{"as_of":"2026-08-08T11:39:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:0ed677e6fbae1cdbde7e9ee6b79c0ef1124c9bd7fa3e1b755c155bcd897bc9dc","coverage":[{"denominator":25,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":25,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-01T03:16:00.728744Z","state":"measured"},{"denominator":25,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":25,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+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/2607.27692/citation-record","integrity":"/paper/2607.27692/integrity","json":"/paper/2607.27692/citation-record.json","paper":"/paper/2607.27692"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T03:15:59.628770Z","title":"Fu and Stefano Ermon and Atri Rudra and Christopher R","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.27692","last_updated":"2026-07-30T05:25:23Z","snapshot_observed_at":"2026-08-07T17:40:33.901477Z","submitted_at":"2026-07-30T05:25:23Z","title":"Recall Before You Rank: Similarity-Guided Top-$K$ Reuse for Efficient Long-Context Attention","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-01T03:15:59.628770Z"},"links":{"citing_paper":"/paper/2607.27692"},"observation_digest":"sha256:1b156210cecd206c410df1ccd4af488293c924a5d18e31e9b1201a7b0b603d1e","observation_id":"2ab4ef15-ec06-4dc4-ac15-9fa17c85f1db","resolution":{"observed_at":"2026-08-01T03:15:59.628770Z","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":"2026-08-01T03:15:59.721684Z","title":"International Conference on Learning Representations , year =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.27692","last_updated":"2026-07-30T05:25:23Z","snapshot_observed_at":"2026-08-07T17:40:33.901477Z","submitted_at":"2026-07-30T05:25:23Z","title":"Recall Before You Rank: Similarity-Guided Top-$K$ Reuse for Efficient Long-Context Attention","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-01T03:15:59.721684Z"},"links":{"citing_paper":"/paper/2607.27692"},"observation_digest":"sha256:f552c124f0a89a7f8be8426b4066476cfb4d43c9450a28494b06ff5971580ffb","observation_id":"4dbd06a6-a0d9-4260-819c-33d476ffa64b","resolution":{"observed_at":"2026-08-01T03:15:59.721684Z","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":"2026-08-01T03:15:59.845311Z","title":"Advances in Neural Information Processing Systems , volume =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.27692","last_updated":"2026-07-30T05:25:23Z","snapshot_observed_at":"2026-08-07T17:40:33.901477Z","submitted_at":"2026-07-30T05:25:23Z","title":"Recall Before You Rank: Similarity-Guided Top-$K$ Reuse for Efficient Long-Context Attention","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-01T03:15:59.845311Z"},"links":{"citing_paper":"/paper/2607.27692"},"observation_digest":"sha256:dcb7f7bf7e57f1f2a628dd8aefe444c4d026131032b607ec00963f2ac74b8963","observation_id":"47ebabf0-1963-4f7e-911d-25a19a419c74","resolution":{"observed_at":"2026-08-01T03:15:59.845311Z","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":"2026-08-01T03:15:59.957191Z","title":"Advances in Neural Information Processing Systems , volume =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.27692","last_updated":"2026-07-30T05:25:23Z","snapshot_observed_at":"2026-08-07T17:40:33.901477Z","submitted_at":"2026-07-30T05:25:23Z","title":"Recall Before You Rank: Similarity-Guided Top-$K$ Reuse for Efficient Long-Context Attention","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-01T03:15:59.957191Z"},"links":{"citing_paper":"/paper/2607.27692"},"observation_digest":"sha256:901cb9bf0f17c393c8fa1034f19d6a27cd8eb51cd3ced83f2199f7bdeea02552","observation_id":"dceae0d5-4cb8-411f-a13a-9a0453f7283b","resolution":{"observed_at":"2026-08-01T03:15:59.957191Z","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":"2026-08-01T03:16:00.061572Z","title":"Second Conference on Language Modeling , year =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.27692","last_updated":"2026-07-30T05:25:23Z","snapshot_observed_at":"2026-08-07T17:40:33.901477Z","submitted_at":"2026-07-30T05:25:23Z","title":"Recall Before You Rank: Similarity-Guided Top-$K$ Reuse for Efficient Long-Context