Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-07-11T09:17:31.040524Z
Paper Citation Record · LEDGER
As of 7 August 2026, this Paper Citation Record lists 88 of 88 outbound references and 1 inbound Pith citation observation for arXiv:2607.05069.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-07-11T09:17:31.040524Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-07-14T09:11:36.225135Z
A source-named dated measurement, never combined with another source.
Source: cited_works
88 of 88 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 7a07bf6a-ad3c-4aed-af25-7baae85cb28b · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution Retrieval-Augmented Generation for
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Observation db0b4299-3b26-4743-9cd8-4f9cf81e8cfd · outbound
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Observation bacd9a48-3afd-4640-a8b9-2458b2c010ec · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , series =
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Observation a4bd67d4-3908-4fb6-b806-063df9550800 · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution ArXiv preprint , volume =
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Observation d89a14cd-87db-43af-8d76-45b69ac52cc1 · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) , series =
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Observation 58ad9662-0b9a-4c5c-9000-cc5dfedcfdb5 · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution Findings of the Association for Computational Linguistics: EMNLP 2023 , series =
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Observation 4c6083c1-eb3d-46e3-853f-ca2772fbb024 · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution and Smith, Noah A
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Observation 9f9a64eb-38d0-4e3b-9d89-a51b9747c257 · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution Findings of the Association for Computational Linguistics: ACL 2024 , series =
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Observation 64fc69b2-dbca-4095-a7f9-b4de3b9f5ec4 · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution Findings of the Association for Computational Linguistics: EMNLP 2023 , series =
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Observation f978ebef-0721-4cd3-8f3f-d09b2b08cffe · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution Findings of the Association for Computational Linguistics: NAACL 2024 , series =
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Observation 5c3f1595-ff66-4068-9660-2800b0db1c2f · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution Findings of the Association for Computational Linguistics: NAACL 2024 , series =
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Observation 798ecb12-31e4-4f30-be0f-c8f0287df02f · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution ArXiv preprint , volume =
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Observation 181b7a4f-8df3-48c0-a154-45dfabe9f653 · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution 2020 , publisher =
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Observation f053dcfd-2d1a-4ce7-a45b-1de79fe3c64f · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , series =
Reference 14
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Observation 2ce4d5da-04a4-469c-8506-1ce98d4237c9 · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution On the Structural Memory of
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Observation 00715289-b1ef-42ee-87c4-f226db0cba8f · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution Proceedings of the International Conference on Learning Representations , series =
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Observation 846de73a-8fd8-4309-a8e4-7829d3afafa3 · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , series =
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Unavailable: canonical work link unavailable.
Observation ef5e92f3-5e44-4a25-880c-a462377f7468 · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution ArXiv preprint , volume =
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Observation 9a73ed8f-75e1-4956-a5b4-b8bd758412c4 · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution Findings of the Association for Computational Linguistics: ACL 2024 , series =
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Observation 9954cb3c-4e85-465b-adce-879d6e43b4bb · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , series =
Reference 20
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Unavailable: canonical work link unavailable.
Observation 3c5e1037-9a66-4964-9a5e-65e739038942 · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution Advances in Neural Information Processing Systems , series =
Reference 21
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Observation 75d556cf-d1a3-4e07-a9d2-a3a23494ea8c · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution Proceedings of the Conference on Language Modeling , series =
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Observation 24cd9ad6-4699-439b-bf2e-1403497b33ad · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution and Hashimoto, Tatsunori B
Reference 23
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Unavailable: canonical work link unavailable.
Observation ba65945b-50f0-4562-bc5d-b34e5c3d3a93 · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing , series =
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Observation 3bb0618b-cfb1-4d11-b1ea-c3b59b113944 · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution ArXiv preprint , volume =
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Observation c25c3c79-3e52-4925-9ef5-fbec991401da · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution 2023 , publisher =
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Observation 81dd4382-0425-4bd9-8632-e502d491caa3 · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution Self-Alignment for Factuality: Mitigating Hallucinations in
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Unavailable: canonical work link unavailable.
