{"as_of":"2026-08-08T00:44:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:e659fd19aaf7312444045bd7dfdf76e7740d52fb7681752397930d8cd2136937","coverage":[{"denominator":40,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":40,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-30T10:56:48.227998Z","state":"measured"},{"denominator":40,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":40,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+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/2607.23838/citation-record","integrity":"/paper/2607.23838/integrity","json":"/paper/2607.23838/citation-record.json","paper":"/paper/2607.23838"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-30T10:56:48.047305Z","title":"Retrieval-augmented generation for knowledge-intensive NLP tasks,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.23838","last_updated":"2026-07-26T20:52:23Z","snapshot_observed_at":"2026-08-05T00:15:21.105413Z","submitted_at":"2026-07-26T20:52:23Z","title":"TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-07-30T10:56:48.047305Z"},"links":{"citing_paper":"/paper/2607.23838"},"observation_digest":"sha256:4ca6f1cf6814d3b775deda32cda84a77e840c2a06b6fdd1d3265bca2d0b7fc64","observation_id":"34d4a1ba-3c68-4470-8737-bfabb166dccb","resolution":{"observed_at":"2026-07-30T10:56:48.047305Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.07867","last_updated":"2024-08-13T01:55:06Z","snapshot_observed_at":"2026-07-06T17:29:05.185768Z","submitted_at":"2024-02-12T18:28:36Z","title":"PoisonedRAG: Knowledge Corruption Attacks to Retrieval-Augmented Generation of Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.07867","snapshot_observed_at":"2026-07-30T10:56:48.053139Z","title":"PoisonedRAG: Knowledge corrup- tion attacks to retrieval-augmented generation of large language models,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.23838","last_updated":"2026-07-26T20:52:23Z","snapshot_observed_at":"2026-08-05T00:15:21.105413Z","submitted_at":"2026-07-26T20:52:23Z","title":"TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-07-30T10:56:48.053139Z"},"links":{"cited_paper":"/paper/2402.07867","citing_paper":"/paper/2607.23838"},"observation_digest":"sha256:d3a3ffee492d5fb65f49fff51031a5d71291f5c4a50570ffab17aa6396f7dfcb","observation_id":"1034e036-5d35-4e13-90d1-5b38feac677c","resolution":{"observed_at":"2026-07-30T10:56:48.053139Z","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":"2026-07-30T10:56:48.058100Z","title":"Poisoning retrieval corpora by injecting adversarial passages,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.23838","last_updated":"2026-07-26T20:52:23Z","snapshot_observed_at":"2026-08-05T00:15:21.105413Z","submitted_at":"2026-07-26T20:52:23Z","title":"TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-07-30T10:56:48.058100Z"},"links":{"citing_paper":"/paper/2607.23838"},"observation_digest":"sha256:8cb354402b417493d6b52c36b83c0e54feaac38fa61c5eb4ea8f293356a2f10a","observation_id":"e1cf35d4-4652-463c-ba29-bed07152b79a","resolution":{"observed_at":"2026-07-30T10:56:48.058100Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.12173","last_updated":"2023-05-05T14:26:17Z","snapshot_observed_at":"2026-07-06T14:55:08.682906Z","submitted_at":"2023-02-23T17:14:38Z","title":"Not what you've signed up for: Compromising Real-World LLM-Integrated Applications with Indirect Prompt Injection","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.12173","snapshot_observed_at":"2026-07-30T10:56:48.063074Z","title":"Not what you’ve signed up for: Compromising real-world LLM- integrated applications with indirect prompt injection,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.23838","last_updated":"2026-07-26T20:52:23Z","snapshot_observed_at":"2026-08-05T00:15:21.105413Z","submitted_at":"2026-07-26T20:52:23Z","title":"TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-07-30T10:56:48.063074Z"},"links":{"cited_paper":"/paper/2302.12173","citing_paper":"/paper/2607.23838"},"observation_digest":"sha256:e4897672f439f95adc60dd14241780f1c1c35b3e846133255d96af1cdb1f902b","observation_id":"b3132ed0-c8b8-4461-80c3-2420095fe1c0","resolution":{"observed_at":"2026-07-30T10:56:48.063074Z","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":"2026-07-30T10:56:48.068027Z","title":"Sentence-BERT: Sentence embeddings using Siamese BERT-networks,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.23838","last_updated":"2026-07-26T20:52:23Z","snapshot_observed_at":"2026-08-05T00:15:21.105413Z","submitted_at":"2026-07-26T20:52:23Z","title":"TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-07-30T10:56:48.068027Z"},"links":{"citing_paper":"/paper/2607.23838"},"observation_digest":"sha256:c77f49055882cada1c1656e672758a3e3978f8e2b042eb968c118bcbada433b3","observation_id":"d1fda1b3-37e0-4c7d-abd6-d571f2313413","resolution":{"observed_at":"2026-07-30T10:56:48.068027Z","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":"2026-07-30T10:56:48.073599Z","title":"Billion-scale similarity search with GPUs,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.23838","last_updated":"2026-07-26T20:52:23Z","snapshot_observed_at":"2026-08-05T00:15:21.105413Z","submitted_at":"2026-07-26T20:52:23Z","title":"TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-07-30T10:56:48.073599Z"},"links":{"citing_paper":"/paper/2607.23838"},"observation_digest":"sha256:1ba965c9f636e6e96a083e5b391432deefdb49fc624cc9d5108af0ccf5591348","observation_id":"66ba4d60-9834-4e95-b354-ae93dd1d7826","resolution":{"observed_at":"2026-07-30T10:56:48.073599Z","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":"2026-07-30T10:56:48.078715Z","title":"Term-weighting approaches in automatic text retrieval,","venue":null,"work_id":null,"year":1988},"citing_paper":{"arxiv_id":"2607.23838","last_updated":"2026-07-26T20:52:23Z","snapshot_observed_at":"2026-08-05T00:15:21.105413Z","submitted_at":"2026-07-26T20:52:23Z","title":"TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-07-30T10:56:48.078715Z"},"links":{"citing_paper":"/paper/2607.23838"},"observation_digest":"sha256:1fa247c472ca4a82aa98775ddb3a3690ba00372f0e4ed9903bdc2617bdf85f0c","observation_id":"971f8b94-21a1-4235-a9b8-8b45a1889eb1","resolution":{"observed_at":"2026-07-30T10:56:48.078715Z","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":"2026-07-30T10:56:48.083117Z","title":"Lan- guage models are unsupervised multitask learners,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.23838","last_updated":"2026-07-26T20:52:23Z","snapshot_observed_at":"2026-08-05T00:15:21.105413Z","submitted_at":"2026-07-26T20:52:23Z","title":"TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-07-30T10:56:48.083117Z"},"links":{"citing_paper":"/paper/2607.23838"},"observation_digest":"sha256:03cb294e5d5d28a25c7c47f2641eedec085b2def11cee7dca2efb28fa2b784dc","observation_id":"e49eb2e4-34c2-4485-9b46-52703edce1d2","resolution":{"observed_at":"2026-07-30T10:56:48.083117Z","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":"2026-07-30T10:56:48.087853Z","title":"The Byzantine generals problem,","venue":null,"work_id":null,"year":1982},"citing_paper":{"arxiv_id":"2607.23838","last_updated":"2026-07-26T20:52:23Z","snapshot_observed_at":"2026-08-05T00:15:21.105413Z","submitted_at":"2026-07-26T20:52:23Z","title":"TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-07-30T10:56:48.087853Z"},"links":{"citing_paper":"/paper/2607.23838"},"observation_digest":"sha256:0732759164d67d29be1b0054e604843f27503cb91c33cacf8d63913424c607c5","observation_id":"f4d09a65-062f-49bd-8149-7091d3275220","resolution":{"observed_at":"2026-07-30T10:56:48.087853Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1902.06705","last_updated":"2019-02-20T17:38:32Z","snapshot_observed_at":"2026-08-02T02:05:14.321072Z","submitted_at":"2019-02-18T18:18:27Z","title":"On Evaluating Adversarial Robustness","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1902.06705","snapshot_observed_at":"2026-07-30T10:56:48.092922Z","title":"On evaluating adversarial