{"as_of":"2026-08-14T18:29:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:b69aa2129bdbb1216e9989b7c53aa999ef449445ca82a348ec56bd815226cd0d","coverage":[{"denominator":57,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":57,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T22:44:04.946360Z","state":"measured"},{"denominator":67,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":67,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-14T06:32:32.682623+00:00","state":"measured"},{"denominator":10,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":10,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-03T07:06:05.559182Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-03T20:28:55.951900Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"cited_work":{"arxiv_id":"2506.20963","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.20963","snapshot_observed_at":"2026-07-03T20:28:55.951900Z","title":"Erarag: Efficient and incremental retrieval augmented generation for growing corpora","venue":null,"work_id":"57b81cf6-d9e0-4569-b106-765fda44cb6c","year":2025},"citing_paper":{"arxiv_id":"2604.15676","last_updated":"2026-04-17T03:54:32Z","snapshot_observed_at":"2026-08-11T16:41:13.268420Z","submitted_at":"2026-04-17T03:54:32Z","title":"EvoRAG: Making Knowledge Graph-based RAG Automatically Evolve through Feedback-driven Backpropagation","version":1},"reference_index":102,"source":"pdf_text","source_observed_at":"2026-05-10T07:59:40.497067Z"},"links":{"cited_paper":"/paper/2506.20963","citing_paper":"/paper/2604.15676"},"observation_digest":"sha256:c2e324f2c05e1ea512825449f6187f697e94e632489c79bd4d83fd050b5bf259","observation_id":"0810a5c1-d984-4722-9e43-9d07423e0488","resolution":{"observed_at":"2026-05-10T08:02:25.166902Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"cited_work":{"arxiv_id":"2506.20963","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.20963","snapshot_observed_at":"2026-07-03T20:28:55.951900Z","title":"Erarag: Efficient and incremental retrieval augmented generation for growing corpora","venue":null,"work_id":"57b81cf6-d9e0-4569-b106-765fda44cb6c","year":2025},"citing_paper":{"arxiv_id":"2605.00505","last_updated":"2026-05-17T17:18:53Z","snapshot_observed_at":"2026-07-06T23:13:57.367556Z","submitted_at":"2026-05-01T08:30:52Z","title":"LLM-Oriented Information Retrieval: A Denoising-First Perspective","version":1},"reference_index":220,"source":"pdf_text","source_observed_at":"2026-05-09T18:54:06.144968Z"},"links":{"cited_paper":"/paper/2506.20963","citing_paper":"/paper/2605.00505"},"observation_digest":"sha256:542286e5397cd6f06b76b4e0631f8100c4a58d4717e59343ec7c35ffc3b78837","observation_id":"576f9127-bca3-4c6f-9e3e-fb5d04323ef3","resolution":{"observed_at":"2026-05-11T16:01:19.789665Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"cited_work":{"arxiv_id":"2506.20963","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.20963","snapshot_observed_at":"2026-07-03T20:28:55.951900Z","title":"Erarag: Efficient and incremental retrieval augmented generation for growing corpora","venue":null,"work_id":"57b81cf6-d9e0-4569-b106-765fda44cb6c","year":2025},"citing_paper":{"arxiv_id":"2605.00505","last_updated":"2026-05-17T17:18:53Z","snapshot_observed_at":"2026-07-06T23:13:57.367556Z","submitted_at":"2026-05-01T08:30:52Z","title":"LLM-Oriented Information Retrieval: A Denoising-First Perspective","version":2},"reference_index":230,"source":"pdf_text","source_observed_at":"2026-05-21T00:18:32.423103Z"},"links":{"cited_paper":"/paper/2506.20963","citing_paper":"/paper/2605.00505"},"observation_digest":"sha256:8606237df999b1de86742b741b832ee3772a54f674480c44b816614b58e8ac50","observation_id":"e8913526-603b-4e27-b7c6-96ec5fe04c2e","resolution":{"observed_at":"2026-05-21T00:19:16.438599Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"cited_work":{"arxiv_id":"2506.20963","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.20963","snapshot_observed_at":"2026-07-03T20:28:55.951900Z","title":"Erarag: Efficient and incremental retrieval augmented generation for growing corpora","venue":null,"work_id":"57b81cf6-d9e0-4569-b106-765fda44cb6c","year":2025},"citing_paper":{"arxiv_id":"2605.02452","last_updated":"2026-05-04T10:56:05Z","snapshot_observed_at":"2026-08-13T17:50:31.134934Z","submitted_at":"2026-05-04T10:56:05Z","title":"Position: How can Graphs Help Large Language Models?","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-05-08T18:48:03.257015Z"},"links":{"cited_paper":"/paper/2506.20963","citing_paper":"/paper/2605.02452"},"observation_digest":"sha256:369e91aadd9d7628d041affbc06f8b9391a2776e3991e46b6e5eb179a4449540","observation_id":"892f4d7f-2625-48ad-829a-ced658f762a0","resolution":{"observed_at":"2026-05-09T06:10:42.903826Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"cited_work":{"arxiv_id":"2506.20963","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.20963","snapshot_observed_at":"2026-07-03T20:28:55.951900Z","title":"Erarag: Efficient and incremental retrieval augmented generation for growing corpora","venue":null,"work_id":"57b81cf6-d9e0-4569-b106-765fda44cb6c","year":2025},"citing_paper":{"arxiv_id":"2605.07358","last_updated":"2026-05-26T05:21:04Z","snapshot_observed_at":"2026-07-06T23:19:46.018236Z","submitted_at":"2026-05-08T07:10:26Z","title":"A Comprehensive Survey on Agent Skills: Taxonomy, Techniques, and Applications","version":1},"reference_index":144,"source":"pdf_text","source_observed_at":"2026-05-11T01:47:39.926540Z"},"links":{"cited_paper":"/paper/2506.20963","citing_paper":"/paper/2605.07358"},"observation_digest":"sha256:5bc918f3a79704d879fa35be834ecb7965c171d63ace8d1e68642f142deeadd9","observation_id":"b4c900dc-5fbf-4985-9e11-84989e080ba7","resolution":{"observed_at":"2026-05-11T04:20:57.538087Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"cited_work":{"arxiv_id":"2506.20963","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.20963","snapshot_observed_at":"2026-07-03T20:28:55.951900Z","title":"Erarag: Efficient and incremental retrieval augmented generation for growing corpora","venue":null,"work_id":"57b81cf6-d9e0-4569-b106-765fda44cb6c","year":2025},"citing_paper":{"arxiv_id":"2605.07358","last_updated":"2026-05-26T05:21:04Z","snapshot_observed_at":"2026-07-06T23:19:46.018236Z","submitted_at":"2026-05-08T07:10:26Z","title":"A