{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:ELVS7EHUGJSSKNZ7N6E3LKSKBJ","short_pith_number":"pith:ELVS7EHU","canonical_record":{"source":{"id":"2408.11058","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2024-08-05T00:43:56Z","cross_cats_sorted":["cs.AI","cs.CL","cs.IR"],"title_canon_sha256":"2a57d6550ddba671fb2d9dad0a1066c32d9b96c330a10d9ca5042b5e6e645a21","abstract_canon_sha256":"2f7a326871293dd0e4e04e5153c978aaa93a1e69f2dc15ca5002d7302e91b4ec"},"schema_version":"1.0"},"canonical_sha256":"22eb2f90f4326525373f6f89b5aa4a0a5db439f1f11dc9cc8be24551b9a1deaf","source":{"kind":"arxiv","id":"2408.11058","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.11058","created_at":"2026-07-05T08:57:24Z"},{"alias_kind":"arxiv_version","alias_value":"2408.11058v1","created_at":"2026-07-05T08:57:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.11058","created_at":"2026-07-05T08:57:24Z"},{"alias_kind":"pith_short_12","alias_value":"ELVS7EHUGJSS","created_at":"2026-07-05T08:57:24Z"},{"alias_kind":"pith_short_16","alias_value":"ELVS7EHUGJSSKNZ7","created_at":"2026-07-05T08:57:24Z"},{"alias_kind":"pith_short_8","alias_value":"ELVS7EHU","created_at":"2026-07-05T08:57:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:ELVS7EHUGJSSKNZ7N6E3LKSKBJ","target":"record","payload":{"canonical_record":{"source":{"id":"2408.11058","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2024-08-05T00:43:56Z","cross_cats_sorted":["cs.AI","cs.CL","cs.IR"],"title_canon_sha256":"2a57d6550ddba671fb2d9dad0a1066c32d9b96c330a10d9ca5042b5e6e645a21","abstract_canon_sha256":"2f7a326871293dd0e4e04e5153c978aaa93a1e69f2dc15ca5002d7302e91b4ec"},"schema_version":"1.0"},"canonical_sha256":"22eb2f90f4326525373f6f89b5aa4a0a5db439f1f11dc9cc8be24551b9a1deaf","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:57:24.093985Z","signature_b64":"A41I6by0FZA55O0+zlTEaRmmqY6mqfr2vw5dfI7vjjf0yg1HWxsSIbRgc/Az7OXgojEWzd0cIYKP8E5u/4h9Cg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"22eb2f90f4326525373f6f89b5aa4a0a5db439f1f11dc9cc8be24551b9a1deaf","last_reissued_at":"2026-07-05T08:57:24.093481Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:57:24.093481Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2408.11058","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":"2026-07-05T08:57:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ap8MnYy18rKrY/OmYOhPK0rZqm60s/dCoeF6aCVcK5x6TiXMo0kkU3vFLIZL3IMqXu3AJyQwrSGKR0f7WQwJBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T18:15:38.768900Z"},"content_sha256":"c86fbe90700dbed7e6a9fc76000e466eeff16cddb45f7a766cbd9ca431142e8b","schema_version":"1.0","event_id":"sha256:c86fbe90700dbed7e6a9fc76000e466eeff16cddb45f7a766cbd9ca431142e8b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:ELVS7EHUGJSSKNZ7N6E3LKSKBJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"LLM Agents Improve Semantic Code Search","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.CL","cs.IR"],"primary_cat":"cs.SE","authors_text":"Aditya Dora (University of Illinois Urbana Champaign), Cisco), Ka Seng Sam (University of Illinois Urbana Champaign), Prabhat Singh (Cisco), Sarthak Jain (University of Illinois Urbana Champaign","submitted_at":"2024-08-05T00:43:56Z","abstract_excerpt":"Code Search is a key task that many programmers often have to perform while developing solutions to problems. Current methodologies suffer from an inability to perform accurately on prompts that contain some ambiguity or ones that require additional context relative to a code-base. We introduce the approach of using Retrieval Augmented Generation (RAG) powered agents to inject information into user prompts allowing for better inputs into embedding models. By utilizing RAG, agents enhance user queries with relevant details from GitHub repositories, making them more informative and contextually "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.11058","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/2408.11058/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":"2026-07-05T08:57:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yn1MdXN5rg52I44VAVkVIj/6YjC9wEVHCrayrNP0UJI5peYRety6QRdGht9u8AoGWQuT0QPSvajepNhX6QI+CQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T18:15:38.769896Z"},"content_sha256":"917018aed9361d1c94c76a64aaf923ecfc82ed87886002bb2a5f7a735daa62da","schema_version":"1.0","event_id":"sha256:917018aed9361d1c94c76a64aaf923ecfc82ed87886002bb2a5f7a735daa62da"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ELVS7EHUGJSSKNZ7N6E3LKSKBJ/bundle.json","state_url":"https://pith.science/pith/ELVS7