robust- ness,","venue":null,"work_id":null,"year":1902},"citing_paper":{"arxiv_id":"2607.23838","last_updated":"2026-07-26T20:52:23Z","snapshot_observed_at":"2026-08-05T00:15:21.105413Z","submitted_at":"2026-07-26T20:52:23Z","title":"TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-07-30T10:56:48.092922Z"},"links":{"cited_paper":"/paper/1902.06705","citing_paper":"/paper/2607.23838"},"observation_digest":"sha256:0bf230c0a25afe1edb1defec30ee8c11b9b6cd55d45c1f2ac0d60cc1a3ef2e7e","observation_id":"6590774d-daec-485a-af93-0d41fb5f8e3e","resolution":{"observed_at":"2026-07-30T10:56:48.092922Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.09288","last_updated":"2023-07-19T17:08:59Z","snapshot_observed_at":"2026-08-07T12:56:43.323460Z","submitted_at":"2023-07-18T14:31:57Z","title":"Llama 2: Open Foundation and Fine-Tuned Chat Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.09288","snapshot_observed_at":"2026-07-30T10:56:48.098490Z","title":"Llama 2: Open foundation and fine-tuned chat models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.23838","last_updated":"2026-07-26T20:52:23Z","snapshot_observed_at":"2026-08-05T00:15:21.105413Z","submitted_at":"2026-07-26T20:52:23Z","title":"TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-07-30T10:56:48.098490Z"},"links":{"cited_paper":"/paper/2307.09288","citing_paper":"/paper/2607.23838"},"observation_digest":"sha256:f3e79dab0a7289f47f538ff009b5876d91f2f8750063bb77a24b0a3c700434d5","observation_id":"2ad9f6d5-99ec-49c6-97b3-b47ed886044e","resolution":{"observed_at":"2026-07-30T10:56:48.098490Z","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":"2026-07-30T10:56:48.103258Z","title":"HotFlip: White-box adversarial examples for text classification,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.23838","last_updated":"2026-07-26T20:52:23Z","snapshot_observed_at":"2026-08-05T00:15:21.105413Z","submitted_at":"2026-07-26T20:52:23Z","title":"TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-07-30T10:56:48.103258Z"},"links":{"citing_paper":"/paper/2607.23838"},"observation_digest":"sha256:02701fbe67aa86a24d250de654f99dae1c72a9d8c7418b457a48ab588707a364","observation_id":"fe375c13-9550-4fcb-8731-134bd124a9ab","resolution":{"observed_at":"2026-07-30T10:56:48.103258Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2604.00387","last_updated":"2026-04-04T07:18:50Z","snapshot_observed_at":"2026-08-04T09:28:38.404006Z","submitted_at":"2026-04-01T02:16:42Z","title":"RAGShield: Detecting Numerical Claim Manipulation in Government RAG Systems","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2604.00387","snapshot_observed_at":"2026-07-30T10:56:48.107630Z","title":"RAGShield: Detecting numerical claim manipulation in government RAG systems,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.23838","last_updated":"2026-07-26T20:52:23Z","snapshot_observed_at":"2026-08-05T00:15:21.105413Z","submitted_at":"2026-07-26T20:52:23Z","title":"TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-07-30T10:56:48.107630Z"},"links":{"cited_paper":"/paper/2604.00387","citing_paper":"/paper/2607.23838"},"observation_digest":"sha256:b76efe7424d1957c0d5761ec02de71143db0b328d64d9dfab6d85a7314811943","observation_id":"6fc8c2de-655d-4dee-bff9-d1a5450edbe2","resolution":{"observed_at":"2026-07-30T10:56:48.107630Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.00879","last_updated":"2025-05-22T22:00:19Z","snapshot_observed_at":"2026-07-06T20:15:31.955797Z","submitted_at":"2025-01-01T15:57:34Z","title":"TrustRAG: Enhancing Robustness and Trustworthiness in Retrieval-Augmented Generation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.00879","snapshot_observed_at":"2026-07-30T10:56:48.112346Z","title":"TrustRAG: Enhancing robustness and trustworthiness in retrieval-augmented generation,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.23838","last_updated":"2026-07-26T20:52:23Z","snapshot_observed_at":"2026-08-05T00:15:21.105413Z","submitted_at":"2026-07-26T20:52:23Z","title":"TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-07-30T10:56:48.112346Z"},"links":{"cited_paper":"/paper/2501.00879","citing_paper":"/paper/2607.23838"},"observation_digest":"sha256:5b69f73de57e66732658295688332b4dcd44f68b6a66822d0d4af15c1dd51963","observation_id":"921d8fdb-c382-4734-9795-2b86a5166311","resolution":{"observed_at":"2026-07-30T10:56:48.112346Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.18543","last_updated":"2025-05-24T06:17:59Z","snapshot_observed_at":"2026-08-08T00:41:28.430373Z","submitted_at":"2025-05-24T06:17:59Z","title":"Benchmarking