{"as_of":"2026-08-09T22:04:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:b65d3dae5b82af41fdb47102f24e508d013b2afcba1b93e61b4351382bf7ad9e","coverage":[{"denominator":11,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":11,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-01T14:30:35.625784Z","state":"measured"},{"denominator":11,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":11,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2607.18756/citation-record","integrity":"/paper/2607.18756/integrity","json":"/paper/2607.18756/citation-record.json","paper":"/paper/2607.18756"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2005.11401","last_updated":"2021-04-12T15:42:18Z","snapshot_observed_at":"2026-08-07T05:44:30.677502Z","submitted_at":"2020-05-22T21:34:34Z","title":"Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2005.11401","snapshot_observed_at":"2026-08-01T14:30:34.919780Z","title":"Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.18756","last_updated":"2026-07-21T06:25:46Z","snapshot_observed_at":"2026-08-06T03:18:43.212808Z","submitted_at":"2026-07-21T06:25:46Z","title":"RAGAL: A Frugal, Fully Local Retrieval-Augmented Assistant for Technical Support at a Government Agency","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-01T14:30:34.919780Z"},"links":{"cited_paper":"/paper/2005.11401","citing_paper":"/paper/2607.18756"},"observation_digest":"sha256:1f0d48984836f0ea63156be51cf1a0976fd6894f4380cb116c4b249396aa3793","observation_id":"e9b20226-9ee6-4c1c-bbe8-89d8da3bf6e4","resolution":{"observed_at":"2026-08-01T14:30:34.919780Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1908.10084","last_updated":"2019-08-27T08:50:17Z","snapshot_observed_at":"2026-07-06T08:17:05.681370Z","submitted_at":"2019-08-27T08:50:17Z","title":"Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1908.10084","snapshot_observed_at":"2026-08-01T14:30:34.970193Z","title":"Sentence-BERT: Sentence Embeddings using Siamese BERT- Networks,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.18756","last_updated":"2026-07-21T06:25:46Z","snapshot_observed_at":"2026-08-06T03:18:43.212808Z","submitted_at":"2026-07-21T06:25:46Z","title":"RAGAL: A Frugal, Fully Local Retrieval-Augmented Assistant for Technical Support at a Government Agency","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-01T14:30:34.970193Z"},"links":{"cited_paper":"/paper/1908.10084","citing_paper":"/paper/2607.18756"},"observation_digest":"sha256:74e4e869c0a6470010a8bcb0e1d2b1ad7e7bb48386985f5dd2588e43f96b3b46","observation_id":"55394ad6-b8ab-428d-8530-e83b08f2842d","resolution":{"observed_at":"2026-08-01T14:30:34.970193Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1705.00652","last_updated":"2017-05-01T18:24:15Z","snapshot_observed_at":"2026-08-05T07:58:48.043089Z","submitted_at":"2017-05-01T18:24:15Z","title":"Efficient Natural Language Response Suggestion for Smart Reply","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1705.00652","snapshot_observed_at":"2026-08-01T14:30:35.048458Z","title":"Efficient Natural Language Response Suggestion for Smart Reply,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.18756","last_updated":"2026-07-21T06:25:46Z","snapshot_observed_at":"2026-08-06T03:18:43.212808Z","submitted_at":"2026-07-21T06:25:46Z","title":"RAGAL: A Frugal, Fully Local Retrieval-Augmented Assistant for Technical Support at a Government Agency","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-01T14:30:35.048458Z"},"links":{"cited_paper":"/paper/1705.00652","citing_paper":"/paper/2607.18756"},"observation_digest":"sha256:6360fc2a78253df9acc1c8752eec5d32f502933d1b5383bd1ada717718fd3c45","observation_id":"5b69bb86-1f63-4784-a972-061cdbe86318","resolution":{"observed_at":"2026-08-01T14:30:35.048458Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2112.07577","last_updated":"2022-04-25T16:32:24Z","snapshot_observed_at":"2026-07-06T12:18:42.245356Z","submitted_at":"2021-12-14T17:34:43Z","title":"GPL: Generative Pseudo