Comprehensive Survey on Agent Skills: Taxonomy, Techniques, and Applications","version":2},"reference_index":146,"source":"pdf_text","source_observed_at":"2026-05-20T23:15:44.550045Z"},"links":{"cited_paper":"/paper/2506.20963","citing_paper":"/paper/2605.07358"},"observation_digest":"sha256:588ffb4b7c8a2128d5c36954b1187ba3829941a4398bcb6bbee0b9a3ac651d7c","observation_id":"5fec0a0d-0925-42da-a551-71e7b0d3d483","resolution":{"observed_at":"2026-05-20T23:19:14.823326Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"cited_work":{"arxiv_id":"2506.20963","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.20963","snapshot_observed_at":"2026-07-03T20:28:55.951900Z","title":"Erarag: Efficient and incremental retrieval augmented generation for growing corpora","venue":null,"work_id":"57b81cf6-d9e0-4569-b106-765fda44cb6c","year":2025},"citing_paper":{"arxiv_id":"2605.07358","last_updated":"2026-05-26T05:21:04Z","snapshot_observed_at":"2026-07-06T23:19:46.018236Z","submitted_at":"2026-05-08T07:10:26Z","title":"A Comprehensive Survey on Agent Skills: Taxonomy, Techniques, and Applications","version":3},"reference_index":138,"source":"pdf_text","source_observed_at":"2026-06-30T23:23:42.883286Z"},"links":{"cited_paper":"/paper/2506.20963","citing_paper":"/paper/2605.07358"},"observation_digest":"sha256:1cf08ce0f2a3778bbd6691af0c584226a5b444fa2ea6f8bf9d1f37fd73a1a92f","observation_id":"fc88736d-4b32-4af4-92cd-937a35e6e776","resolution":{"observed_at":"2026-06-30T23:25:07.393247Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"cited_work":{"arxiv_id":"2506.20963","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.20963","snapshot_observed_at":"2026-07-03T20:28:55.951900Z","title":"Erarag: Efficient and incremental retrieval augmented generation for growing corpora","venue":null,"work_id":"57b81cf6-d9e0-4569-b106-765fda44cb6c","year":2025},"citing_paper":{"arxiv_id":"2606.00610","last_updated":"2026-05-30T08:18:53Z","snapshot_observed_at":"2026-08-14T14:55:36.035071Z","submitted_at":"2026-05-30T08:18:53Z","title":"MemGraphRAG: Memory-based Multi-Agent System for Graph Retrieval-Augmented Generation","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-06-28T18:20:43.092561Z"},"links":{"cited_paper":"/paper/2506.20963","citing_paper":"/paper/2606.00610"},"observation_digest":"sha256:cd9230c23b6f296d472f605c06349a26c8ba2a7289863e5ef2ed2fb77d76060a","observation_id":"853cb3a7-c004-4f80-914d-218a2743e6bc","resolution":{"observed_at":"2026-06-28T20:42:37.984526Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"cited_work":{"arxiv_id":"2506.20963","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.20963","snapshot_observed_at":"2026-07-03T20:28:55.951900Z","title":"Erarag: Efficient and incremental retrieval augmented generation for growing corpora","venue":null,"work_id":"57b81cf6-d9e0-4569-b106-765fda44cb6c","year":2025},"citing_paper":{"arxiv_id":"2606.18075","last_updated":"2026-06-16T15:44:10Z","snapshot_observed_at":"2026-07-06T23:53:36.096914Z","submitted_at":"2026-06-16T15:44:10Z","title":"A Unified Framework for Context-Aware and Relation-Aware Graph Retrieval-Augmented Generation","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-06-27T01:17:21.685012Z"},"links":{"cited_paper":"/paper/2506.20963","citing_paper":"/paper/2606.18075"},"observation_digest":"sha256:3b6f20abd9e503c6c88b4734f1c50991b856d63b038fc41da3911296c4789206","observation_id":"14aa0775-3f5b-4082-a936-3452a6ba8092","resolution":{"observed_at":"2026-07-03T20:28:55.953568Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.20963","snapshot_observed_at":"2026-08-03T07:06:05.559182Z","title":"arXiv preprint arXiv:2506.20963 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.29440","last_updated":"2026-07-31T14:07:12Z","snapshot_observed_at":"2026-08-08T03:55:00.361919Z","submitted_at":"2026-07-31T14:07:12Z","title":"Beyond Retrieval: Analytic Memory for Multimodal Agents","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-03T07:06:05.559182Z"},"links":{"cited_paper":"/paper/2506.20963","citing_paper":"/paper/2607.29440"},"observation_digest":"sha256:1841b4fffea60c3a7666cee4b86c819fe2c53309b8bcb30e37b8cf22b1f65ac0","observation_id":"be408f80-03ee-4265-855e-57ff85ce9385","resolution":{"observed_at":"2026-08-03T07:06:05.559182Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2506.20963/citation-record","integrity":"/paper/2506.20963/integrity","json":"/paper/2506.20963/citation-record.json","paper":"/paper/2506.20963"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2303.08774","last_updated":"2024-03-04T06:01:33Z","snapshot_observed_at":"2026-08-07T07:30:12.213965Z","submitted_at":"2023-03-15T17:15:04Z","title":"GPT-4 Technical Report","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.08774","snapshot_observed_at":"2026-08-06T22:43:59.653085Z","title":"Gpt-4 technical report","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T22:43:59.653085Z"},"links":{"cited_paper":"/paper/2303.08774","citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:6673a5f8ed8f979ffe7deb78271d18a558f8fc5e0be66cf396188c9bc60bc7fe","observation_id":"c0224478-3920-4f09-86c8-c4aaf1388ffa","resolution":{"observed_at":"2026-08-06T22:43:59.653085Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.15115","last_updated":"2025-01-03T02:18:21Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-19T17:56:09Z","title":"Qwen2.5 Technical Report","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.15115","snapshot_observed_at":"2026-08-06T22:43:59.730585Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T22:43:59.730585Z"},"links":{"cited_paper":"/paper/2412.15115","citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:577b7ffd690670577e56700e70234d1ef7a0c375786b86a543c4ab8586a82104","observation_id":"69c73ba9-5abe-40b8-b56b-3b45a1f6b082","resolution":{"observed_at":"2026-08-06T22:43:59.730585Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.13971","last_updated":"2023-02-27T17:11:15Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-02-27T17:11:15Z","title":"LLaMA: Open and Efficient Foundation Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.13971","snapshot_observed_at":"2026-08-06T22:43:59.848853Z","title":"Llama: Open and efficient foundation language models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T22:43:59.848853Z"},"links":{"cited_paper":"/paper/2302.13971","citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:7a410cecb928ad60754c59984f8e8e901189a24749099816813b57ab7da0d26c","observation_id":"9f4a143b-b385-4478-9f9b-0906f8b179b6","resolution":{"observed_at":"2026-08-06T22:43:59.848853Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:43:59.913811Z","title":"A comprehensive survey on process-oriented automatic text summarization with exploration of llm-based methods","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T22:43:59.913811Z"},"links":{"citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:bb01f785a2eed7bbcfedec122ca220a5db5e58ec24cd7a2f565c8b2d3fe4b96a","observation_id":"624f3545-e491-4725-bae5-bb42b485789a","resolution":{"observed_at":"2026-08-06T22:43:59.913811Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:43:59.956565Z","title":"Llm-based code generation method for golang compiler testing","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T22:43:59.956565Z"},"links":{"citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:e77a4f418a8f88b86e93faadf92080c1d571874be8f5a399b7932371a5808227","observation_id":"10fd2167-574a-4693-9d25-85d3c2451f45","resolution":{"observed_at":"2026-08-06T22:43:59.956565Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.18400","last_updated":"2025-03-20T16:37:17Z","snapshot_observed_at":"2026-08-13T00:19:49.230909Z","submitted_at":"2024-04-29T03:30:06Z","title":"LLM-SR: Scientific Equation Discovery via Programming with Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.18400","snapshot_observed_at":"2026-08-06T22:44:00.078070Z","title":"Llm-sr: Scientific equation discovery via pro- gramming with large language models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:00.078070Z"},"links":{"cited_paper":"/paper/2404.18400","citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:23d6d65514007b849278fb4a6d879430d6b8452fdf57a38a6a0f39477f6ec082","observation_id":"33d12c52-6780-4edc-ba04-77da5e147745","resolution":{"observed_at":"2026-08-06T22:44:00.078070Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.12399","last_updated":"2024-04-24T08:48:13Z","snapshot_observed_at":"2026-08-13T05:20:39.225920Z","submitted_at":"2023-11-21T07:22:48Z","title":"A Survey of Graph Meets Large Language Model: Progress and Future Directions","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.12399","snapshot_observed_at":"2026-08-06T22:44:00.189627Z","title":"A survey of graph meets large language model: Progress and future directions","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:00.189627Z"},"links":{"cited_paper":"/paper/2311.12399","citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:c9aae1ae92e3cf565b2e4f67438f35b91d3aafa5ad2b986ded51068943058ef3","observation_id":"52a04137-34b6-49e8-9179-0ff68e0e35ff","resolution":{"observed_at":"2026-08-06T22:44:00.189627Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:44:08.244475Z","title":"Beyond one-model-fits-all: A survey of domain specialization for large language models","venue":null,"work_id":"c3224691-70f9-4272-893b-fb03b4485256","year":2023},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:00.228567Z"},"links":{"citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:436e28187cec63cf58cf900325811a0433b0d45cc1895d0606cb36ea77cc9ddc","observation_id":"48ab8693-af50-4e92-9c7d-3947e5ddfa38","resolution":{"observed_at":"2026-08-06T22:44:08.304517Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:44:08.055320Z","title":"Openagi: When llm meets domain experts","venue":null,"work_id":"aa1253f1-ecf2-4c57-8121-a5066d1487fa","year":2023},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:00.260905Z"},"links":{"citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:12b31a2db05f7286000f353a12e08431a323eb8b5d11ce77923bbe5dccda3828","observation_id":"706a406d-970d-43a5-bb4c-0e02af7bab3f","resolution":{"observed_at":"2026-08-06T22:44:08.137988Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.05232","last_updated":"2024-11-19T12:42:45Z","snapshot_observed_at":"2026-07-06T16:45:07.733095Z","submitted_at":"2023-11-09T09:25:37Z","title":"A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.05232","snapshot_observed_at":"2026-08-06T22:44:00.339825Z","title":"A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:00.339825Z"},"links":{"cited_paper":"/paper/2311.05232","citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:9c8a8a6cc606d2702d7eb1d995bb914ba1dbc21f62fc391e41cdd827ac0c0a55","observation_id":"598ae65b-1105-4b92-b7cf-676e5de2e8c0","resolution":{"observed_at":"2026-08-06T22:44:00.339825Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:44:00.484315Z","title":"A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:00.484315Z"},"links":{"citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:c5ea1aa9133cdf5e00666dd0476d6c74fde5b6314a214eaeccd2a743c4d57ad3","observation_id":"71f0ecf2-3ae1-4e8d-b65b-27acc177a4c6","resolution":{"observed_at":"2026-08-06T22:44:00.484315Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.01469","last_updated":"2024-08-04T16:26:14Z","snapshot_observed_at":"2026-08-13T05:59:09.625642Z","submitted_at":"2023-10-02T17:01:56Z","title":"LLM Lies: Hallucinations are not Bugs, but Features as Adversarial Examples","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.01469","snapshot_observed_at":"2026-08-06T22:44:00.555656Z","title":"Llm lies: Hallucinations are not bugs, but features as adversarial examples","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:00.555656Z"},"links":{"cited_paper":"/paper/2310.01469","citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:12d3ca45195f3063534dd67f83e48241957ac3d3e9c3e27ebf853748f5ee02a1","observation_id":"b941c1e2-2f5d-4dd5-a024-b6b17658da2c","resolution":{"observed_at":"2026-08-06T22:44:00.555656Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.17193","last_updated":"2024-02-27T04:18:49Z","snapshot_observed_at":"2026-08-14T10:43:08.339405Z","submitted_at":"2024-02-27T04:18:49Z","title":"When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.17193","snapshot_observed_at":"2026-08-06T22:44:00.581983Z","title":"When