Poisoning Attacks against Retrieval-Augmented Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.18543","snapshot_observed_at":"2026-07-30T10:56:48.116996Z","title":"Benchmarking poisoning attacks against retrieval- augmented generation,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.23838","last_updated":"2026-07-26T20:52:23Z","snapshot_observed_at":"2026-08-05T00:15:21.105413Z","submitted_at":"2026-07-26T20:52:23Z","title":"TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-07-30T10:56:48.116996Z"},"links":{"cited_paper":"/paper/2505.18543","citing_paper":"/paper/2607.23838"},"observation_digest":"sha256:a9b44f2529a2e7ee516381164d89e10032f99b733d6b9c3a3af9a929eeb5cec7","observation_id":"61e0e649-2c5d-45e0-ba93-81d2ba35811d","resolution":{"observed_at":"2026-07-30T10:56:48.116996Z","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":"2026-07-30T10:56:48.121314Z","title":"Practical poi- soning attacks against retrieval-augmented generation,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.23838","last_updated":"2026-07-26T20:52:23Z","snapshot_observed_at":"2026-08-05T00:15:21.105413Z","submitted_at":"2026-07-26T20:52:23Z","title":"TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-07-30T10:56:48.121314Z"},"links":{"citing_paper":"/paper/2607.23838"},"observation_digest":"sha256:04f8017a2d4de921cc87cc73dfdd1640e4af207c8489cf43375a4435b8664640","observation_id":"0625251b-8242-4d11-b35b-27000d0535c5","resolution":{"observed_at":"2026-07-30T10:56:48.121314Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2605.26754","last_updated":"2026-05-26T09:27:19Z","snapshot_observed_at":"2026-08-01T03:19:41.601621Z","submitted_at":"2026-05-26T09:27:19Z","title":"Cordon-MAS: Defending RAG against Knowledge Poisoning via Information-Flow Control","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2605.26754","snapshot_observed_at":"2026-07-30T10:56:48.125605Z","title":"Cordon-MAS: Defending RAG against knowledge poi- soning via information-flow control,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.23838","last_updated":"2026-07-26T20:52:23Z","snapshot_observed_at":"2026-08-05T00:15:21.105413Z","submitted_at":"2026-07-26T20:52:23Z","title":"TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-07-30T10:56:48.125605Z"},"links":{"cited_paper":"/paper/2605.26754","citing_paper":"/paper/2607.23838"},"observation_digest":"sha256:133c3cc34c45381ebd84a8e10526a431b8ea0b8a12d04041bd128e810b018257","observation_id":"5070b6fa-8154-45e7-a317-ecaf7fa0da6a","resolution":{"observed_at":"2026-07-30T10:56:48.125605Z","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":"2026-07-30T10:56:48.130258Z","title":"Rescuing the unpoisoned: Efficient defense against knowledge corruption attacks on RAG systems,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.23838","last_updated":"2026-07-26T20:52:23Z","snapshot_observed_at":"2026-08-05T00:15:21.105413Z","submitted_at":"2026-07-26T20:52:23Z","title":"TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-07-30T10:56:48.130258Z"},"links":{"citing_paper":"/paper/2607.23838"},"observation_digest":"sha256:a1eb7be53bdd03b462ec2a3bb1b32def4e286dd6dcc887d8833c4e5f1427ce53","observation_id":"b628c666-e4c0-4d0a-a533-51cb2361457f","resolution":{"observed_at":"2026-07-30T10:56:48.130258Z","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":"2026-07-30T10:56:48.134698Z","title":"Traceback of poisoning attacks to retrieval-augmented generation,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.23838","last_updated":"2026-07-26T20:52:23Z","snapshot_observed_at":"2026-08-05T00:15:21.105413Z","submitted_at":"2026-07-26T20:52:23Z","title":"TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-07-30T10:56:48.134698Z"},"links":{"citing_paper":"/paper/2607.23838"},"observation_digest":"sha256:ac706cc94128f859961bb85a3406df3fe93ae09a7f144194d0cd1a4c0bbde449","observation_id":"9652c7b4-c465-4a88-b82b-6bc5e1e5ae1e","resolution":{"observed_at":"2026-07-30T10:56:48.134698Z","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":"2026-07-30T10:56:48.139137Z","title":"Dense