Attention","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-01T03:16:00.061572Z"},"links":{"citing_paper":"/paper/2607.27692"},"observation_digest":"sha256:417b4226106afc720a8fb07093bb08dc9647197b25554549e64f91960f75b017","observation_id":"b4c93835-dc42-4640-b128-761db8a532a9","resolution":{"observed_at":"2026-08-01T03:16:00.061572Z","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":"2026-08-01T03:16:00.162908Z","title":"Proceedings of the 41st International Conference on Machine Learning , series =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.27692","last_updated":"2026-07-30T05:25:23Z","snapshot_observed_at":"2026-08-07T17:40:33.901477Z","submitted_at":"2026-07-30T05:25:23Z","title":"Recall Before You Rank: Similarity-Guided Top-$K$ Reuse for Efficient Long-Context Attention","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-01T03:16:00.162908Z"},"links":{"citing_paper":"/paper/2607.27692"},"observation_digest":"sha256:79ba1e7df754ab99a6c6e198191682ab4e547b8df6b6b3431b0d3bcb1726b46c","observation_id":"2dc72fea-a4fe-4c0c-8570-3c614d5703b2","resolution":{"observed_at":"2026-08-01T03:16:00.162908Z","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":"2026-08-01T03:16:00.274052Z","title":"Proceedings of the 41st International Conference on Machine Learning , series =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.27692","last_updated":"2026-07-30T05:25:23Z","snapshot_observed_at":"2026-08-07T17:40:33.901477Z","submitted_at":"2026-07-30T05:25:23Z","title":"Recall Before You Rank: Similarity-Guided Top-$K$ Reuse for Efficient Long-Context Attention","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-01T03:16:00.274052Z"},"links":{"citing_paper":"/paper/2607.27692"},"observation_digest":"sha256:a6f10cdf18a7668371c320fa9f6e3d6a32cb02409e62d5a12104344975ebac35","observation_id":"87a2c056-ae50-4283-9446-5e12a0f589ea","resolution":{"observed_at":"2026-08-01T03:16:00.274052Z","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":"2026-08-01T03:16:00.511168Z","title":"Rae and Anna Potapenko and Siddhant M","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.27692","last_updated":"2026-07-30T05:25:23Z","snapshot_observed_at":"2026-08-07T17:40:33.901477Z","submitted_at":"2026-07-30T05:25:23Z","title":"Recall Before You Rank: Similarity-Guided Top-$K$ Reuse for Efficient Long-Context Attention","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-01T03:16:00.511168Z"},"links":{"citing_paper":"/paper/2607.27692"},"observation_digest":"sha256:7f4cdbcc70517a19a688b91ae27f3286d0022fa9438b3d950b695ed2e5bcc8f6","observation_id":"851867ad-93dc-43ec-8f53-fbf2c53b0314","resolution":{"observed_at":"2026-08-01T03:16:00.511168Z","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":"2026-08-01T03:16:00.664841Z","title":"Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.27692","last_updated":"2026-07-30T05:25:23Z","snapshot_observed_at":"2026-08-07T17:40:33.901477Z","submitted_at":"2026-07-30T05:25:23Z","title":"Recall Before You Rank: Similarity-Guided Top-$K$ Reuse for Efficient Long-Context Attention","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-01T03:16:00.664841Z"},"links":{"citing_paper":"/paper/2607.27692"},"observation_digest":"sha256:b4d5ae7b7ccc7aff2aa08cc43d5cba621cf5eb360d99a7dd330d93eb51f28a7d","observation_id":"c0e3e9e6-90e0-48d7-b9e7-1e17c10dcd22","resolution":{"observed_at":"2026-08-01T03:16:00.664841Z","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":"2026-08-01T03:16:00.684562Z","title":"First Conference on Language Modeling , year =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.27692","last_updated":"2026-07-30T05:25:23Z","snapshot_observed_at":"2026-08-07T17:40:33.901477Z","submitted_at":"2026-07-30T05:25:23Z","title":"Recall Before You Rank: Similarity-Guided Top-$K$ Reuse for Efficient Long-Context Attention","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-01T03:16:00.684562Z"},"links":{"citing_paper":"/paper/2607.27692"},"observation_digest":"sha256:657c34862f2b420e1103177b52dd740bb5ff8cea15fd3bc0946aee596c64ed1d","observation_id":"b1f5872d-a4ee-4bfc-9c5e-0c02b5c1a491","resolution":{"observed_at":"2026-08-01T03:16:00.684562Z","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":"2026-08-01T03:16:00.687695Z","title":"Advances in Neural Information Processing Systems , volume =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.27692","last_updated":"2026-07-30T05:25:23Z","snapshot_observed_at":"2026-08-07T17:40:33.901477Z","submitted_at":"2026-07-30T05:25:23Z","title":"Recall Before You Rank: Similarity-Guided Top-$K$ Reuse for Efficient Long-Context Attention","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-01T03:16:00.687695Z"},"links":{"citing_paper":"/paper/2607.27692"},"observation_digest":"sha256:b780255180892eb701436bfe8d4a6aba47fe8c7e11589bf7ab3573aca9239f2a","observation_id":"3271bafc-6754-4eb2-af8f-a8147012ab08","resolution":{"observed_at":"2026-08-01T03:16:00.687695Z","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":"2026-08-01T03:16:00.690573Z","title":"Abdi and Dongsheng Li and Chin-Yew Lin and Yuqing Yang and Lili Qiu , title =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.27692","last_updated":"2026-07-30T05:25:23Z","snapshot_observed_at":"2026-08-07T17:40:33.901477Z","submitted_at":"2026-07-30T05:25:23Z","title":"Recall Before You Rank: Similarity-Guided Top-$K$ Reuse for Efficient Long-Context Attention","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-01T03:16:00.690573Z"},"links":{"citing_paper":"/paper/2607.27692"},"observation_digest":"sha256:b22bb7e3f8da7ed40939f742553922576abb252187d276b898378d33c7049bdc","observation_id":"7bf59ca7-97c6-404c-8bac-f06c4c8ba205","resolution":{"observed_at":"2026-08-01T03:16:00.690573Z","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":"2026-08-01T03:16:00.693677Z","title":"Advances in Neural Information Processing Systems , volume =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.27692","last_updated":"2026-07-30T05:25:23Z","snapshot_observed_at":"2026-08-07T17:40:33.901477Z","submitted_at":"2026-07-30T05:25:23Z","title":"Recall Before You Rank: Similarity-Guided Top-$K$ Reuse for Efficient Long-Context Attention","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-01T03:16:00.693677Z"},"links":{"citing_paper":"/paper/2607.27692"},"observation_digest":"sha256:bb2bedbccc6ac37a744a9e04c56b08bab53407a736b5ee2b8b00bb9e8a2b856c","observation_id":"3e01394f-c140-40fc-a518-d10170a628b7","resolution":{"observed_at":"2026-08-01T03:16:00.693677Z","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":"2026-08-01T03:16:00.696431Z","title":"Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing , pages =","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.27692","last_updated":"2026-07-30T05:25:23Z","snapshot_observed_at":"2026-08-07T17:40:33.901477Z","submitted_at":"2026-07-30T05:25:23Z","title":"Recall Before You Rank: Similarity-Guided Top-$K$ Reuse for Efficient Long-Context Attention","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-01T03:16:00.696431Z"},"links":{"citing_paper":"/paper/2607.27692"},"observation_digest":"sha256:bd88ca22ec7ec9889ba22187495dc00ffb5f59cc94be458dc8ffa684165b73ef","observation_id":"100bebf8-b013-4374-87f8-a9a8f261d421","resolution":{"observed_at":"2026-08-01T03:16:00.696431Z","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":"2026-08-01T03:16:00.699225Z","title":"International Conference on Learning Representations , year =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.27692","last_updated":"2026-07-30T05:25:23Z","snapshot_observed_at":"2026-08-07T17:40:33.901477Z","submitted_at":"2026-07-30T05:25:23Z","title":"Recall Before You Rank: Similarity-Guided Top-$K$ Reuse for Efficient Long-Context Attention","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-01T03:16:00.699225Z"},"links":{"citing_paper":"/paper/2607.27692"},"observation_digest":"sha256:b3df0a69c43cc1e19b3e99e82b3c75bc3659fcf16b7d85dfddd45125a3f4459e","observation_id":"a8992d4f-21cf-4e47-aa5f-c5d2eb9ffc79","resolution":{"observed_at":"2026-08-01T03:16:00.699225Z","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":"2026-08-01T03:16:00.702223Z","title":"Advances in Neural Information Processing Systems , volume =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.27692","last_updated":"2026-07-30T05:25:23Z","snapshot_observed_at":"2026-08-07T17:40:33.901477Z","submitted_at":"2026-07-30T05:25:23Z","title":"Recall Before You Rank: Similarity-Guided Top-$K$ Reuse for Efficient Long-Context