scaling meets llm finetuning: The effect of data, model and finetuning method","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:00.581983Z"},"links":{"cited_paper":"/paper/2402.17193","citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:0b0b5b95a21d34bdd609efa2d8a2d1e78310ec77bb868d6e588dec5bdf3977cb","observation_id":"29f86ffd-cb2c-43b0-badf-3f835637a52e","resolution":{"observed_at":"2026-08-06T22:44:00.581983Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.05119","last_updated":"2024-07-14T18:14:57Z","snapshot_observed_at":"2026-08-13T04:27:54.647812Z","submitted_at":"2024-02-03T04:45:25Z","title":"A Closer Look at the Limitations of Instruction Tuning","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.05119","snapshot_observed_at":"2026-08-06T22:44:00.658347Z","title":"A closer look at the limitations of instruction tuning","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:00.658347Z"},"links":{"cited_paper":"/paper/2402.05119","citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:db1dbccf2e65e9b4051b1edd607d404154947abcab508de7ec5c91b5d479b3fa","observation_id":"9856e163-d5df-4e37-93df-8cf6a885b186","resolution":{"observed_at":"2026-08-06T22:44:00.658347Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:44:07.876482Z","title":"Getting it right: the limits of fine-tuning large language models","venue":null,"work_id":"82134dbd-59fd-4b78-86f6-90ecca96aa58","year":2024},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:00.803862Z"},"links":{"citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:bf1fa4347007e7255ceca7e881cff75d35853cdeb08a673198ddbabd1791d446","observation_id":"f3609128-1cd8-4902-85d5-d306b14313d1","resolution":{"observed_at":"2026-08-06T22:44:07.955893Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.10997","last_updated":"2024-03-27T09:16:57Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-12-18T07:47:33Z","title":"Retrieval-Augmented Generation for Large Language Models: A Survey","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.10997","snapshot_observed_at":"2026-08-06T22:44:00.904058Z","title":"Retrieval- augmented generation for large language models: A survey","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:00.904058Z"},"links":{"cited_paper":"/paper/2312.10997","citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:8ae082c5c9cb0f7e40a5cfa6a25dda62c31438dc0a9a4426153eef0269a9a8de","observation_id":"db4b8f53-7063-4a2e-98f3-b0362549feba","resolution":{"observed_at":"2026-08-06T22:44:00.904058Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:44:00.973994Z","title":"A survey on rag meeting llms: Towards retrieval-augmented large language models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:00.973994Z"},"links":{"citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:7c42fd5648bb2bcc5e0e5d7b31b215c8c1b06e86727f46af0ad2e27d0e8ec9da","observation_id":"07e15a44-8a4a-4258-b1b7-2aa3a3540519","resolution":{"observed_at":"2026-08-06T22:44:00.973994Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.13193","last_updated":"2026-05-19T15:04:52Z","snapshot_observed_at":"2026-08-12T20:18:42.397749Z","submitted_at":"2024-07-18T06:06:53Z","title":"Retrieval-Augmented Generation for Natural Language Processing: A Survey","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.13193","snapshot_observed_at":"2026-08-06T22:44:01.038308Z","title":"Retrieval- augmented generation for natural language processing: A survey","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:01.038308Z"},"links":{"cited_paper":"/paper/2407.13193","citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:0a68c86f39bb9b5976490f08dbdccd7d43dab77795b3e59e543a88ecda643cd5","observation_id":"0be9a3f5-2683-4659-895e-7919c8fcf3cf","resolution":{"observed_at":"2026-08-06T22:44:01.038308Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.19473","last_updated":"2024-06-21T08:26:36Z","snapshot_observed_at":"2026-08-13T05:27:55.126585Z","submitted_at":"2024-02-29T18:59:01Z","title":"Retrieval-Augmented Generation for AI-Generated Content: A Survey","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.19473","snapshot_observed_at":"2026-08-06T22:44:01.237558Z","title":"Retrieval-augmented generation for ai-generated content: A survey","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:01.237558Z"},"links":{"cited_paper":"/paper/2402.19473","citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:d3b0ad7e11c41b436803183731e2cb881ce7a4f8e1143193fb2b77805cc01d23","observation_id":"ea971c73-1678-47c7-9045-11e218c9c493","resolution":{"observed_at":"2026-08-06T22:44:01.237558Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.10102","last_updated":"2026-05-16T07:15:07Z","snapshot_observed_at":"2026-08-04T19:12:49.508911Z","submitted_at":"2024-09-16T09:06:44Z","title":"Trustworthiness in Retrieval-Augmented Generation Systems: A Survey","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.10102","snapshot_observed_at":"2026-08-06T22:44:01.292422Z","title":"Trustworthiness in retrieval-augmented generation systems: A survey","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:01.292422Z"},"links":{"cited_paper":"/paper/2409.10102","citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:461f7e0a2abcde64ed5f0cf2bc76c578ffb6374cb872bfac4f2eeb1d177bc426","observation_id":"e85e3748-9045-41e6-ae16-ef0dd60ed78a","resolution":{"observed_at":"2026-08-06T22:44:01.292422Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.14924","last_updated":"2024-09-23T11:20:20Z","snapshot_observed_at":"2026-08-13T05:59:29.635188Z","submitted_at":"2024-09-23T11:20:20Z","title":"Retrieval Augmented Generation (RAG) and Beyond: A Comprehensive Survey on How to Make your LLMs use External Data More Wisely","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.14924","snapshot_observed_at":"2026-08-06T22:44:01.343918Z","title":"Retrieval augmented generation (rag) and beyond: A comprehensive survey on how to make your llms use external data more