passage retrieval for open-domain question answering,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.23838","last_updated":"2026-07-26T20:52:23Z","snapshot_observed_at":"2026-08-05T00:15:21.105413Z","submitted_at":"2026-07-26T20:52:23Z","title":"TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-07-30T10:56:48.139137Z"},"links":{"citing_paper":"/paper/2607.23838"},"observation_digest":"sha256:2ae5bf600550f7861ab54f551fbca288162723e11a9a342d55d04faf99ccb301","observation_id":"70b730e6-c6ea-44dd-a019-99e2bb09f793","resolution":{"observed_at":"2026-07-30T10:56:48.139137Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2112.09118","last_updated":"2022-08-29T12:17:32Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2021-12-16T18:57:37Z","title":"Unsupervised Dense Information Retrieval with Contrastive Learning","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2112.09118","snapshot_observed_at":"2026-07-30T10:56:48.144011Z","title":"Unsupervised dense information retrieval with con- trastive learning,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.23838","last_updated":"2026-07-26T20:52:23Z","snapshot_observed_at":"2026-08-05T00:15:21.105413Z","submitted_at":"2026-07-26T20:52:23Z","title":"TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-07-30T10:56:48.144011Z"},"links":{"cited_paper":"/paper/2112.09118","citing_paper":"/paper/2607.23838"},"observation_digest":"sha256:fcf4858c07789b6d6d0562d1f44ad9b852289d32a62ea7c1fa3dda659e1d0785","observation_id":"ec7f8b21-5958-4bfe-be0b-7dc38b343b7c","resolution":{"observed_at":"2026-07-30T10:56:48.144011Z","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":"2026-07-30T10:56:48.148626Z","title":"Approximate nearest neighbor negative contrastive learning for dense text retrieval,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.23838","last_updated":"2026-07-26T20:52:23Z","snapshot_observed_at":"2026-08-05T00:15:21.105413Z","submitted_at":"2026-07-26T20:52:23Z","title":"TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-07-30T10:56:48.148626Z"},"links":{"citing_paper":"/paper/2607.23838"},"observation_digest":"sha256:e78f08400d3461cf419e480b19e9d611035801e2d4d8164fb86b0f2051931345","observation_id":"3cfa86c3-7dc1-45c5-9f68-3be40958d1f5","resolution":{"observed_at":"2026-07-30T10:56:48.148626Z","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":"2026-07-30T10:56:48.152701Z","title":"The probabilistic relevance framework: BM25 and beyond,","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2607.23838","last_updated":"2026-07-26T20:52:23Z","snapshot_observed_at":"2026-08-05T00:15:21.105413Z","submitted_at":"2026-07-26T20:52:23Z","title":"TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-07-30T10:56:48.152701Z"},"links":{"citing_paper":"/paper/2607.23838"},"observation_digest":"sha256:ae7d2bdeb8e23eaa160ca9ddd2b68400d851a0679b910331af968fc3deeccd5f","observation_id":"c81475a1-4d4a-49fb-bdd0-a5abddf8689d","resolution":{"observed_at":"2026-07-30T10:56:48.152701Z","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":"2026-07-30T10:56:48.156828Z","title":"BEIR: A heterogeneous benchmark for zero-shot evaluation of infor- mation retrieval models,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.23838","last_updated":"2026-07-26T20:52:23Z","snapshot_observed_at":"2026-08-05T00:15:21.105413Z","submitted_at":"2026-07-26T20:52:23Z","title":"TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-07-30T10:56:48.156828Z"},"links":{"citing_paper":"/paper/2607.23838"},"observation_digest":"sha256:2f115287d061e71c6be9bac64cc76a6c9fd49f55d1e33788468f40246fd6250f","observation_id":"9ef3a9f1-8071-497a-9a29-4fe59ca6bfd3","resolution":{"observed_at":"2026-07-30T10:56:48.156828Z","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":"2026-07-30T10:56:48.160912Z","title":"Machine learning with adversaries: Byzantine tolerant gradient