval-Augmented Generation (RAG) architectures have recently garnered significant attention for their ability to improve truth grounding and coherence in natural language processing tasks. However, the reliability of RAG systems in producing accurate answers diminishes as the volume of data they access increases. Even with smaller datasets, these systems occasionally fail to address simple queries. This issue arises from their dependence on state-of-the-art large language models (LLMs), which can introduce uncertainty into the system's outputs. In this work, I propose a novel Comparative R","authors_text":"Joel Suro","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-12-03T16:52:06Z","title":"Semantic Tokens in Retrieval Augmented Generation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.02563","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":"sha256:9503d4482544db0f88ea76a681dbfd5b3a14b50120d28aa607670ef840a77298","target":"record","created_at":"2026-07-05T09:43:51Z","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":"b87c67759f0d268283cfae0abbd3386172816c3741da03cd42425ac4c2546b2a","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-12-03T16:52:06Z","title_canon_sha256":"fabbc524089178ac4c2017af7e1b44782c7b77ec98b44d7ba821933209263a0e"},"schema_version":"1.0","source":{"id":"2412.02563","kind":"arxiv","version":1}},"canonical_sha256":"d6c5006f2eb2384da153751eaf54648cde7a3deb42d19ff190dc907f8a641d1e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d6c5006f2eb2384da153751eaf54648cde7a3deb42d19ff190dc907f8a641d1e","first_computed_at":"2026-07-05T09:43:51.735734Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:43:51.735734Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"qmGz1vwTflLCAUUy1DQJ2dCtERXGxRp1VRvbz1ygOquDZZugR2zAn1u6VeohJv1e0tBBBWEW4x23QLqOC41uAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T09:43:51.736218Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.02563","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9503d4482544db0f88ea76a681dbfd5b3a14b50120d28aa607670ef840a77298","sha256:08262dd9e03cac524b85594f2886071bad8c9f642fe2f9f37eaf2b0c00fa0d14"],"state_sha256":"504137d847fab12da5c6943651447238d38f09d9e620927beb878acfa636d418"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WrCSy8u/o/IKyycZEHHNULOGuaGtFnzwFcNUQGBQjPI0heQrDIWdRP12ehUxLBoqqeNfuTz4Mjaac5cZq1rNCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-18T11:07:59.028139Z","bundle_sha256":"234394cad0d6555b404e46052ccf347f9da1beaf47a041253d45e18930fee694"}}