wisely","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:01.343918Z"},"links":{"cited_paper":"/paper/2409.14924","citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:9f817c49255a4145c4bc4024813c217f13e6a1a6ce68f092f9591b73c2b88572","observation_id":"891f6ee1-e69b-45dc-8125-ca2b63f05d03","resolution":{"observed_at":"2026-08-06T22:44:01.343918Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.10446","last_updated":"2024-03-15T16:30:14Z","snapshot_observed_at":"2026-08-14T12:37:51.344845Z","submitted_at":"2024-03-15T16:30:14Z","title":"Enhancing LLM Factual Accuracy with RAG to Counter Hallucinations: A Case Study on Domain-Specific Queries in Private Knowledge-Bases","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.10446","snapshot_observed_at":"2026-08-06T22:44:01.502044Z","title":"Enhancing llm factual accuracy with rag to counter hallucinations: A case study on domain-specific queries in private knowledge-bases","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:01.502044Z"},"links":{"cited_paper":"/paper/2403.10446","citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:ca27fece849aacf9592bc6b536053e2bb44fbb8f139e5a4dcda0f6f8bf4dc974","observation_id":"31d7142f-67f4-4a27-bdbb-8ce83fe7b0a6","resolution":{"observed_at":"2026-08-06T22:44:01.502044Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.19463","last_updated":"2026-05-29T07:23:04Z","snapshot_observed_at":"2026-08-12T15:15:30.117060Z","submitted_at":"2024-11-29T04:25:31Z","title":"Understanding the Fundamental Design Decisions of Retrieval-Augmented Generation Systems","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.19463","snapshot_observed_at":"2026-08-06T22:44:01.593757Z","title":"Towards understanding retrieval accuracy and prompt quality in rag systems","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:01.593757Z"},"links":{"cited_paper":"/paper/2411.19463","citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:c595e3bf8bf46d91af8d8c041ac577a617fac2fac1a37205ae824c57f5608608","observation_id":"02430805-5554-4437-9138-9bf59d28754e","resolution":{"observed_at":"2026-08-06T22:44:01.593757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.02338","last_updated":"2024-10-04T14:59:04Z","snapshot_observed_at":"2026-08-14T07:06:03.634694Z","submitted_at":"2024-10-03T09:48:09Z","title":"How Much Can RAG Help the Reasoning of LLM?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.02338","snapshot_observed_at":"2026-08-06T22:44:01.630597Z","title":"How much can rag help the reasoning of llm? arXiv preprint arXiv:2410.02338 , 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:01.630597Z"},"links":{"cited_paper":"/paper/2410.02338","citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:9b9003d76e2e74e5a2ef1fa3e865f7a9a6bd5d9772494e362e4cee5f5929b9ee","observation_id":"2b913be1-8284-46c4-859f-e4e1a9452d8a","resolution":{"observed_at":"2026-08-06T22:44:01.630597Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.00309","last_updated":"2025-01-08T05:16:25Z","snapshot_observed_at":"2026-08-07T12:37:34.294206Z","submitted_at":"2024-12-31T06:59:35Z","title":"Retrieval-Augmented Generation with Graphs (GraphRAG)","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.00309","snapshot_observed_at":"2026-08-06T22:44:01.696766Z","title":"Retrieval-augmented generation with graphs (graphrag)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:01.696766Z"},"links":{"cited_paper":"/paper/2501.00309","citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:a11caee2bed1e70f202e048e12ed6e462da264b5e02ecc3d8137ba35024b0199","observation_id":"c1faa3bd-357b-46c2-a423-4f9b10db6a98","resolution":{"observed_at":"2026-08-06T22:44:01.696766Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:44:01.759649Z","title":"A survey of graph retrieval-augmented generation for customized large language models","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:01.759649Z"},"links":{"citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:22603796c8a61e650ecf36d1d1bb15338a6eb6c171a87a2a1218b4729a23019f","observation_id":"bd9ce4be-5c2c-4f7f-9df1-4ee5ba370724","resolution":{"observed_at":"2026-08-06T22:44:01.759649Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:44:01.819517Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:01.819517Z"},"links":{"citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:b0aa1ea6b48fda9e5ad7e5c96a9d36a3480e8f9f384b0a0f00051a970f7e7753","observation_id":"e1ed3fb7-da87-46a3-a43f-8c2eae208e9d","resolution":{"observed_at":"2026-08-06T22:44:01.819517Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.16506","last_updated":"2025-07-12T11:09:06Z","snapshot_observed_at":"2026-08-12T23:57:50.319793Z","submitted_at":"2024-05-26T10:11:40Z","title":"GRAG: Graph Retrieval-Augmented Generation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.16506","snapshot_observed_at":"2026-08-06T22:44:01.866785Z","title":"Grag: Graph retrieval-augmented generation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:01.866785Z"},"links":{"cited_paper":"/paper/2405.16506","citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:1ce84e2e58762c28b6b63f3ca580236ac3570dabb20382575cbfbfe4b1d9a2af","observation_id":"7707218b-ee5f-4335-84a2-79c6f3aa9d49","resolution":{"observed_at":"2026-08-06T22:44:01.866785Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.08921","last_updated":"2024-09-10T15:38:56Z","snapshot_observed_at":"2026-08-12T23:03:11.496267Z","submitted_at":"2024-08-15T12:20:24Z","title":"Graph Retrieval-Augmented Generation: A Survey","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.08921","snapshot_observed_at":"2026-08-06T22:44:01.941176Z","title":"Graph retrieval-augmented generation: A survey","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:01.941176Z"},"links":{"cited_paper":"/paper/2408.08921","citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:d62f6aa126486528d65d09064b51193ac13912d0e6baa4438c871b99dfb9fcbc","observation_id":"926c8d90-9707-44ca-9594-1a7e1f365bc2","resolution":{"observed_at":"2026-08-06T22:44:01.941176Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:44:07.665143Z","title":null,"venue":null,"work_id":"55c511c3-77bb-49ea-9a6e-893e44cca3ae","year":2025},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:02.060733Z"},"links":{"citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:b40c5274cbd8ea04d9f0eff0905f16df3a967fc29ebdeea79a7a967ff7cb0b23","observation_id":"3d695b85-fd7d-41c6-895a-09263ea62fcb","resolution":{"observed_at":"2026-08-06T22:44:07.746179Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.10081","last_updated":"2024-09-21T08:27:16Z","snapshot_observed_at":"2026-08-13T00:53:41.480879Z","submitted_at":"2024-03-15T07:45:37Z","title":"DRAGIN: Dynamic Retrieval Augmented Generation based on the Information Needs of Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.10081","snapshot_observed_at":"2026-08-06T22:44:02.147506Z","title":"Dragin: Dynamic retrieval augmented generation based on the information needs of llms","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:02.147506Z"},"links":{"cited_paper":"/paper/2403.10081","citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:952581cf21d7ffbb80d851a4cc551ffc9cb3a1b9920b67252294ca9069fa23a0","observation_id":"fa094e38-195e-4e5c-8621-9af6b0ebee0d","resolution":{"observed_at":"2026-08-06T22:44:02.147506Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.04338","last_updated":"2026-04-27T08:04:44Z","snapshot_observed_at":"2026-08-03T03:43:27.981758Z","submitted_at":"2025-03-06T11:34:49Z","title":"In-depth Analysis of Graph-based RAG in a Unified Framework","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.04338","snapshot_observed_at":"2026-08-06T22:44:02.284597Z","title":"In-depth analysis of graph-based rag in a unified framework","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:02.284597Z"},"links":{"cited_paper":"/paper/2503.04338","citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:64cc7aa73d815fb95f10482c625bfa031a84a95d96b7a5e79f94d73171d7adcf","observation_id":"975c69b1-f360-42c9-9870-5459e5419e48","resolution":{"observed_at":"2026-08-06T22:44:02.284597Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.16130","last_updated":"2025-02-19T10:49:41Z","snapshot_observed_at":"2026-07-06T18:05:11.700127Z","submitted_at":"2024-04-24T18:38:11Z","title":"From Local to Global: A Graph RAG Approach to Query-Focused Summarization","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.16130","snapshot_observed_at":"2026-08-06T22:44:02.411801Z","title":"From local to global: A graph rag approach to query-focused summarization","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:02.411801Z"},"links":{"cited_paper":"/paper/2404.16130","citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:f554d9a104acad15fa454237343167636a1ac4bf055e85e62ee1f3726969f979","observation_id":"46187748-14ca-4f79-83aa-277d167e2e84","resolution":{"observed_at":"2026-08-06T22:44:02.411801Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:44:07.504032Z","title":"Approximate nearest neighbors: Towards removing the curse of dimensionality","venue":null,"work_id":"7b732743-3cd3-44fe-85af-541b1dedcb08","year":1998},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:02.552094Z"},"links":{"citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:9efd136bb54267ca26c712f93095c9c7d76fada6264966a07516c4516f7c83f7","observation_id":"ab8f81ea-33e5-4d85-af0c-21b811624d50","resolution":{"observed_at":"2026-08-06T22:44:07.567083Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:44:07.283524Z","title":"Locality-sensitive hashing scheme based on p-stable distributions","venue":null,"work_id":"1c9740d2-6a17-4e0c-9581-8d705c7c2415","year":2004},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:02.595034Z"},"links":{"citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:0ffa525124ed66b5010a9cfb740684a35b5a705f7446dfc5e2a2aa381dc3353a","observation_id":"c161058c-1499-4060-aeea-717c40d6da0e","resolution":{"observed_at":"2026-08-06T22:44:07.372583Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:44:07.130658Z","title":"Razenshteyn, and Ludwig Schmidt","venue":null,"work_id":"67971a79-3bc5-4e62-aae6-5ab52cab2f41","year":2015},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:02.754230Z"},"links":{"citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:35a69bb6360bb73ea33007f0a27c61fc799e0d47389d8c10f655e7c712ad1448","observation_id":"61cb99b7-3c43-4aa2-8b00-5ddf2f6e66b2","resolution":{"observed_at":"2026-08-06T22:44:07.177358Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:44:06.974347Z","title":"Lightrag: Simple and fast retrieval-augmented generation, 2024","venue":null,"work_id":"bab446af-3611-44e6-8e9d-c28b9208f798","year":2024},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:02.816428Z"},"links":{"citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:469f1baaf486555f716d20e1df715a42da899028f86149b5dfa1f09ec2ae9ccb","observation_id":"fd8b7b64-a594-44fd-9a2a-1cf07af688f0","resolution":{"observed_at":"2026-08-06T22:44:07.041512Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.23895","last_updated":"2025-05-06T03:04:20Z","snapshot_observed_at":"2026-08-07T16:25:39.788137Z","submitted_at":"2025-03-31T09:46:35Z","title":"Dynamic Parametric Retrieval Augmented Generation for Test-time Knowledge Enhancement","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.23895","snapshot_observed_at":"2026-08-06T22:44:02.869515Z","title":"Dyprag: Retrieval-augmented generation with dynamic parameter- efficient adaptation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:02.869515Z"},"links":{"cited_paper":"/paper/2503.23895","citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:6bf798e371251e5a237b892f775a5ede5d977c63fc277c0c6b03a5c51c7aff93","observation_id":"295205d4-d1ba-4c94-aa88-832a949125ff","resolution":{"observed_at":"2026-08-06T22:44:02.869515Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:44:06.839081Z","title":null,"venue":null,"work_id":"0bec63c5-7d05-40be-9b3c-53ec8fd30a11","year":2024},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:03.012102Z"},"links":{"citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:8f9ade8b1dff0ab234680b9f54a2dc435d71f7cc034e5e27f16b6ad1d2d10bca","observation_id":"0606efa3-630d-4425-bb0e-4a174a42a375","resolution":{"observed_at":"2026-08-06T22:44:06.907571Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:44:06.731906Z","title":"Gslb: The graph structure learning