{"as_of":"2026-08-09T15:10:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f4077bcaf10186cd56902e11ecd0483500cceb7c46c652db1c35ff963276bede","coverage":[{"denominator":60,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":60,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-11T21:31:04.773453Z","state":"measured"},{"denominator":60,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":60,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2607.04125/citation-record","integrity":"/paper/2607.04125/integrity","json":"/paper/2607.04125/citation-record.json","paper":"/paper/2607.04125"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T21:31:04.773453Z","title":"Faster r-cnn: Towards real-time object detection with region proposal networks,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:6b38ea5710e4f8b9d8fa3bc437acf3423e4c03ea249c2884d20635a742bb39b6","observation_id":"15e8819e-9336-4c84-88db-dce54aff1b3a","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"Yolov7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:6cc60d06be85bacc996d52b4d2de3e4c265ed050fa24ac5060894a2eb1514d1f","observation_id":"77b873f5-ccba-4bdb-9562-dcca9eb24deb","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2010.11929","last_updated":"2021-06-03T13:08:56Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2020-10-22T17:55:59Z","title":"An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.11929","snapshot_observed_at":"2026-07-11T21:31:04.773453Z","title":"An image is worth 16x16 words: Transformers for image recognition at scale,","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"cited_paper":"/paper/2010.11929","citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:03542f3d2f6ffbad626a0c87bcb7fcc349615fa1b3cd8074b33b7614e51d7730","observation_id":"a0690c49-51c7-42c7-82d1-5ec5c41f8d32","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"Swin transformer: Hierarchical vision transformer using shifted windows,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:8fcd9865949e85e79c467fae9b10932845937dfd260599dd4f4b46ba1b88c156","observation_id":"e2644b29-6cfc-4dc2-9487-29f09211ccd3","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"Detrs beat yolos on real-time object detection,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:3d57720015c2424fbce7506349d567ca31f94e61d1c3c3d14c34a18187205ab6","observation_id":"2e94a6a9-0b98-4151-8419-16373646edc8","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.00752","last_updated":"2024-05-31T17:55:27Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-12-01T18:01:34Z","title":"Mamba: Linear-Time Sequence Modeling with Selective State Spaces","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.00752","snapshot_observed_at":"2026-07-11T21:31:04.773453Z","title":"Mamba: Linear-time sequence modeling with selective state spaces,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"cited_paper":"/paper/2312.00752","citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:4bcb6495171c58f9e792e5b9d164c059ecd0f86f73d22f945ea68bc68f106aa5","observation_id":"4982220d-2863-4c6b-a9f2-546a993c7a56","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"Microsoft coco: Common objects in context,","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:5487b443552482bf9af5bd8636228aaa2584f3db028b67da1881b9ec385bf74a","observation_id":"1e46c4dc-2f7b-4145-9d4d-59ec53ffa554","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"Refining activation down- sampling with softpool,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:fbf406c8a096454a0ab429493d622263b00cdad437503a1adbc19f71be7f8607","observation_id":"4906a698-5f19-4ed7-b702-1c54162f3624","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"Feature selective anchor-free module for single-shot object detection,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:ed45d73e193fea4e7ecd760cc0c560f62f5ed727495c92996e3568edf6ae36c9","observation_id":"3ebb2c10-b527-4961-9034-b349b14b7e7e","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"Adaptive sparse convolutional networks with global context enhancement for faster object detection on drone images,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:bfd9fb451548593927c586a0fd9696977b96a2386c9205989f1cd1865f3b55ae","observation_id":"999eb913-b827-4ca5-b735-f44cb6566dbb","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"Remdet: Rethinking efficient model design for uav object