descent,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.23838","last_updated":"2026-07-26T20:52:23Z","snapshot_observed_at":"2026-08-05T00:15:21.105413Z","submitted_at":"2026-07-26T20:52:23Z","title":"TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-07-30T10:56:48.160912Z"},"links":{"citing_paper":"/paper/2607.23838"},"observation_digest":"sha256:84775331cc4c72e41076e8904f69f236afcafe11e7bd61c83bcc0c8ed93bee6d","observation_id":"d373f52e-34c9-4470-acb9-f6489e8f8416","resolution":{"observed_at":"2026-07-30T10:56:48.160912Z","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":"2026-07-30T10:56:48.165390Z","title":"Byzantine-robust distributed learning: Towards optimal statistical rates,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.23838","last_updated":"2026-07-26T20:52:23Z","snapshot_observed_at":"2026-08-05T00:15:21.105413Z","submitted_at":"2026-07-26T20:52:23Z","title":"TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-07-30T10:56:48.165390Z"},"links":{"citing_paper":"/paper/2607.23838"},"observation_digest":"sha256:c3ac070ba1b2ab965fecf915a439403fa5103c1ac2b5451941057bc34390b359","observation_id":"9f147973-fd66-4b21-891b-31032c124f7e","resolution":{"observed_at":"2026-07-30T10:56:48.165390Z","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":"2026-07-30T10:56:48.169371Z","title":"The hidden vul- nerability of distributed learning in Byzantium,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.23838","last_updated":"2026-07-26T20:52:23Z","snapshot_observed_at":"2026-08-05T00:15:21.105413Z","submitted_at":"2026-07-26T20:52:23Z","title":"TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-07-30T10:56:48.169371Z"},"links":{"citing_paper":"/paper/2607.23838"},"observation_digest":"sha256:8b4d37831e55f0a3585aa8ce395efc27c34f07d6a1be0710818f8cb92d551ecb","observation_id":"da3fb2a6-d82b-4af1-a8b0-dd1d549df9c1","resolution":{"observed_at":"2026-07-30T10:56:48.169371Z","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":"2026-07-30T10:56:48.173608Z","title":"Distributed statistical machine learning in adversarial settings: Byzantine gradient descent,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.23838","last_updated":"2026-07-26T20:52:23Z","snapshot_observed_at":"2026-08-05T00:15:21.105413Z","submitted_at":"2026-07-26T20:52:23Z","title":"TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-07-30T10:56:48.173608Z"},"links":{"citing_paper":"/paper/2607.23838"},"observation_digest":"sha256:b4b3801d375300ce3618f14f271c7b1825283959790198ee3841df405d9f1a15","observation_id":"594f06a7-30e3-480d-9c0e-b2a5eac7f6fd","resolution":{"observed_at":"2026-07-30T10:56:48.173608Z","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":"2026-07-30T10:56:48.179154Z","title":"FLTrust: Byzantine- robust federated learning via trust bootstrapping,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.23838","last_updated":"2026-07-26T20:52:23Z","snapshot_observed_at":"2026-08-05T00:15:21.105413Z","submitted_at":"2026-07-26T20:52:23Z","title":"TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-07-30T10:56:48.179154Z"},"links":{"citing_paper":"/paper/2607.23838"},"observation_digest":"sha256:8420617c710eff30be28f4cb275b1688a2b2d43119395a9f2c667be77b147f18","observation_id":"1e67a15e-fe5e-44a3-ae45-5c4ab8bcf028","resolution":{"observed_at":"2026-07-30T10:56:48.179154Z","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":"2026-07-30T10:56:48.183785Z","title":"Efficient and robust approxi- mate nearest neighbor search using hierarchical navigable small world graphs,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.23838","last_updated":"2026-07-26T20:52:23Z","snapshot_observed_at":"2026-08-05T00:15:21.105413Z","submitted_at":"2026-07-26T20:52:23Z","title":"TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-07-30T10:56:48.183785Z"},"links":{"citing_paper":"/paper/2607.23838"},"observation_digest":"sha256:7c65ae5665256d8706a2225263e929aa63eebf835384e10523f042b2202c616d","observation_id":"745c57ad-0c86-4afd-9463-1f5a3fd9b97b","resolution":{"observed_at":"2026-07-30T10:56:48.183785Z","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":"2026-07-30T10:56:48.188911Z","title":"Product