benchmark","venue":null,"work_id":"e9d0cdff-2a37-4f11-a60a-9f7b324037b8","year":2023},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:03.067732Z"},"links":{"citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:4c51098d2db84db363325e9fe81edeea8b272de02835a35d32a93c1cda1bb3f5","observation_id":"ad71dad1-0e54-4a7b-aaf9-9c65e2c0e706","resolution":{"observed_at":"2026-08-06T22:44:06.779774Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2102.08942","last_updated":"2021-02-17T18:56:03Z","snapshot_observed_at":"2026-08-13T20:13:00.087942Z","submitted_at":"2021-02-17T18:56:03Z","title":"A Survey on Locality Sensitive Hashing Algorithms and their Applications","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2102.08942","snapshot_observed_at":"2026-08-06T22:44:03.206239Z","title":"A survey on locality sensitive hashing algorithms and their applications","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:03.206239Z"},"links":{"cited_paper":"/paper/2102.08942","citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:4feb62ad180f5bc09fac0130b7b6fc3872cfd1e4dd3d25e418cd526f8fec1fad","observation_id":"80373868-90a0-4f83-b344-9131cd22bcf2","resolution":{"observed_at":"2026-08-06T22:44:03.206239Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.15391","last_updated":"2024-01-27T11:41:48Z","snapshot_observed_at":"2026-08-13T01:06:03.395715Z","submitted_at":"2024-01-27T11:41:48Z","title":"MultiHop-RAG: Benchmarking Retrieval-Augmented Generation for Multi-Hop Queries","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.15391","snapshot_observed_at":"2026-08-06T22:44:03.400107Z","title":"Multihop-rag: Benchmarking retrieval- augmented generation for multi-hop queries","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:03.400107Z"},"links":{"cited_paper":"/paper/2401.15391","citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:afc7072a97d929a0a432aaf5d913afc48a01af916d92109926e014c05aa5d717","observation_id":"90ff8a7f-9d2f-47ff-b034-0550dad1abec","resolution":{"observed_at":"2026-08-06T22:44:03.400107Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1809.09600","last_updated":"2018-09-25T17:28:20Z","snapshot_observed_at":"2026-08-11T10:35:06.989614Z","submitted_at":"2018-09-25T17:28:20Z","title":"HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1809.09600","snapshot_observed_at":"2026-08-06T22:44:03.469518Z","title":"Hotpotqa: A dataset for diverse, explainable multi-hop question answering","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:03.469518Z"},"links":{"cited_paper":"/paper/1809.09600","citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:a01a52832494b44afdbd5a8dea2ef314ded3d94543f7e3951e776d0dae17d850","observation_id":"5a881f9f-0404-429f-b993-ab37c539720e","resolution":{"observed_at":"2026-08-06T22:44:03.469518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2112.08608","last_updated":"2022-05-11T04:59:10Z","snapshot_observed_at":"2026-08-13T17:14:18.870964Z","submitted_at":"2021-12-16T04:14:38Z","title":"QuALITY: Question Answering with Long Input Texts, Yes!","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2112.08608","snapshot_observed_at":"2026-08-06T22:44:03.520449Z","title":"Quality: Question answering with long input texts, yes! arXiv preprint arXiv:2112.08608 , 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:03.520449Z"},"links":{"cited_paper":"/paper/2112.08608","citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:1bc71f87e7042c7fe98592fb8cec8da87cc8b3a706b4668402a437f6261152b3","observation_id":"31856ce6-6472-4705-be76-9eddccbbee0e","resolution":{"observed_at":"2026-08-06T22:44:03.520449Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:44:06.604598Z","title":"Musique: Multihop questions via single-hop question com- position","venue":null,"work_id":"aec3ab3c-4828-4908-9b9d-6a98f5e224fa","year":2022},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:03.737642Z"},"links":{"citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:7ee865e57b1cbc045747a479a18f787150ca92776df63f3e22b30ef6ce8c34b0","observation_id":"edc5addf-ae67-4f30-b97a-1c16109bc877","resolution":{"observed_at":"2026-08-06T22:44:06.660024Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:44:03.854209Z","title":"Large language models are zero-shot reasoners","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:03.854209Z"},"links":{"citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:652cee645faa4be6594e7ba28b1ab8d7f30abb8cc10caeab0fae9a5c914313ca","observation_id":"0e53aa3e-f2f7-44ed-8a0d-7709226e13d7","resolution":{"observed_at":"2026-08-06T22:44:03.854209Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:44:06.471832Z","title":"Some simple effective approximations to the 2-poisson model for probabilistic weighted retrieval","venue":null,"work_id":"6e7a09cc-49bc-45f1-baf9-d961a8533c99","year":1994},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:03.960658Z"},"links":{"citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:760c2a3a944521fce7a8040e9abb709ddec59e6c2b0239f06fde48424a43f01a","observation_id":"f6b21f42-1844-43eb-abdb-002aeea84473","resolution":{"observed_at":"2026-08-06T22:44:06.529348Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:44:04.067384Z","title":"Retrieval-augmented generation for knowledge- intensive nlp tasks","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:04.067384Z"},"links":{"citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:5d2eef89e1f07c8854d90122b924c23effd9b7281253a6a518355b5ee310a8a3","observation_id":"b1e538f7-24a4-4303-9ceb-3c3ba2c49f47","resolution":{"observed_at":"2026-08-06T22:44:04.067384Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:44:06.302306Z","title":"Hipporag: Neurobiologically inspired long-term memory for large language models","venue":null,"work_id":"69212927-3ad6-4776-9030-74bc3551c246","year":2024},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:04.225449Z"},"links":{"citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:aa572431b97af93d1fc131e4604b4224dc400c59d760b4bb8367a26f02fdb44a","observation_id":"9e024cf0-8c7b-457c-88b3-31d01ad12c2c","resolution":{"observed_at":"2026-08-06T22:44:06.374367Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:44:06.130517Z","title":"Toolformer: Language models can teach themselves to use