{"as_of":"2026-08-05T01:00:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:7f8227b2c67431b72a2a06154c494618435b5355dd2fce903bda22c4ac196309","coverage":[{"denominator":18,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":18,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-03T05:21:48.992677Z","state":"measured"},{"denominator":18,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":18,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-04T06:34:03.388597+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/2602.02827/citation-record","integrity":"/paper/2602.02827/integrity","json":"/paper/2602.02827/citation-record.json","paper":"/paper/2602.02827"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T05:21:47.061885Z","title":"and Bubeck, S","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2602.02827","last_updated":"2026-06-02T15:26:45Z","snapshot_observed_at":"2026-08-04T23:44:48.120786Z","submitted_at":"2026-02-02T21:27:01Z","title":"Col-Bandit: Query-Time Top-$K$ Estimation for Late-Interaction Retrieval","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-03T05:21:47.061885Z"},"links":{"citing_paper":"/paper/2602.02827"},"observation_digest":"sha256:951e48dff62231ea19afa4dac18b6eab82f19c6b72f15c456f7e90971a3f63c2","observation_id":"023de680-cc86-4e08-ac22-e064f74a25d3","resolution":{"observed_at":"2026-08-03T05:21:47.061885Z","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":"2026-08-03T05:21:48.992677Z","title":"This stage is the computational bottleneck","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2602.02827","last_updated":"2026-06-02T15:26:45Z","snapshot_observed_at":"2026-08-04T23:44:48.120786Z","submitted_at":"2026-02-02T21:27:01Z","title":"Col-Bandit: Query-Time Top-$K$ Estimation for Late-Interaction Retrieval","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-03T05:21:48.992677Z"},"links":{"citing_paper":"/paper/2602.02827"},"observation_digest":"sha256:be52f395a26fd8d19f2fcc54f2c346ba89afa00f722f7cfb9c65b01208b32278","observation_id":"4b3b38cd-f957-4bba-a6bb-cdac75526fc1","resolution":{"observed_at":"2026-08-03T05:21:48.992677Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.19504","last_updated":"2026-06-08T18:58:48Z","snapshot_observed_at":"2026-08-04T23:43:03.375891Z","submitted_at":"2024-05-29T20:40:20Z","title":"MUVERA: Multi-Vector Retrieval via Fixed Dimensional Encodings","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.19504","snapshot_observed_at":"2026-08-03T05:21:47.597342Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.02827","last_updated":"2026-06-02T15:26:45Z","snapshot_observed_at":"2026-08-04T23:44:48.120786Z","submitted_at":"2026-02-02T21:27:01Z","title":"Col-Bandit: Query-Time Top-$K$ Estimation for Late-Interaction Retrieval","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-03T05:21:47.597342Z"},"links":{"cited_paper":"/paper/2405.19504","citing_paper":"/paper/2602.02827"},"observation_digest":"sha256:974e943f366278fc46b7155107a787275611365fa47cadb25c30ad0c20a3a4cb","observation_id":"f59bb19b-3ffa-4b39-88b5-be007bfe5ebd","resolution":{"observed_at":"2026-08-03T05:21:47.597342Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2112.06540","last_updated":"2021-12-13T10:24:54Z","snapshot_observed_at":"2026-07-06T12:18:03.877754Z","submitted_at":"2021-12-13T10:24:54Z","title":"A Study on Token Pruning for ColBERT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2112.06540","snapshot_observed_at":"2026-08-03T05:21:48.161461Z","title":"A study on token pruning for colbert.arXiv preprint arXiv:2112.06540,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.02827","last_updated":"2026-06-02T15:26:45Z","snapshot_observed_at":"2026-08-04T23:44:48.120786Z","submitted_at":"2026-02-02T21:27:01Z","title":"Col-Bandit: Query-Time Top-$K$ Estimation for Late-Interaction Retrieval","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-03T05:21:48.161461Z"},"links":{"cited_paper":"/paper/2112.06540","citing_paper":"/paper/2602.02827"},"observation_digest":"sha256:60f2721ec624befde2ea4259e66bb717b441a9689e87138e67a220236886d486","observation_id":"eee88bab-2fd0-449f-b403-cfb82911b39a","resolution":{"observed_at":"2026-08-03T05:21:48.161461Z","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":"2026-08-03T05:21:48.228158Z","title":"PLAID: An efficient engine for late interaction retrieval","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2602.02827","last_updated":"2026-06-02T15:26:45Z","snapshot_observed_at":"2026-08-04T23:44:48.120786Z","submitted_at":"2026-02-02T21:27:01Z","title":"Col-Bandit: Query-Time Top-$K$ Estimation for Late-Interaction Retrieval","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-03T05:21:48.228158Z"},"links":{"citing_paper":"/paper/2602.02827"},"observation_digest":"sha256:15ae3eae3993d13cf0ef89f4b1f7be57eec171198b7880a1421ab46682737ce4","observation_id":"d5e46fcf-75ed-430a-8359-c6370dd29559","resolution":{"observed_at":"2026-08-03T05:21:48.228158Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.09723","last_updated":"2024-05-30T19:40:21Z","snapshot_observed_at":"2026-07-06T17:30:25.359458Z","submitted_at":"2024-02-15T05:31:13Z","title":"Efficient Prompt Optimization Through the Lens of Best Arm Identification","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.09723","snapshot_observed_at":"2026-08-03T05:21:48.328839Z","title":"Best arm identifi- cation for prompt learning under a limited budget.arXiv preprint arXiv:2402.09723,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.02827","last_updated":"2026-06-02T15:26:45Z","snapshot_observed_at":"2026-08-04T23:44:48.120786Z","submitted_at":"2026-02-02T21:27:01Z","title":"Col-Bandit: Query-Time Top-$K$ Estimation for Late-Interaction Retrieval","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-03T05:21:48.328839Z"},"links":{"cited_paper":"/paper/2402.09723","citing_paper":"/paper/2602.02827"},"observation_digest":"sha256:ac3d1912c6dd5e097282940744d1a86182aeaef15e87bee9a886e410326cc2c8","observation_id":"9dbe732f-da27-4bc7-ae40-744da8d66c7f","resolution":{"observed_at":"2026-08-03T05:21:48.328839Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.12342","last_updated":"2025-02-17T22:10:47Z","snapshot_observed_at":"2026-07-06T20:38:10.691943Z","submitted_at":"2025-02-17T22:10:47Z","title":"REAL-MM-RAG: A Real-World Multi-Modal Retrieval Benchmark","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.12342","snapshot_observed_at":"2026-08-03T05:21:48.563328Z","title":"R., Schwartz, E., Barzelay, U., and Karlinsky, L","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.02827","last_updated":"2026-06-02T15:26:45Z","snapshot_observed_at":"2026-08-04T23:44:48.120786Z","submitted_at":"2026-02-02T21:27:01Z","title":"Col-Bandit: Query-Time Top-$K$ Estimation for Late-Interaction Retrieval","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-03T05:21:48.563328Z"},"links":{"cited_paper":"/paper/2502.12342","citing_paper":"/paper/2602.02827"},"observation_digest":"sha256:edee36f01fdf13fd5d2d9baae205c8de32a7ae087beedb2bd5c9b20ae2d9adb5","observation_id":"71d2e44f-35fb-4b6b-aa03-8e6989d8c89e","resolution":{"observed_at":"2026-08-03T05:21:48.563328Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2507.05513","last_updated":"2025-07-07T22:20:04Z","snapshot_observed_at":"2026-08-02T00:14:37.528134Z","submitted_at":"2025-07-07T22:20:04Z","title":"Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2507.05513","snapshot_observed_at":"2026-08-03T05:21:48.770461Z","title":"Yang, Z., Qi, P., Zhang, S., Bengio, Y ., Cohen, W., Salakhut- dinov, R., and Manning, C","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2602.02827","last_updated":"2026-06-02T15:26:45Z","snapshot_observed_at":"2026-08-04T23:44:48.120786Z","submitted_at":"2026-02-02T21:27:01Z","title":"Col-Bandit: Query-Time Top-$K$ Estimation for Late-Interaction Retrieval","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-03T05:21:48.770461Z"},"links":{"cited_paper":"/paper/2507.05513","citing_paper":"/paper/2602.02827"},"observation_digest":"sha256:9d8c2d76e90397f2975caf2ba20f8f41395d4e9ce748b09e9d3dde492b98f453","observation_id":"eb29bfa4-1cda-4f4c-9651-a6da50627910","resolution":{"observed_at":"2026-08-03T05:21:48.770461Z","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":"2026-08-03T05:21:48.868879Z","title":"In our framework, the relaxation factor αef practically compensates for this approximation","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2602.02827","last_updated":"2026-06-02T15:26:45Z","snapshot_observed_at":"2026-08-04T23:44:48.120786Z","submitted_at":"2026-02-02T21:27:01Z","title":"Col-Bandit: Query-Time Top-$K$ Estimation for Late-Interaction Retrieval","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-03T05:21:48.868879Z"},"links":{"citing_paper":"/paper/2602.02827"},"observation_digest":"sha256:9b3fbb3cf11a0b58340c714cd87470b6d8d83cde2f18410b4a5aedac986c9875","observation_id":"46484239-241b-4075-a932-4e6af6183184","resolution":{"observed_at":"2026-08-03T05:21:48.868879Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2104.08663","last_updated":"2021-10-21T01:18:28Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2021-04-17T23:29:55Z","title":"BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2104.08663","snapshot_observed_at":"2026-08-03T05:21:48.429059Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.02827","last_updated":"2026-06-02T15:26:45Z","snapshot_observed_at":"2026-08-04T23:44:48.120786Z","submitted_at":"2026-02-02T21:27:01Z","title":"Col-Bandit: Query-Time Top-$K$ Estimation for Late-Interaction Retrieval","version":2},"reference_index":1998,"source":"pdf_text","source_observed_at":"2026-08-03T05:21:48.429059Z"},"links":{"cited_paper":"/paper/2104.08663","citing_paper":"/paper/2602.02827"},"observation_digest":"sha256:aced6389629554c5ec5795692d72baafac8ab6e3c3f4a458187812212af02a71","observation_id":"cb226bfb-f2e4-47bc-b2b2-41e427fc57bc","resolution":{"observed_at":"2026-08-03T05:21:48.429059Z","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":"2026-08-03T05:21:47.682677Z","title":"DESSERT: An efficient algorithm for vector set search with vector set queries","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2602.02827","last_updated":"2026-06-02T15:26:45Z","snapshot_observed_at":"2026-08-04T23:44:48.120786Z","submitted_at":"2026-02-02T21:27:01Z","title":"Col-Bandit: Query-Time Top-$K$ Estimation for Late-Interaction Retrieval","version":2},"reference_index":2011,"source":"pdf_text","source_observed_at":"2026-08-03T05:21:47.682677Z"},"links":{"citing_paper":"/paper/2602.02827"},"observation_digest":"sha256:8f23bd1a85eb291cfc6c63066cbdbd9e434c75935954497f18b8b03345b81cea","observation_id":"f6b1c1df-9ddd-47e1-bd83-0c31f682f403","resolution":{"observed_at":"2026-08-03T05:21:47.682677Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.14683","last_updated":"2024-09-23T03:12:43Z","snapshot_observed_at":"2026-07-06T19:19:37.350445Z","submitted_at":"2024-09-23T03:12:43Z","title":"Reducing the Footprint of Multi-Vector Retrieval with Minimal Performance Impact via Token Pooling","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.14683","snapshot_observed_at":"2026-08-03T05:21:47.310010Z","title":"Reducing