detection,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:3208c5460a42c710000ae800ddca30fcfe40c2730c29eef736c09ab3d5c3487d","observation_id":"4b2e8d3a-2f96-4d43-b053-a3ebe6abf4a3","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"Slicing aided hyper inference and fine-tuning for small object detection,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:aeceab41d0037ad6d2b14e5ce19d64b21a1e4230a0d481ac72cb168b0440836b","observation_id":"e864564b-110f-45c5-9329-bce13298a4ca","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"Ufpmp-det: Toward accurate and efficient object detection on drone imagery,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:b6f3a7d075c5b6000cbd00495357698726b5068ae8178917471229685b917dc3","observation_id":"212fcb7f-07af-4458-9fe7-d5a14cd6d247","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"A global-local self-adaptive network for drone-view object detection,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:491604f1814f1b65d2584ab2f08a06dc70c76cb9b39154fb3ce29fc325d17558","observation_id":"a4cb6497-aeff-4d85-b0aa-3cfa9d60512a","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"Hrdnet: High-resolution detection network for small objects,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:d6c33a1225d97a57187f452249d24a4dc8ab2a70c69535f009644b4f4ccdd214","observation_id":"500af441-cbf1-406e-a092-9c5f9bdf1bc0","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"Visdrone-det2019: The vision meets drone object detection in image challenge results,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:4722908ae12074cb28c78ca8ebec5e23d5e50e138a3a9c991b05c4d938d4a481","observation_id":"134e889f-e862-4270-99f0-887ce4fad1eb","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"The unmanned aerial vehicle benchmark: Object detection and tracking,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:71f665875dffdfa64731f5939aeeac018560743d2d5da0ebbcf3b9dac5b67977","observation_id":"3f42156a-17f4-42a0-b056-33e1f7e014a7","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.19833","last_updated":"2025-05-26T05:15:33Z","snapshot_observed_at":"2026-07-06T19:24:12.811792Z","submitted_at":"2024-09-30T00:11:40Z","title":"HazyDet: Open-Source Benchmark for Drone-View Object Detection with Depth-Cues in Hazy Scenes","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.19833","snapshot_observed_at":"2026-07-11T21:31:04.773453Z","title":"Hazydet: Open-source benchmark for drone- view object detection with depth-cues in hazy scenes,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"cited_paper":"/paper/2409.19833","citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:4c74f3228bc1d5cd20b5852d102bd729b3d587d117130f5a1672cf06146d2477","observation_id":"91ef7702-108f-4894-90a7-2511673a5616","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"Focal loss for dense object detection,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:642decd28ecd90f08a1546d511294734851ec61af4621a3abeedb24eaa5ba699","observation_id":"27bb72f1-ce39-46cf-8f53-83552a56e0bd","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"Bridging the gap between anchor-based and anchor-free detection via adaptive training sample selection,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:7fc891383c1535be6cfcd169cfe5b945f1b752d4fc7d26f0208c0536e4904859","observation_id":"60defb29-3fb9-41b9-b22c-a17c26bb232d","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"Disentangle your dense object detector,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:1bc2053711ddae2ef9b4a8c74a875ea47b4cd1ffcd3b6e9d93ec05332a44606a","observation_id":"0ccce714-ddcc-4260-8138-f3cda4654e49","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"Reppoints: Point set representation for object detection,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:d354d10c5e0ee19a9e88eeebe9d35ddeb2f3929c3c620f803c6ac0737858d154","observation_id":"2969800a-578e-403e-981b-4596ba6acd61","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"Fcos: Fully convolutional one- stage object detection,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:4a2c568e849fb80cdcac400b86775aca1d3a9ca9e9996c0b2888e2d3757bdac2","observation_id":"3412e394-dd03-474a-bb0e-2bf6f9ababd2","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"Centernet: Keypoint triplets for object detection,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:734209bef88e1ea8f594437bdc85f8abc432a764379fdb8261ec0fd50f0beb86","observation_id":"ffd61687-6d4b-47ef-a04c-c11582177baa","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"Generalized focal