tools","venue":null,"work_id":"4c17c520-9d49-4562-bcc3-f58ef6e02b86","year":2023},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:04.356110Z"},"links":{"citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:8bcb633385b8976cb16127a1935a46f5e8f7adb4d3cf17cb8541d51ae88cc973","observation_id":"871795a1-7e62-4397-9892-ea812655b73a","resolution":{"observed_at":"2026-08-06T22:44:06.207772Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2212.10511","last_updated":"2023-07-02T07:21:59Z","snapshot_observed_at":"2026-07-06T14:33:08.041820Z","submitted_at":"2022-12-20T18:30:15Z","title":"When Not to Trust Language Models: Investigating Effectiveness of Parametric and Non-Parametric Memories","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2212.10511","snapshot_observed_at":"2026-08-06T22:44:04.458103Z","title":"When not to trust language models: Investi- gating effectiveness of parametric and non-parametric memories","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:04.458103Z"},"links":{"cited_paper":"/paper/2212.10511","citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:cf765d52fd8f47198b7626bb15631ba815d3e102130ca328b1fd17a810689f82","observation_id":"c6c3bdd4-e7e6-47ec-94e0-11013dc86fc5","resolution":{"observed_at":"2026-08-06T22:44:04.458103Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.21039","last_updated":"2025-04-28T08:41:12Z","snapshot_observed_at":"2026-08-07T15:58:40.459044Z","submitted_at":"2025-04-28T08:41:12Z","title":"Llama-3.1-FoundationAI-SecurityLLM-Base-8B Technical Report","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.21039","snapshot_observed_at":"2026-08-06T22:44:04.596340Z","title":"Llama-3.1-foundationai-securityllm-base- 8b technical report","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:04.596340Z"},"links":{"cited_paper":"/paper/2504.21039","citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:1f6b73c09f4b7591dac54d013a14a94edaa8f67454d6ec03d5488fef340dfa6d","observation_id":"dc365024-fb1e-4075-af81-bffb556a7b67","resolution":{"observed_at":"2026-08-06T22:44:04.596340Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.05030","last_updated":"2025-01-09T07:41:22Z","snapshot_observed_at":"2026-08-14T08:54:48.285044Z","submitted_at":"2025-01-09T07:41:22Z","title":"A General Retrieval-Augmented Generation Framework for Multimodal Case-Based Reasoning Applications","version":1},"cited_work":{"arxiv_id":"2501.05030","doi":null,"metadata_source":"pith","pith_arxiv_id":"2501.05030","snapshot_observed_at":"2026-08-06T22:44:05.075522Z","title":"A General Retrieval-Augmented Generation Framework for Multimodal Case-Based Reasoning Applications","venue":"cs.AI","work_id":"83c41389-6d93-4a08-a7fa-f7552eeed887","year":2025},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:04.660922Z"},"links":{"cited_paper":"/paper/2501.05030","citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:9ed339dd541b3ce3ccbeb6732666e94fcd9f31b35d4a89e4db7d9d3e8ad05147","observation_id":"e9b72f9b-a344-4ac7-905e-34ca5660ef2d","resolution":{"observed_at":"2026-08-06T22:44:05.142608Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:44:06.016127Z","title":"M3-embedding: Multi-linguality, multi-functionality, multi-granularity text embeddings through self-knowledge distillation","venue":null,"work_id":"fd3f8623-483a-4817-9d6a-ed1f8df15334","year":2024},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:04.735731Z"},"links":{"citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:ca356ff5ac7bf3034885ee58ff9a2320a32351816440bda247b92f886db365fa","observation_id":"36d79908-6ee9-405c-a7eb-99d934a96936","resolution":{"observed_at":"2026-08-06T22:44:06.059990Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2409.05591","last_updated":"2025-04-09T09:09:37Z","snapshot_observed_at":"2026-08-12T22:48:39.524090Z","submitted_at":"2024-09-09T13:20:31Z","title":"MemoRAG: Boosting Long Context Processing with Global Memory-Enhanced Retrieval Augmentation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.05591","snapshot_observed_at":"2026-08-06T22:44:04.826487Z","title":"Memorag: Moving towards next-gen rag via memory-inspired knowledge discovery","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:04.826487Z"},"links":{"cited_paper":"/paper/2409.05591","citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:7acdb89536ce48041145c2d5e35123a65f1b9040d98713e0270e08829c0cb153","observation_id":"3bbe0b2b-07f0-4181-8883-66b9e444ae18","resolution":{"observed_at":"2026-08-06T22:44:04.826487Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:44:04.891202Z","title":"Language models are few-shot learners","venue":null,"work_id":null,"year":1901},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:04.891202Z"},"links":{"citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:060b352c403c1d031be96dcd30c47669d6ea0029cec352ce182692eaff07e2b2","observation_id":"e42123be-4497-4b8f-9c67-76dd21d7f4c3","resolution":{"observed_at":"2026-08-06T22:44:04.891202Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.07883","last_updated":"2024-01-15T18:25:18Z","snapshot_observed_at":"2026-08-13T04:42:33.845936Z","submitted_at":"2024-01-15T18:25:18Z","title":"The Chronicles of RAG: The Retriever, the Chunk and the Generator","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.07883","snapshot_observed_at":"2026-08-06T22:44:04.946360Z","title":"The chronicles of rag: The retriever, the chunk and the generator","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora","version":2},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:04.946360Z"},"links":{"cited_paper":"/paper/2401.07883","citing_paper":"/paper/2506.20963"},"observation_digest":"sha256:1da781f4b7cf9edee4b44b6af563b4b8ffca7304aabd14b4001b392ec0997f83","observation_id":"871d0ca4-5930-4f5f-8378-7e659668fe87","resolution":{"observed_at":"2026-08-06T22:44:04.946360Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2506.20963","last_updated":"2025-07-04T01:31:36Z","latest_version":2,"primary_category":"cs.IR","snapshot_observed_at":"2026-08-09T23:24:21.009731Z","submitted_at":"2025-06-26T03:01:33Z","title":"EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora"},"reference_resolution":{"displayed":57,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":43,"verified_exact":1,"verified_fuzzy":13},"total_outbound_references":57},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"thesis":"As of 14 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 10 inbound Pith citation observations for arXiv:2506.20963."}