{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:TIM7VIAGTTETVTXQYZBUJJV3S4","short_pith_number":"pith:TIM7VIAG","canonical_record":{"source":{"id":"2402.17081","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.IR","submitted_at":"2024-02-26T23:37:59Z","cross_cats_sorted":[],"title_canon_sha256":"df904631b623bf6c7adf4245835a4a074e3b340260ca63cf47920da2fc6d00dd","abstract_canon_sha256":"e23348623b6c965b952dfc0d5b55f6a378e707eef85372ef4bc314f37b064c5f"},"schema_version":"1.0"},"canonical_sha256":"9a19faa0069cc93acef0c64344a6bb973d126c193270d1ce972aa9b84d8d67d6","source":{"kind":"arxiv","id":"2402.17081","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.17081","created_at":"2026-07-05T07:49:42Z"},{"alias_kind":"arxiv_version","alias_value":"2402.17081v1","created_at":"2026-07-05T07:49:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.17081","created_at":"2026-07-05T07:49:42Z"},{"alias_kind":"pith_short_12","alias_value":"TIM7VIAGTTET","created_at":"2026-07-05T07:49:42Z"},{"alias_kind":"pith_short_16","alias_value":"TIM7VIAGTTETVTXQ","created_at":"2026-07-05T07:49:42Z"},{"alias_kind":"pith_short_8","alias_value":"TIM7VIAG","created_at":"2026-07-05T07:49:42Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:TIM7VIAGTTETVTXQYZBUJJV3S4","target":"record","payload":{"canonical_record":{"source":{"id":"2402.17081","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.IR","submitted_at":"2024-02-26T23:37:59Z","cross_cats_sorted":[],"title_canon_sha256":"df904631b623bf6c7adf4245835a4a074e3b340260ca63cf47920da2fc6d00dd","abstract_canon_sha256":"e23348623b6c965b952dfc0d5b55f6a378e707eef85372ef4bc314f37b064c5f"},"schema_version":"1.0"},"canonical_sha256":"9a19faa0069cc93acef0c64344a6bb973d126c193270d1ce972aa9b84d8d67d6","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:49:42.447473Z","signature_b64":"1NcuYvvzdLX4Qi1kHuvTMaZWtKJsvWn64m+1comZH8crcKplNsyvPVJAVRCYjSHW1ssCZWPqlmzRWRUJ77BsDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9a19faa0069cc93acef0c64344a6bb973d126c193270d1ce972aa9b84d8d67d6","last_reissued_at":"2026-07-05T07:49:42.447021Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:49:42.447021Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2402.17081","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":"2026-07-05T07:49:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"stKY3wk4Pm4LyU3CyU24oygoSKQuReIE8itxVQmkk7bl1Cu/I/dgyBxf9EKyL/XUlrfw+958tBcAcq5V9qjCAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T20:42:47.186847Z"},"content_sha256":"184fac30f8878dbc2875b68e6385e8e0b42a4f11c3485822c3cd61319509d901","schema_version":"1.0","event_id":"sha256:184fac30f8878dbc2875b68e6385e8e0b42a4f11c3485822c3cd61319509d901"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:TIM7VIAGTTETVTXQYZBUJJV3S4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Fine-tuning Enhanced RAG System with Quantized Influence Measure as AI Judge","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.IR","authors_text":"Keshav Rangan, Yiqiao Yin","submitted_at":"2024-02-26T23:37:59Z","abstract_excerpt":"This study presents an innovative enhancement to retrieval-augmented generation (RAG) systems by seamlessly integrating fine-tuned large language models (LLMs) with vector databases. This integration capitalizes on the combined strengths of structured data retrieval and the nuanced comprehension provided by advanced LLMs. Central to our approach are the LoRA and QLoRA methodologies, which stand at the forefront of model refinement through parameter-efficient fine-tuning and memory optimization. A novel feature of our research is the incorporation of user feedback directly into the training pro"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.17081","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/2402.17081/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":"2026-07-05T07:49:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"k0Jl0Ye+mHcZAXW5mOYaQzivSHdRInr+M8/4dMJSIjp4WSN+008H13TB73FMH+8xVBwTo/Ig3Zftdn90s3ueBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T20:42:47.187996Z"},"content_sha256":"7c9729227324e80dcf12680b9db283586d09c51d651b2f5c06a3c099ea855540","schema_version":"1.0","event_id":"sha256:7c9729227324e80dcf12680b9db283586d09c51d651b2f5c06a3c099ea855540"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TIM7VIAGTTETVTXQYZBUJJV3S4/bundle.json","state_url":"https://pith.science