Labeling for Unsupervised Domain Adaptation of Dense Retrieval","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2112.07577","snapshot_observed_at":"2026-08-01T14:30:35.141673Z","title":"GPL: Generative Pseudo Labeling for Unsu- pervised Domain Adaptation of Dense Retrieval,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.18756","last_updated":"2026-07-21T06:25:46Z","snapshot_observed_at":"2026-08-06T03:18:43.212808Z","submitted_at":"2026-07-21T06:25:46Z","title":"RAGAL: A Frugal, Fully Local Retrieval-Augmented Assistant for Technical Support at a Government Agency","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-01T14:30:35.141673Z"},"links":{"cited_paper":"/paper/2112.07577","citing_paper":"/paper/2607.18756"},"observation_digest":"sha256:c51495a8d38b0b48e51b1ec9d543e76d0bbb5c34d657d81bf6070c7224ad1dd1","observation_id":"1132ebc8-669b-438b-9602-395a41e38998","resolution":{"observed_at":"2026-08-01T14:30:35.141673Z","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":"2026-08-01T14:30:35.221808Z","title":"GRILE: A Benchmark for Grammar Reason- ing and Explanation in Romanian LLMs,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.18756","last_updated":"2026-07-21T06:25:46Z","snapshot_observed_at":"2026-08-06T03:18:43.212808Z","submitted_at":"2026-07-21T06:25:46Z","title":"RAGAL: A Frugal, Fully Local Retrieval-Augmented Assistant for Technical Support at a Government Agency","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-01T14:30:35.221808Z"},"links":{"citing_paper":"/paper/2607.18756"},"observation_digest":"sha256:a8c187eeee298d5fffbf6442f72c30f3e5960de4388a85f1f6ed3baec0ce61af","observation_id":"6088e9d1-f2bc-4013-96f3-e92ba617a301","resolution":{"observed_at":"2026-08-01T14:30:35.221808Z","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":"2026-08-01T14:30:35.288217Z","title":"Finetune-RAG: Fine-Tuning Language Models to Resist Hallucination in Retrieval-Augmented Generation,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.18756","last_updated":"2026-07-21T06:25:46Z","snapshot_observed_at":"2026-08-06T03:18:43.212808Z","submitted_at":"2026-07-21T06:25:46Z","title":"RAGAL: A Frugal, Fully Local Retrieval-Augmented Assistant for Technical Support at a Government Agency","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-01T14:30:35.288217Z"},"links":{"citing_paper":"/paper/2607.18756"},"observation_digest":"sha256:b836149221b0b1cf3ede939e4415e6b9e331422d13d5389f2dcae156688c7f54","observation_id":"2a2e8518-9fc8-42a4-87a4-a5973d220d85","resolution":{"observed_at":"2026-08-01T14:30:35.288217Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.03216","last_updated":"2025-12-12T11:26:32Z","snapshot_observed_at":"2026-07-06T17:25:35.493362Z","submitted_at":"2024-02-05T17:26:49Z","title":"M3-Embedding: Multi-Linguality, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.03216","snapshot_observed_at":"2026-08-01T14:30:35.349759Z","title":"M3-Embedding: Multi-Linguality, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.18756","last_updated":"2026-07-21T06:25:46Z","snapshot_observed_at":"2026-08-06T03:18:43.212808Z","submitted_at":"2026-07-21T06:25:46Z","title":"RAGAL: A Frugal, Fully Local Retrieval-Augmented Assistant for Technical Support at a Government Agency","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-01T14:30:35.349759Z"},"links":{"cited_paper":"/paper/2402.03216","citing_paper":"/paper/2607.18756"},"observation_digest":"sha256:d100dec37b395304c64b72e9c2ff2dfedf60acbc2e938ada618396bda98eaad1","observation_id":"187c4f63-c7ac-4d18-858f-a8ede73feb10","resolution":{"observed_at":"2026-08-01T14:30:35.349759Z","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":"2026-08-01T14:30:35.411741Z","title":"Reciprocal Rank Fusion Outperforms Condorcet and Individual Rank Learning Methods,","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2607.18756","last_updated":"2026-07-21T06:25:46Z","snapshot_observed_at":"2026-08-06T03:18:43.212808Z","submitted_at":"2026-07-21T06:25:46Z","title":"RAGAL: A Frugal, Fully Local Retrieval-Augmented Assistant for Technical Support at a Government Agency","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-01T14:30:35.411741Z"},"links":{"citing_paper":"/paper/2607.18756"},"observation_digest":"sha256:9dc69d73b476f73937e23e4a24feb0a3e06893f054d8c19cb8648ad16f0e1d2b","observation_id":"078a9e41-8aff-4afc-b222-4031ba1de688","resolution":{"observed_at":"2026-08-01T14:30:35.411741Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2110.02861","last_updated":"2022-06-20T16:05:15Z","snapshot_observed_at":"2026-07-06T11:55:04.054344Z","submitted_at":"2021-10-06T15:43:20Z","title":"8-bit Optimizers via Block-wise Quantization","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2110.02861","snapshot_observed_at":"2026-08-01T14:30:35.482308Z","title":"8-bit Optimizers via Block-wise Quantiza- tion,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.18756","last_updated":"2026-07-21T06:25:46Z","snapshot_observed_at":"2026-08-06T03:18:43.212808Z","submitted_at":"2026-07-21T06:25:46Z","title":"RAGAL: A Frugal, Fully Local Retrieval-Augmented Assistant for Technical Support at a Government Agency","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-01T14:30:35.482308Z"},"links":{"cited_paper":"/paper/2110.02861","citing_paper":"/paper/2607.18756"},"observation_digest":"sha256:49ab3a0919c5a2c4e5422bebefa7c9abf15dd603f6394e60c3cb04f222f35d39","observation_id":"aec9d49b-5138-48d3-979d-83f9af323cdb","resolution":{"observed_at":"2026-08-01T14:30:35.482308Z","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":"2026-08-01T14:30:35.564692Z","title":"Training Deep Nets with Sublinear Memory Cost,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18756","last_updated":"2026-07-21T06:25:46Z","snapshot_observed_at":"2026-08-06T03:18:43.212808Z","submitted_at":"2026-07-21T06:25:46Z","title":"RAGAL: A Frugal, Fully Local Retrieval-Augmented Assistant for Technical Support at a Government Agency","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-01T14:30:35.564692Z"},"links":{"citing_paper":"/paper/2607.18756"},"observation_digest":"sha256:5f1c10ea1b9ab0441f7a81f6815df8fcb01e75248609845d035966832e0de2bc","observation_id":"ed3550a1-5695-4c6c-8e0a-5be0fc61074b","resolution":{"observed_at":"2026-08-01T14:30:35.564692Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1604.06174","last_updated":"2016-04-22T19:21:36Z","snapshot_observed_at":"2026-08-08T09:03:25.135475Z","submitted_at":"2016-04-21T04:15:27Z","title":"Training Deep Nets with Sublinear Memory Cost","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1604.06174","snapshot_observed_at":"2026-08-01T14:30:35.625784Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18756","last_updated":"2026-07-21T06:25:46Z","snapshot_observed_at":"2026-08-06T03:18:43.212808Z","submitted_at":"2026-07-21T06:25:46Z","title":"RAGAL: A Frugal, Fully Local Retrieval-Augmented Assistant for Technical Support at a Government Agency","version":1},"reference_index":2016,"source":"pdf_text","source_observed_at":"2026-08-01T14:30:35.625784Z"},"links":{"cited_paper":"/paper/1604.06174","citing_paper":"/paper/2607.18756"},"observation_digest":"sha256:78ef8a89055dc48dc12a79daa85cad5e1560c8f6b853a0c0d21f4a92d7d1c55c","observation_id":"f5f1961b-2f38-450e-9515-f691bf4ce7fc","resolution":{"observed_at":"2026-08-01T14:30:35.625784Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.18756","last_updated":"2026-07-21T06:25:46Z","latest_version":1,"primary_category":"cs.IR","snapshot_observed_at":"2026-08-06T03:18:43.212808Z","submitted_at":"2026-07-21T06:25:46Z","title":"RAGAL: A Frugal, Fully Local Retrieval-Augmented Assistant for Technical Support at a Government Agency"},"reference_resolution":{"displayed":11,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":11,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":11},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 11 of 11 outbound references and 0 inbound Pith citation observations for arXiv:2607.18756."}