EHUGJSSKNZ7N6E3LKSKBJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ELVS7EHUGJSSKNZ7N6E3LKSKBJ/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":"2026-08-18T18:15:38Z","links":{"resolver":"https://pith.science/pith/ELVS7EHUGJSSKNZ7N6E3LKSKBJ","bundle":"https://pith.science/pith/ELVS7EHUGJSSKNZ7N6E3LKSKBJ/bundle.json","state":"https://pith.science/pith/ELVS7EHUGJSSKNZ7N6E3LKSKBJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ELVS7EHUGJSSKNZ7N6E3LKSKBJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:ELVS7EHUGJSSKNZ7N6E3LKSKBJ","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":"2f7a326871293dd0e4e04e5153c978aaa93a1e69f2dc15ca5002d7302e91b4ec","cross_cats_sorted":["cs.AI","cs.CL","cs.IR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2024-08-05T00:43:56Z","title_canon_sha256":"2a57d6550ddba671fb2d9dad0a1066c32d9b96c330a10d9ca5042b5e6e645a21"},"schema_version":"1.0","source":{"id":"2408.11058","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.11058","created_at":"2026-07-05T08:57:24Z"},{"alias_kind":"arxiv_version","alias_value":"2408.11058v1","created_at":"2026-07-05T08:57:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.11058","created_at":"2026-07-05T08:57:24Z"},{"alias_kind":"pith_short_12","alias_value":"ELVS7EHUGJSS","created_at":"2026-07-05T08:57:24Z"},{"alias_kind":"pith_short_16","alias_value":"ELVS7EHUGJSSKNZ7","created_at":"2026-07-05T08:57:24Z"},{"alias_kind":"pith_short_8","alias_value":"ELVS7EHU","created_at":"2026-07-05T08:57:24Z"}],"graph_snapshots":[{"event_id":"sha256:917018aed9361d1c94c76a64aaf923ecfc82ed87886002bb2a5f7a735daa62da","target":"graph","created_at":"2026-07-05T08:57:24Z","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/2408.11058/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Code Search is a key task that many programmers often have to perform while developing solutions to problems. Current methodologies suffer from an inability to perform accurately on prompts that contain some ambiguity or ones that require additional context relative to a code-base. We introduce the approach of using Retrieval Augmented Generation (RAG) powered agents to inject information into user prompts allowing for better inputs into embedding models. By utilizing RAG, agents enhance user queries with relevant details from GitHub repositories, making them more informative and contextually ","authors_text":"Aditya Dora (University of Illinois Urbana Champaign), Cisco), Ka Seng Sam (University of Illinois Urbana Champaign), Prabhat Singh (Cisco), Sarthak Jain (University of Illinois Urbana Champaign","cross_cats":["cs.AI","cs.CL","cs.IR"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2024-08-05T00:43:56Z","title":"LLM Agents Improve Semantic Code Search"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.11058","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:c86fbe90700dbed7e6a9fc76000e466eeff16cddb45f7a766cbd9ca431142e8b","target":"record","created_at":"2026-07-05T08:57:24Z","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":"2f7a326871293dd0e4e04e5153c978aaa93a1e69f2dc15ca5002d7302e91b4ec","cross_cats_sorted":["cs.AI","cs.CL","cs.IR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2024-08-05T00:43:56Z","title_canon_sha256":"2a57d6550ddba671fb2d9dad0a1066c32d9b96c330a10d9ca5042b5e6e645a21"},"schema_version":"1.0","source":{"id":"2408.11058","kind":"arxiv","version":1}},"canonical_sha256":"22eb2f90f4326525373f6f89b5aa4a0a5db439f1f11dc9cc8be24551b9a1deaf","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"22eb2f90f4326525373f6f89b5aa4a0a5db439f1f11dc9cc8be24551b9a1deaf","first_computed_at":"2026-07-05T08:57:24.093481Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:57:24.093481Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"A41I6by0FZA55O0+zlTEaRmmqY6mqfr2vw5dfI7vjjf0yg1HWxsSIbRgc/Az7OXgojEWzd0cIYKP8E5u/4h9Cg==","signature_status":"signed_v1","signed_at":"2026-07-05T08:57:24.093985Z","signed_message":"canonical_sha256_bytes"},"source_id":"2408.11058","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c86fbe90700dbed7e6a9fc76000e466eeff16cddb45f7a766cbd9ca431142e8b","sha256:917018aed9361d1c94c76a64aaf923ecfc82ed87886002bb2a5f7a735daa62da"],"state_sha256":"6be84f47d0e39b6faeb386563b8505e07e10426ae4bf5c088af935a2cf5c9ec4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RvokWlIHERjfoHjtS0L83PsHOgQMB2wFQrPSW5EyLm/ouIQV+8hPhUu0/Y1doKYIWhZszwcajJISWjWtcDSVDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-18T18:15:38.778195Z","bundle_sha256":"53c0061b78088c1e10fb5784054e3fe6f9b9c2549e72dc61f90b715c99c6af86"}}