the footprint of multi-vector retrieval with minimal per- formance impact via token pooling.arXiv preprint arXiv:2409.14683,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.02827","last_updated":"2026-06-02T15:26:45Z","snapshot_observed_at":"2026-08-04T23:44:48.120786Z","submitted_at":"2026-02-02T21:27:01Z","title":"Col-Bandit: Query-Time Top-$K$ Estimation for Late-Interaction Retrieval","version":2},"reference_index":2014,"source":"pdf_text","source_observed_at":"2026-08-03T05:21:47.310010Z"},"links":{"cited_paper":"/paper/2409.14683","citing_paper":"/paper/2602.02827"},"observation_digest":"sha256:bc595488215e9f4f9b0a04b87c6d16aeaf2163f11d8e41597523a58a3769cc82","observation_id":"21382b26-3c7b-4175-a41b-f7af92aeee5e","resolution":{"observed_at":"2026-08-03T05:21:47.310010Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1309.4029","last_updated":"2015-07-27T12:08:24Z","snapshot_observed_at":"2026-07-06T03:23:08.647067Z","submitted_at":"2013-09-16T16:38:20Z","title":"Concentration inequalities for sampling without replacement","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1309.4029","snapshot_observed_at":"2026-08-03T05:21:47.173286Z","title":"URL https: //arxiv.org/abs/1309.4029","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.02827","last_updated":"2026-06-02T15:26:45Z","snapshot_observed_at":"2026-08-04T23:44:48.120786Z","submitted_at":"2026-02-02T21:27:01Z","title":"Col-Bandit: Query-Time Top-$K$ Estimation for Late-Interaction Retrieval","version":2},"reference_index":2015,"source":"pdf_text","source_observed_at":"2026-08-03T05:21:47.173286Z"},"links":{"cited_paper":"/paper/1309.4029","citing_paper":"/paper/2602.02827"},"observation_digest":"sha256:615792a87771a59dd23b0790b3f78bf6e2728090e9edd6ce161b93b20615b0f1","observation_id":"de119e0c-970f-4180-86d6-c42061aad1e9","resolution":{"observed_at":"2026-08-03T05:21:47.173286Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1902.09465","last_updated":"2019-02-25T17:30:07Z","snapshot_observed_at":"2026-08-04T14:27:52.304740Z","submitted_at":"2019-02-25T17:30:07Z","title":"Adaptive Estimation for Approximate k-Nearest-Neighbor Computations","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1902.09465","snapshot_observed_at":"2026-08-03T05:21:48.053017Z","title":"org/abs/1902.09465","venue":null,"work_id":null,"year":1902},"citing_paper":{"arxiv_id":"2602.02827","last_updated":"2026-06-02T15:26:45Z","snapshot_observed_at":"2026-08-04T23:44:48.120786Z","submitted_at":"2026-02-02T21:27:01Z","title":"Col-Bandit: Query-Time Top-$K$ Estimation for Late-Interaction Retrieval","version":2},"reference_index":2019,"source":"pdf_text","source_observed_at":"2026-08-03T05:21:48.053017Z"},"links":{"cited_paper":"/paper/1902.09465","citing_paper":"/paper/2602.02827"},"observation_digest":"sha256:0dbdb110c3d6dbcd09d735d8725b73d63521399ee76e8f0cf8135b721977713f","observation_id":"9039c711-a469-4ea8-9b47-2ab7ba684b39","resolution":{"observed_at":"2026-08-03T05:21:48.053017Z","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":"2026-08-03T05:21:47.508809Z","title":"MUVERA: Multi-vector retrieval via fixed dimensional encodings","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2602.02827","last_updated":"2026-06-02T15:26:45Z","snapshot_observed_at":"2026-08-04T23:44:48.120786Z","submitted_at":"2026-02-02T21:27:01Z","title":"Col-Bandit: Query-Time Top-$K$ Estimation for Late-Interaction Retrieval","version":2},"reference_index":2020,"source":"pdf_text","source_observed_at":"2026-08-03T05:21:47.508809Z"},"links":{"citing_paper":"/paper/2602.02827"},"observation_digest":"sha256:5441758b8bc64216ef8e937b908a64e9c6e1fc66270f8991687d33063e79c425","observation_id":"a29689de-be46-4e2b-b133-da460999b068","resolution":{"observed_at":"2026-08-03T05:21:47.508809Z","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":"2026-08-03T05:21:47.873029Z","title":"K., Mohr, I., Ungureanu, A., Wang, B., Eslami, S., Martens, S., Werk, M., Wang, N., et