Attention","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-01T03:16:00.702223Z"},"links":{"citing_paper":"/paper/2607.27692"},"observation_digest":"sha256:b6599c846435fd5235fc62831c5d507655ae29863867c77b3e137117cff0b7b7","observation_id":"bf4f2920-02db-49ae-a977-3a384e3347c5","resolution":{"observed_at":"2026-08-01T03:16:00.702223Z","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":"2026-08-01T03:16:00.704760Z","title":"Mahoney and Kurt Keutzer and Amir Gholami , title =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.27692","last_updated":"2026-07-30T05:25:23Z","snapshot_observed_at":"2026-08-07T17:40:33.901477Z","submitted_at":"2026-07-30T05:25:23Z","title":"Recall Before You Rank: Similarity-Guided Top-$K$ Reuse for Efficient Long-Context Attention","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-01T03:16:00.704760Z"},"links":{"citing_paper":"/paper/2607.27692"},"observation_digest":"sha256:5659afc9e25741c8643adfea7c3e48ad50a9cfc365953b836a0802ecc89d7159","observation_id":"b9cfb101-c4a1-4b22-aa72-e32714c7f80d","resolution":{"observed_at":"2026-08-01T03:16:00.704760Z","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":"2026-08-01T03:16:00.707608Z","title":"International Conference on Learning Representations , year =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.27692","last_updated":"2026-07-30T05:25:23Z","snapshot_observed_at":"2026-08-07T17:40:33.901477Z","submitted_at":"2026-07-30T05:25:23Z","title":"Recall Before You Rank: Similarity-Guided Top-$K$ Reuse for Efficient Long-Context Attention","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-01T03:16:00.707608Z"},"links":{"citing_paper":"/paper/2607.27692"},"observation_digest":"sha256:f3533665ed7e4071d68caa36128633cc1764f9e93327a07f63482b95d6c3c732","observation_id":"18928cb4-0624-496d-b38b-ca67c6ca5275","resolution":{"observed_at":"2026-08-01T03:16:00.707608Z","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":"2026-08-01T03:16:00.711171Z","title":"Advances in Neural Information Processing Systems , volume =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.27692","last_updated":"2026-07-30T05:25:23Z","snapshot_observed_at":"2026-08-07T17:40:33.901477Z","submitted_at":"2026-07-30T05:25:23Z","title":"Recall Before You Rank: Similarity-Guided Top-$K$ Reuse for Efficient Long-Context Attention","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-01T03:16:00.711171Z"},"links":{"citing_paper":"/paper/2607.27692"},"observation_digest":"sha256:4bd311f596295d4562e237ff8ede5a99f5edc183e698192aa21901b6d4d39636","observation_id":"1fe13450-06ab-4852-a247-09cc54f880ab","resolution":{"observed_at":"2026-08-01T03:16:00.711171Z","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":"2026-08-01T03:16:00.713750Z","title":"arXiv preprint arXiv:2412.15115 , year =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.27692","last_updated":"2026-07-30T05:25:23Z","snapshot_observed_at":"2026-08-07T17:40:33.901477Z","submitted_at":"2026-07-30T05:25:23Z","title":"Recall Before You Rank: Similarity-Guided Top-$K$ Reuse for Efficient Long-Context Attention","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-01T03:16:00.713750Z"},"links":{"cited_paper":"/paper/2412.15115","citing_paper":"/paper/2607.27692"},"observation_digest":"sha256:e476839781bae3feb4998797984461e0f77062ef709f103b3f0073864ff5208e","observation_id":"ffe95f2f-1446-4cdb-9cfb-312e4d223407","resolution":{"observed_at":"2026-08-01T03:16:00.713750Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.15383","last_updated":"2025-01-26T03:47:25Z","snapshot_observed_at":"2026-07-31T01:49:29.562668Z","submitted_at":"2025-01-26T03:47:25Z","title":"Qwen2.5-1M Technical Report","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.15383","snapshot_observed_at":"2026-08-01T03:16:00.717109Z","title":"arXiv preprint arXiv:2501.15383 , year =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.27692","last_updated":"2026-07-30T05:25:23Z","snapshot_observed_at":"2026-08-07T17:40:33.901477Z","submitted_at":"2026-07-30T05:25:23Z","title":"Recall Before You Rank: Similarity-Guided Top-$K$ Reuse for Efficient Long-Context Attention","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-01T03:16:00.717109Z"},"links":{"cited_paper":"/paper/2501.15383","citing_paper":"/paper/2607.27692"},"observation_digest":"sha256:be74b456ea72c565eec2e603dc4f95cf88b068c8b431b30aabb20f46483f4028","observation_id":"2190ae60-f75b-4f09-9b8e-6341835856d4","resolution":{"observed_at":"2026-08-01T03:16:00.717109Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.21783","last_updated":"2024-11-23T23:27:33Z","snapshot_observed_at":"2026-07-06T18:55:11.576666Z","submitted_at":"2024-07-31T17:54:27Z","title":"The