loss: Learning qualified and distributed bounding boxes for dense object detection,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:c33c679a93fc9a222be6d90486035720b9d217d1bb1b2430be998df9bd6346cd","observation_id":"7db876cf-07ce-4458-bd5d-1e3ef1289754","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"Tood: Task- aligned one-stage object detection,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:9c60d0939d1f2e47d94e427e256c1d9dfa2fbe8095179565391a990b6956e40c","observation_id":"a742cb33-8975-486d-900f-b5d7248a6750","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"End-to-end object detection with transformers,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:53b84b7f8ed7000412ce353f6281973ab29fdd3f5d726ec8a7c0052fedfc2d7e","observation_id":"fa831823-ce3c-475b-ae27-c61d98603ff8","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2010.04159","last_updated":"2021-03-18T03:14:26Z","snapshot_observed_at":"2026-07-06T10:02:45.105181Z","submitted_at":"2020-10-08T17:59:21Z","title":"Deformable DETR: Deformable Transformers for End-to-End Object Detection","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.04159","snapshot_observed_at":"2026-07-11T21:31:04.773453Z","title":"Deformable detr: Deformable transformers for end-to-end object detection,","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"cited_paper":"/paper/2010.04159","citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:73b1aa0874460842198c9a901d76649ea63e8d413e1fbf238f834dc6cf7fd24f","observation_id":"993a3778-a352-43f7-b44d-80b71c027eb1","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2301.05586","last_updated":"2023-01-13T14:46:46Z","snapshot_observed_at":"2026-07-06T14:41:06.148813Z","submitted_at":"2023-01-13T14:46:46Z","title":"YOLOv6 v3.0: A Full-Scale Reloading","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2301.05586","snapshot_observed_at":"2026-07-11T21:31:04.773453Z","title":"Yolov6 v3. 0: A full-scale reloading,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"cited_paper":"/paper/2301.05586","citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:f7ea4cc414b59d08ea826aa3a8879858bae58a421fe880db715b45075a9fc1b7","observation_id":"a95e5480-2927-43f4-b378-d3e857607636","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"Yolov9: Learning what you want to learn using programmable gradient information,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:548b17109497cb9cee026c11f1fc3bb18d8597f03018ffc8b4187ef549fdc8ae","observation_id":"8981bf99-fbeb-4a08-86a3-663b8585b47d","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"Yolov10: Real-time end-to-end object detection,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:5c78af0ded21d48ea0f8b1fd4f675cb39a3b006b4780f652e100194cfa65a870","observation_id":"1ecebbcf-5f20-490a-acb8-8979f12f143b","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"Ultralytics yolo11,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:1929d4d9d6bb6757090be29bdd56ea6f7864bf5179c134161e5a24d53549b841","observation_id":"c1380695-8f73-416c-bf50-e890a35c6531","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.12524","last_updated":"2025-02-18T04:20:14Z","snapshot_observed_at":"2026-07-06T20:38:20.545914Z","submitted_at":"2025-02-18T04:20:14Z","title":"YOLOv12: Attention-Centric Real-Time Object Detectors","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.12524","snapshot_observed_at":"2026-07-11T21:31:04.773453Z","title":"Yolov12: Attention-centric real-time object detectors,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"cited_paper":"/paper/2502.12524","citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:b535b894cf61897a1668cf9bada8811a8365acee6a4c91736bd6c0d02423a7f0","observation_id":"e10692a0-da13-474d-bd71-f1e187c795ad","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"Gold- yolo: Efficient object detector via gather-and-distribute mechanism,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:7ecc473d79e26315fe74387f64811c3f79943d92a4e2edc3af32f0acda38290b","observation_id":"34395d76-82c8-49e1-8a63-9a95bb22f814","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"Hyper-yolo: When visual object detection meets hypergraph computation,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:4c2cf527952ac963073e4f22b95a184c5fbcf6c9f5b6afba9c64a321fccaa761","observation_id":"2c0ac4f9-c081-4ec1-b5eb-c34f6737191d","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"Clustered object de- tection in aerial