Observation 422ea3c0-f22d-4b0d-b42c-704f3538c0b1 · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution Findings of the Association for Computational Linguistics: EMNLP 2024 , series =
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Unavailable: canonical work link unavailable.
Observation 68236428-7dcc-4246-a5b0-fb775217eb02 · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , series =
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MIRAGE: Defending Long-Form RAG Against Misinformation Pollution Findings of the Association for Computational Linguistics: EMNLP 2024 , series =
Reference 30
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Observation f6c1e5dc-6fd6-4189-b460-b1bf86834235 · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution Length-Controlled
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Observation a140693f-f411-4b1e-9582-236c2dc34dd4 · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution Retrieval-Augmented Generation for Knowledge-Intensive
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Unavailable: canonical work link unavailable.
Observation 2353cc0d-8f21-4ce4-be3b-61b9d10b1d17 · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution Proceedings of the 37th International Conference on Machine Learning , series =
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Observation f1226489-a4a9-445d-8eda-62abbb4c044c · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution ArXiv preprint , volume =
Reference 34
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Observation 4e0c46ae-1349-489e-b77a-de29b7bfaf0c · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing , series =
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Observation 5d5a61db-d2fb-4a2a-8385-aa36ed93de41 · outbound
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Observation 95fec5b3-918d-4662-81f1-febe26ea924d · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , series =
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Observation c2ccc5de-c3e9-4f0c-98d5-e49ed0e27944 · outbound
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Observation 5f796948-25ea-4827-8a36-1b72627b6184 · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution Certifiably Robust
Reference 39
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Observation 421dc119-9000-4ae9-a02d-e9dc93633997 · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics , series =
Reference 40
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Observation 7ff744b3-4944-4973-8c34-0888f63102e7 · outbound
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Observation 693bf6ae-e041-49ff-8285-af4f5bed2b75 · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution Proceedings of the Conference on Language Modeling , series =
Reference 42
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Observation a6f9d253-2838-446f-b5bd-d6febaf868cd · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution , editor =
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Observation 563a68c9-2d80-4889-af87-ee1b81ae41e0 · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution Findings of the Association for Computational Linguistics: ACL 2023 , series =
Reference 44
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Observation 628c0384-14b9-4a15-85e0-1e148a271a4c · outbound
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Observation da4b4bd3-4c1a-4e6f-8d4c-5768568afdb1 · outbound
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Observation 9ecac441-c187-4062-b8f2-e9679e57e6b0 · outbound
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Observation e52fe096-da0d-442e-83e8-c471ab37c4c5 · outbound
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Reference 48
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Observation 50be28b6-e64a-4059-86e4-2cb1ad61d007 · outbound
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Reference 49
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Observation cf44ebed-3fb0-442f-a02d-1799552f3c19 · outbound
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Observation adbfff8d-a914-43be-acd2-a319882404ab · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution 2025 , eprint =
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Observation 1e99ff86-8ce5-478d-9088-a855c1e15e53 · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution 2019 , eprint =
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Observation f576e9bc-233e-4587-88d6-a6e991f63310 · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics , series =
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Observation b4f88cc8-659f-49b2-ab2c-b241792d3d01 · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution Findings of the Association for Computational Linguistics: EMNLP 2025 , series =
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Observation 9a26b0e5-acd0-4ed7-b811-8f0eb8e5360f · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution Findings of the Association for Computational Linguistics: EMNLP 2025 , series =
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Observation 6ead5ad8-c92b-41a6-a929-4dfdf6280720 · outbound
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Reference 58
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Observation 2f1cd032-bc91-4dd3-bda4-eba55879e9a8 · outbound
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution Trust Before Fusion:
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Observation 1a11d036-f849-419f-a327-f7c4dc4af20f · outbound
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Observation 54921353-21fb-4e1f-be6b-8aa7e0142e71 · outbound
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Observation 84db175a-c3de-4020-8988-cf5ddc5ea714 · outbound
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Observation 27feb0e5-a0a5-4631-8105-c494c5d6dc1d · outbound
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Observation b8602020-1bac-4b0e-99bc-54c1b02f7b14 · outbound
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