quantization for nearest neighbor search,","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2607.23838","last_updated":"2026-07-26T20:52:23Z","snapshot_observed_at":"2026-08-05T00:15:21.105413Z","submitted_at":"2026-07-26T20:52:23Z","title":"TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-07-30T10:56:48.188911Z"},"links":{"citing_paper":"/paper/2607.23838"},"observation_digest":"sha256:8677456d48a070cab18fadbd9336b5ed7148c829c0c1c69495fc7a5374d39867","observation_id":"d5c15f7c-95c2-4507-9822-ce4fa2857076","resolution":{"observed_at":"2026-07-30T10:56:48.188911Z","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":"2026-07-30T10:56:48.193157Z","title":"Natural Questions: A benchmark for question answering research,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.23838","last_updated":"2026-07-26T20:52:23Z","snapshot_observed_at":"2026-08-05T00:15:21.105413Z","submitted_at":"2026-07-26T20:52:23Z","title":"TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-07-30T10:56:48.193157Z"},"links":{"citing_paper":"/paper/2607.23838"},"observation_digest":"sha256:bb86c0f5a02aaa537e764a512fcc9d3a629e819c9019ab96ec2cb457831de9d7","observation_id":"f12dcd3c-5ccb-4b9e-b867-be102f3d8a10","resolution":{"observed_at":"2026-07-30T10:56:48.193157Z","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":"2026-07-30T10:56:48.197292Z","title":"HotpotQA: A dataset for diverse, explainable multi-hop question answering,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.23838","last_updated":"2026-07-26T20:52:23Z","snapshot_observed_at":"2026-08-05T00:15:21.105413Z","submitted_at":"2026-07-26T20:52:23Z","title":"TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-07-30T10:56:48.197292Z"},"links":{"citing_paper":"/paper/2607.23838"},"observation_digest":"sha256:c48dd69ed2bc8e2fbacf10affb5f5c58603f4da1299c6fb44d3a3f146324e402","observation_id":"eca42611-fef9-4e8f-ad10-ab75d945df62","resolution":{"observed_at":"2026-07-30T10:56:48.197292Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1611.09268","last_updated":"2018-10-31T14:46:47Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2016-11-28T18:14:11Z","title":"MS MARCO: A Human Generated MAchine Reading COmprehension Dataset","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1611.09268","snapshot_observed_at":"2026-07-30T10:56:48.201295Z","title":"MS MARCO: A human-generated machine reading comprehension dataset,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2607.23838","last_updated":"2026-07-26T20:52:23Z","snapshot_observed_at":"2026-08-05T00:15:21.105413Z","submitted_at":"2026-07-26T20:52:23Z","title":"TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-07-30T10:56:48.201295Z"},"links":{"cited_paper":"/paper/1611.09268","citing_paper":"/paper/2607.23838"},"observation_digest":"sha256:ad96849bd5422b8c517dc509de04e1471a9d93225a89f18b9001aeaa5e90926b","observation_id":"42ce52f1-3874-4c42-a5b6-630a2969330b","resolution":{"observed_at":"2026-07-30T10:56:48.201295Z","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":"2026-07-30T10:56:48.206120Z","title":"MPNet: Masked and permuted pre-training for language understanding,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.23838","last_updated":"2026-07-26T20:52:23Z","snapshot_observed_at":"2026-08-05T00:15:21.105413Z","submitted_at":"2026-07-26T20:52:23Z","title":"TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-07-30T10:56:48.206120Z"},"links":{"citing_paper":"/paper/2607.23838"},"observation_digest":"sha256:4ddab05325f918eca146dbeb3bc3fd5a436a1e7ef8aac48a1e0857cb45eaab18","observation_id":"63eac46f-8f0b-439f-8049-e19d75c9d4c5","resolution":{"observed_at":"2026-07-30T10:56:48.206120Z","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":"2026-07-30T10:56:48.210449Z","title":"BERT: Pre-training of deep bidirectional transformers for language