al","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2602.02827","last_updated":"2026-06-02T15:26:45Z","snapshot_observed_at":"2026-08-04T23:44:48.120786Z","submitted_at":"2026-02-02T21:27:01Z","title":"Col-Bandit: Query-Time Top-$K$ Estimation for Late-Interaction Retrieval","version":2},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-03T05:21:47.873029Z"},"links":{"citing_paper":"/paper/2602.02827"},"observation_digest":"sha256:03673bdfc9c9bf92288e156e67010eaffc19b7d8979b8ed9b0989dcb75085542","observation_id":"cecdb8c3-cae6-4ab0-93b9-d58ddec85642","resolution":{"observed_at":"2026-08-03T05:21:47.873029Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.01449","last_updated":"2025-02-28T08:51:57Z","snapshot_observed_at":"2026-07-06T18:39:43.472708Z","submitted_at":"2024-06-27T15:45:29Z","title":"ColPali: Efficient Document Retrieval with Vision Language Models","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.01449","snapshot_observed_at":"2026-08-03T05:21:47.768264Z","title":"Faysse, M., Sibille, H., Wu, T., Omrani, B., Viaud, G., Hudelot, C., and Colombo, P","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.02827","last_updated":"2026-06-02T15:26:45Z","snapshot_observed_at":"2026-08-04T23:44:48.120786Z","submitted_at":"2026-02-02T21:27:01Z","title":"Col-Bandit: Query-Time Top-$K$ Estimation for Late-Interaction Retrieval","version":2},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-03T05:21:47.768264Z"},"links":{"cited_paper":"/paper/2407.01449","citing_paper":"/paper/2602.02827"},"observation_digest":"sha256:2fc504d1567a8afe894e14fd7be26068d938fce875872ebf046d4157ed625586","observation_id":"4e19a6d6-b7f2-4dda-afc2-cda7dcb8a960","resolution":{"observed_at":"2026-08-03T05:21:47.768264Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2004.07180","last_updated":"2020-05-20T17:39:52Z","snapshot_observed_at":"2026-07-06T09:12:35.818953Z","submitted_at":"2020-04-15T16:05:51Z","title":"SPECTER: Document-level Representation Learning using Citation-informed Transformers","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2004.07180","snapshot_observed_at":"2026-08-03T05:21:47.425338Z","title":null,"venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2602.02827","last_updated":"2026-06-02T15:26:45Z","snapshot_observed_at":"2026-08-04T23:44:48.120786Z","submitted_at":"2026-02-02T21:27:01Z","title":"Col-Bandit: Query-Time Top-$K$ Estimation for Late-Interaction Retrieval","version":2},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-03T05:21:47.425338Z"},"links":{"cited_paper":"/paper/2004.07180","citing_paper":"/paper/2602.02827"},"observation_digest":"sha256:9d3ca321157518d193d0d6c47412c83b7decd49e7901964dad9d84c3470105d7","observation_id":"af2404a3-30ee-471d-b1f1-9844ac07a474","resolution":{"observed_at":"2026-08-03T05:21:47.425338Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2602.02827","last_updated":"2026-06-02T15:26:45Z","latest_version":2,"primary_category":"cs.IR","snapshot_observed_at":"2026-08-04T23:44:48.120786Z","submitted_at":"2026-02-02T21:27:01Z","title":"Col-Bandit: Query-Time Top-$K$ Estimation for Late-Interaction Retrieval"},"reference_resolution":{"displayed":18,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":18,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":18},"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":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"thesis":"As of 5 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2602.02827."}