Llama 3 Herd of Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.21783","snapshot_observed_at":"2026-08-01T03:16:00.720266Z","title":"arXiv preprint arXiv:2407.21783 , year =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.27692","last_updated":"2026-07-30T05:25:23Z","snapshot_observed_at":"2026-08-07T17:40:33.901477Z","submitted_at":"2026-07-30T05:25:23Z","title":"Recall Before You Rank: Similarity-Guided Top-$K$ Reuse for Efficient Long-Context Attention","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-01T03:16:00.720266Z"},"links":{"cited_paper":"/paper/2407.21783","citing_paper":"/paper/2607.27692"},"observation_digest":"sha256:99cb62cc1264f42357b88b1a91e1d3ea9e01cf6f5a532a94ff6d9d4f4f96b697","observation_id":"e1f10915-945e-44c4-86b7-2e8aa4268d33","resolution":{"observed_at":"2026-08-01T03:16:00.720266Z","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":"2026-08-01T03:16:00.723048Z","title":"arXiv preprint arXiv:2512.16391 , year =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.27692","last_updated":"2026-07-30T05:25:23Z","snapshot_observed_at":"2026-08-07T17:40:33.901477Z","submitted_at":"2026-07-30T05:25:23Z","title":"Recall Before You Rank: Similarity-Guided Top-$K$ Reuse for Efficient Long-Context Attention","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-01T03:16:00.723048Z"},"links":{"citing_paper":"/paper/2607.27692"},"observation_digest":"sha256:615a3c9bcbb8c0b4635edec7f4bfdd616e50c29f024f68c453d1f09fddbdacf6","observation_id":"b155baae-52e4-47a4-84cb-6e83b59ee671","resolution":{"observed_at":"2026-08-01T03:16:00.723048Z","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":"2026-08-01T03:16:00.725727Z","title":"arXiv preprint arXiv:2603.12201 , year =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.27692","last_updated":"2026-07-30T05:25:23Z","snapshot_observed_at":"2026-08-07T17:40:33.901477Z","submitted_at":"2026-07-30T05:25:23Z","title":"Recall Before You Rank: Similarity-Guided Top-$K$ Reuse for Efficient Long-Context Attention","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-01T03:16:00.725727Z"},"links":{"citing_paper":"/paper/2607.27692"},"observation_digest":"sha256:bf17715c6f2087b68a7cac8d47531b537ebd8f8a31440fd66e943cef2878ba2f","observation_id":"74ec2415-5011-4437-af3e-8f9b395c3d4f","resolution":{"observed_at":"2026-08-01T03:16:00.725727Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2606.30389","last_updated":"2026-06-29T14:43:25Z","snapshot_observed_at":"2026-08-08T05:45:34.017287Z","submitted_at":"2026-06-29T14:43:25Z","title":"Predict, Reuse, and Repair: Accelerating Dynamic Sparse Attention for Long-Context LLM Decoding","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2606.30389","snapshot_observed_at":"2026-08-01T03:16:00.728744Z","title":"arXiv preprint arXiv:2606.30389 , year =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.27692","last_updated":"2026-07-30T05:25:23Z","snapshot_observed_at":"2026-08-07T17:40:33.901477Z","submitted_at":"2026-07-30T05:25:23Z","title":"Recall Before You Rank: Similarity-Guided Top-$K$ Reuse for Efficient Long-Context Attention","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-01T03:16:00.728744Z"},"links":{"cited_paper":"/paper/2606.30389","citing_paper":"/paper/2607.27692"},"observation_digest":"sha256:f96b3df6bb5daeb0802f1f3d1cfc195eb9c62b289264160a013352ce495384c9","observation_id":"5e1622d2-98b4-4cdd-ae13-bdc2e6edcb71","resolution":{"observed_at":"2026-08-01T03:16:00.728744Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.27692","last_updated":"2026-07-30T05:25:23Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-07T17:40:33.901477Z","submitted_at":"2026-07-30T05:25:23Z","title":"Recall Before You Rank: Similarity-Guided Top-$K$ Reuse for Efficient Long-Context Attention"},"reference_resolution":{"displayed":25,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":25,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":25},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 0 inbound Pith citation observations for arXiv:2607.27692."}