understanding,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.23838","last_updated":"2026-07-26T20:52:23Z","snapshot_observed_at":"2026-08-05T00:15:21.105413Z","submitted_at":"2026-07-26T20:52:23Z","title":"TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-07-30T10:56:48.210449Z"},"links":{"citing_paper":"/paper/2607.23838"},"observation_digest":"sha256:4087b27779ea8598515aa4809f052fd86aba33659a39e324ae6a10bd84f752fc","observation_id":"bb78122b-43fd-46b5-a697-e14a7156bf25","resolution":{"observed_at":"2026-07-30T10:56:48.210449Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.08281","last_updated":"2025-10-23T09:36:08Z","snapshot_observed_at":"2026-07-31T05:45:37.385210Z","submitted_at":"2024-01-16T11:12:36Z","title":"The Faiss library","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.08281","snapshot_observed_at":"2026-07-30T10:56:48.214716Z","title":"The Faiss library,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.23838","last_updated":"2026-07-26T20:52:23Z","snapshot_observed_at":"2026-08-05T00:15:21.105413Z","submitted_at":"2026-07-26T20:52:23Z","title":"TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-07-30T10:56:48.214716Z"},"links":{"cited_paper":"/paper/2401.08281","citing_paper":"/paper/2607.23838"},"observation_digest":"sha256:0cceff2c058c074a27c8ae750004fc13d0a45880cfa2230405d31133c21bb3d1","observation_id":"190f8434-b261-43c7-98f9-fb4b2a21efb2","resolution":{"observed_at":"2026-07-30T10:56:48.214716Z","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":"2026-07-30T10:56:48.219172Z","title":"Milvus: A purpose-built vector data management system,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.23838","last_updated":"2026-07-26T20:52:23Z","snapshot_observed_at":"2026-08-05T00:15:21.105413Z","submitted_at":"2026-07-26T20:52:23Z","title":"TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-07-30T10:56:48.219172Z"},"links":{"citing_paper":"/paper/2607.23838"},"observation_digest":"sha256:5f55e7cd3b2f4f067a618eae0471b7b4f6b5ca034d36e3289609c81e9fe92383","observation_id":"ab7716de-4149-441a-8a2d-7446cab7e207","resolution":{"observed_at":"2026-07-30T10:56:48.219172Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.14021","last_updated":"2023-10-21T14:09:48Z","snapshot_observed_at":"2026-08-05T16:24:13.936533Z","submitted_at":"2023-10-21T14:09:48Z","title":"Survey of Vector Database Management Systems","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.14021","snapshot_observed_at":"2026-07-30T10:56:48.223099Z","title":"Survey of vector database management systems,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.23838","last_updated":"2026-07-26T20:52:23Z","snapshot_observed_at":"2026-08-05T00:15:21.105413Z","submitted_at":"2026-07-26T20:52:23Z","title":"TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-07-30T10:56:48.223099Z"},"links":{"cited_paper":"/paper/2310.14021","citing_paper":"/paper/2607.23838"},"observation_digest":"sha256:acee74edab35447b3ecf2483d2bff2411d47980020adb9d3da28fdbcc51371d6","observation_id":"d8131fc9-f083-4d85-bdb7-cc9d4d3d7158","resolution":{"observed_at":"2026-07-30T10:56:48.223099Z","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":"2026-07-30T10:56:48.227998Z","title":"RAGPart & RAGMask: Retrieval-stage defenses against corpus poi- soning in retrieval-augmented generation,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.23838","last_updated":"2026-07-26T20:52:23Z","snapshot_observed_at":"2026-08-05T00:15:21.105413Z","submitted_at":"2026-07-26T20:52:23Z","title":"TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-07-30T10:56:48.227998Z"},"links":{"citing_paper":"/paper/2607.23838"},"observation_digest":"sha256:5eb8bec58b1c827768c4b047aa4338b9f8ddd76572c5b87e7c7111e8d99e7f7c","observation_id":"85c7b8db-690a-427d-bf1e-32fd6b72e00d","resolution":{"observed_at":"2026-07-30T10:56:48.227998Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.23838","last_updated":"2026-07-26T20:52:23Z","latest_version":1,"primary_category":"cs.CR","snapshot_observed_at":"2026-08-05T00:15:21.105413Z","submitted_at":"2026-07-26T20:52:23Z","title":"TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation"},"reference_resolution":{"displayed":40,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":40,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":40},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2607.23838."}