images,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:8816aa086978ce169ffd7662b7965ef2fdc8bf63ef3149204616b9b093ba3ccb","observation_id":"48386b45-bcd3-459c-971c-8c83315c2b82","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"Density map guided object detection in aerial images,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:e758ee4286b5e70eade5034f6d04357053066c395f8a5d931daee111f2ec3816","observation_id":"bda96b66-10e9-4db6-90d0-06c6781f3ac2","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"Coarse-grained density map guided object detection in aerial images,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:ac07d108416f33c4eb43478df7b9f8f69f9ace90180f062a71d188922671c536","observation_id":"d479d5d5-363e-48d7-bba4-5337105f76a1","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"Querydet: Cascaded sparse query for accelerating high-resolution small object detection,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:2a0fc0d103997065c733a21da87df66321028437cbafb70a6ec0722f70809e02","observation_id":"4c1dd318-5a90-4499-a4ef-49808a84d290","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"Esod: Efficient small object detection on high-resolution images,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:0dfafa38cf5abfb811673d5533b38688e1e06b4382f8271ac85d4c77e7806cb6","observation_id":"84f554cb-4d00-4fee-98ad-4aebcace163b","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"Feature pyramid networks for object detection,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:9f5026ff1e78c0cfcf1ef8120378ce675dbdcbce284d73f88c711ca1e638d87a","observation_id":"3dd191d1-5c2a-4621-8a4d-d10653f93b13","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"Efficientdet: Scalable and efficient object detection,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:60a3ba83c15ba30ff6159202de805ca55dfb3a3e180764cb4a5b4f24363c2bfd","observation_id":"cebd631d-7e02-4e22-875c-8acba57a695a","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"Ultralytics yolov8,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:2eb2dfe6b8b455f4964eea7540f247f3d27cf57f53695296d61d09153fb3697d","observation_id":"93c5183d-ac94-4fa7-967a-753b88653b32","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"Dtssnet: Dynamic training sample selection network for uav object detection,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:db959e04f72da889963b6eb443ec8061e22f07badeb89578b2c1361f4eec737e","observation_id":"d0a565e2-deb6-4ad6-b9f0-767032404f9a","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"Yolc: You only look clusters for tiny object detection in aerial images,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:27c4ab324b8828ba0331d34b73899ba4f8e249d33a89df25e004eeac0fe54e8c","observation_id":"2bb08bce-2716-417f-864c-ff3991a63cc5","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"A lightweight fusion strategy with enhanced inter-layer feature correlation for small object detection,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:1f6845de0ed1015edf1eda89210feb06a0176b7fe5cfa6b1b3422ff50036db0c","observation_id":"5468b87c-a00f-43ba-9cde-54f72c9fba5e","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"Global-local fusion with semantic information-guidance for accurate small object detection in uav aerial images,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:056e9480d53a486e634d08d3d898fb34e9f0b73ceaa62d0070647b2356069fe5","observation_id":"55253f6c-b136-47ea-978b-250e2b706a7d","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"Explaining neural scaling laws,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:e8a0c19154cfde6acc76b64618079a7135c922f8412db9b63579fb0479e0b60b","observation_id":"ef166a1d-1064-4b0c-9cb4-35bd183415a5","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"Conditional-pooling for improved data transmission,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:b20f748b435cfcf4e2af1a2986871b410afe318a85e85ce45357e478722b90e5","observation_id":"8dfed51d-b48b-4bd4-9ff3-ae3528aeb6fe","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"Carafe: Content-aware reassembly of features,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:1c0650a51f86d059254bac3aea32779304bd14638b8e35c893315e45d8411539","observation_id":"8e5b5b05-5128-43fb-9e12-aa19469b43e6","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"Learning to upsample by learning to sample,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:a43f4172456d4d0fee01aff072f9cff6f7777d8501a72a5d2cfc4b4613d65692","observation_id":"479c9776-be2c-433a-b6ca-b2b55e570fe2","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"Afpn: Asymptotic feature pyramid network for object detection,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:54ae4fe2762032a5a78365a4f8feef03c200e61f855db495b1ed10da9d08fede","observation_id":"37fc0bbb-97b2-403b-840c-c1c60831d8b5","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"Centralized feature pyramid for object detection,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:0c343e0e4d82e2405d9351263a83c02975d34bd9c5e176b5b2d5dedf5c8e4153","observation_id":"2d58ad9d-5c9a-4fe5-b2f7-a9f43d11803e","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2511.21631","last_updated":"2025-11-27T12:16:54Z","snapshot_observed_at":"2026-07-06T22:37:03.716474Z","submitted_at":"2025-11-26T17:59:08Z","title":"Qwen3-VL Technical Report","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2511.21631","snapshot_observed_at":"2026-07-11T21:31:04.773453Z","title":"Qwen3-vl technical report,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"cited_paper":"/paper/2511.21631","citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:8848efadb034e096f7582fabbabd273a1e7fb15b35009ca9cfb27c51ca82ba91","observation_id":"3f9d4a7e-b402-4f2e-bc37-0b2fde402ec1","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01006","last_updated":"2026-01-01T13:07:25Z","snapshot_observed_at":"2026-08-03T18:50:30.558321Z","submitted_at":"2025-07-01T17:55:04Z","title":"GLM-4.5V and GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2507.01006","snapshot_observed_at":"2026-07-11T21:31:04.773453Z","title":"Glm-4.1 v-thinking: Towards versatile mul- timodal reasoning with scalable reinforcement learning,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"cited_paper":"/paper/2507.01006","citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:151786cdf4080bc008256b1d0181efa100a54d5ab284980e4681933b19623f52","observation_id":"5e5fc546-4c4a-417e-af25-509072b64db5","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.05302","last_updated":"2025-06-05T17:51:39Z","snapshot_observed_at":"2026-08-09T01:44:49.494240Z","submitted_at":"2025-06-05T17:51:39Z","title":"Perceive Anything: Recognize, Explain, Caption, and Segment Anything in Images and Videos","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.05302","snapshot_observed_at":"2026-07-11T21:31:04.773453Z","title":"Perceive anything: Recognize, explain, cap- tion, and segment anything in images and videos,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"cited_paper":"/paper/2506.05302","citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:c7cf278275120a057c6e483b683cae3ee27e87fee7c9745eed5d5385237a84de","observation_id":"f067d0b1-ed72-4548-b86f-4a796ce217ed","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"Personalq: Select, quantize, and serve personalized diffusion models for efficient inference,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:9d92e29634155865789bba123b4f5da044838755ded13660dcfda65b96360e43","observation_id":"f480d2c7-a2b1-494a-81e8-72f16393059f","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:9b1f040d7fb5aa86b7fad7a5c5b751a1a53b8c45c3c551b5a3a999a41d7ab02f","observation_id":"e6c53555-bd8d-4ee6-b9c5-9d83761ab007","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:73694b074eff0c75d00ea52aa5fbff23dfa64e15b6901311f0a3316fdc630271","observation_id":"11b7f4d9-b37d-4bb0-b502-c94578e874f5","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","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":"2026-07-11T21:31:04.773453Z","title":"LayerGroup (IBS- D+IBS-U)","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-07-11T21:31:04.773453Z"},"links":{"citing_paper":"/paper/2607.04125"},"observation_digest":"sha256:1602097070751f07a03db667a7db156eef2cdca7ff2334c011ecbb0efc049a70","observation_id":"b972a6fc-1c76-4c3c-8281-0620e4a60d47","resolution":{"observed_at":"2026-07-11T21:31:04.773453Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.04125","last_updated":"2026-07-05T05:42:56Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-09T01:44:53.560742Z","submitted_at":"2026-07-05T05:42:56Z","title":"FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion"},"reference_resolution":{"displayed":60,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":60,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":60},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 60 of 60 outbound references and 0 inbound Pith citation observations for arXiv:2607.04125."}