/pith/TIM7VIAGTTETVTXQYZBUJJV3S4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TIM7VIAGTTETVTXQYZBUJJV3S4/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":"2026-08-13T20:42:47Z","links":{"resolver":"https://pith.science/pith/TIM7VIAGTTETVTXQYZBUJJV3S4","bundle":"https://pith.science/pith/TIM7VIAGTTETVTXQYZBUJJV3S4/bundle.json","state":"https://pith.science/pith/TIM7VIAGTTETVTXQYZBUJJV3S4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TIM7VIAGTTETVTXQYZBUJJV3S4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:TIM7VIAGTTETVTXQYZBUJJV3S4","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":"e23348623b6c965b952dfc0d5b55f6a378e707eef85372ef4bc314f37b064c5f","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.IR","submitted_at":"2024-02-26T23:37:59Z","title_canon_sha256":"df904631b623bf6c7adf4245835a4a074e3b340260ca63cf47920da2fc6d00dd"},"schema_version":"1.0","source":{"id":"2402.17081","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.17081","created_at":"2026-07-05T07:49:42Z"},{"alias_kind":"arxiv_version","alias_value":"2402.17081v1","created_at":"2026-07-05T07:49:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.17081","created_at":"2026-07-05T07:49:42Z"},{"alias_kind":"pith_short_12","alias_value":"TIM7VIAGTTET","created_at":"2026-07-05T07:49:42Z"},{"alias_kind":"pith_short_16","alias_value":"TIM7VIAGTTETVTXQ","created_at":"2026-07-05T07:49:42Z"},{"alias_kind":"pith_short_8","alias_value":"TIM7VIAG","created_at":"2026-07-05T07:49:42Z"}],"graph_snapshots":[{"event_id":"sha256:7c9729227324e80dcf12680b9db283586d09c51d651b2f5c06a3c099ea855540","target":"graph","created_at":"2026-07-05T07:49:42Z","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/2402.17081/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This study presents an innovative enhancement to retrieval-augmented generation (RAG) systems by seamlessly integrating fine-tuned large language models (LLMs) with vector databases. This integration capitalizes on the combined strengths of structured data retrieval and the nuanced comprehension provided by advanced LLMs. Central to our approach are the LoRA and QLoRA methodologies, which stand at the forefront of model refinement through parameter-efficient fine-tuning and memory optimization. A novel feature of our research is the incorporation of user feedback directly into the training pro","authors_text":"Keshav Rangan, Yiqiao Yin","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.IR","submitted_at":"2024-02-26T23:37:59Z","title":"A Fine-tuning Enhanced RAG System with Quantized Influence Measure as AI Judge"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.17081","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":"sha256:184fac30f8878dbc2875b68e6385e8e0b42a4f11c3485822c3cd61319509d901","target":"record","created_at":"2026-07-05T07:49:42Z","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":"e23348623b6c965b952dfc0d5b55f6a378e707eef85372ef4bc314f37b064c5f","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.IR","submitted_at":"2024-02-26T23:37:59Z","title_canon_sha256":"df904631b623bf6c7adf4245835a4a074e3b340260ca63cf47920da2fc6d00dd"},"schema_version":"1.0","source":{"id":"2402.17081","kind":"arxiv","version":1}},"canonical_sha256":"9a19faa0069cc93acef0c64344a6bb973d126c193270d1ce972aa9b84d8d67d6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9a19faa0069cc93acef0c64344a6bb973d126c193270d1ce972aa9b84d8d67d6","first_computed_at":"2026-07-05T07:49:42.447021Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:49:42.447021Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"1NcuYvvzdLX4Qi1kHuvTMaZWtKJsvWn64m+1comZH8crcKplNsyvPVJAVRCYjSHW1ssCZWPqlmzRWRUJ77BsDA==","signature_status":"signed_v1","signed_at":"2026-07-05T07:49:42.447473Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.17081","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:184fac30f8878dbc2875b68e6385e8e0b42a4f11c3485822c3cd61319509d901","sha256:7c9729227324e80dcf12680b9db283586d09c51d651b2f5c06a3c099ea855540"],"state_sha256":"170e62e0aeefabcefb1db5e28f885624ef89f19de8b067998b1bc36148334e5c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wEqAAvzfn6zgyPfljobkwV+P4/S6M1ucTOlpUAZ4kClvh2i4fpumWTzd95Pe1QP2YOJVA2mNjb1BvnoJoJf4Dw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-13T20:42:47.202211Z","bundle_sha256":"a7b96e42469f99b613a560987c0ade5285fd288d2615d1ad97ae123ed6080b84"}}