{"as_of":"2026-08-10T06:15:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:c292eba7fae53954b766452f7e7a54a1b6e2f51918f6f4fee582708d187b55ea","coverage":[{"denominator":57,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":57,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-03T15:29:40.807911Z","state":"measured"},{"denominator":57,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":57,"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/2607.02139/citation-record","integrity":"/paper/2607.02139/integrity","json":"/paper/2607.02139/citation-record.json","paper":"/paper/2607.02139"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.066802Z","title":"Open-world text-specifed object counting","venue":null,"work_id":"b19747d7-9dae-4b4c-add4-d950d44be6e3","year":2023},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:2291cd987f6650f9afe2a5e6789e2b6fc55e6bff0eb96f2091418d65dc056faf","observation_id":"71a2090d-0397-4111-90b4-ed2f1c84d716","resolution":{"observed_at":"2026-07-05T06:20:45.068058Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.101647Z","title":"Countgd: Multi-modal open-world counting.Advances in Neural In- formation Processing Systems, 37:48810–48837, 2024","venue":null,"work_id":"0cc90231-03a9-4e96-9bfd-33a66a8b8141","year":2024},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:742c0295f81153b99d4646ab13ad8c1eb5b34a328dc62a9435226a3014777647","observation_id":"b581eeab-403c-4839-8ced-23e316c7fd45","resolution":{"observed_at":"2026-07-05T06:20:45.103241Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.070876Z","title":"Countgd++: Gen- eralized prompting for open-world counting","venue":null,"work_id":"f13f7cae-f76a-4668-ad71-884d98dd6b01","year":2026},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:988fa0e846b125be030c477c12a5494610f316f64501f958a454e6824d6f935c","observation_id":"d3d9702f-af47-4316-93c1-005b2934d8cd","resolution":{"observed_at":"2026-07-05T06:20:45.072566Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.136051Z","title":"Open-world ob- ject counting in videos","venue":null,"work_id":"c0aa58a2-1b8d-4c98-a276-f1300cb73da2","year":2026},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:ffe8d712e4e8904d27efcb0c6ef375e98f15e0cfc27c88f60f90dce2384b87e1","observation_id":"33a08891-32f8-4081-ae13-edee06388e91","resolution":{"observed_at":"2026-07-05T06:20:45.137536Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.105620Z","title":"Completely self-supervised crowd counting via distribution matching","venue":null,"work_id":"a843862c-41bb-4956-b79f-0464c5593af4","year":2022},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:79141a79b0ef334e752f285fee6015cf92bae5da01b35ee2d4b3258da3411ae4","observation_id":"401831d9-acb6-4aa6-a6b1-7a0380a6a830","resolution":{"observed_at":"2026-07-05T06:20:45.106971Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.034732Z","title":"Unveiling visual perception in language models: An attention head analysis approach","venue":null,"work_id":"6d04e424-f5d3-4442-bb77-5ee1726df253","year":2025},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:3f14f9d5748a8c4e5013fc77f5496397be4cb728fabdf4da5fa2c047d6a79f94","observation_id":"af9cfde5-9fdb-4c48-9dee-a6c7b2760692","resolution":{"observed_at":"2026-07-05T06:20:45.036269Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.107571Z","title":"Perception encoder: The best visual embeddings are not at the output of the net- work.Advances in Neural Information Processing Systems, 38:60884–60937, 2026","venue":null,"work_id":"85bcf4a8-ff95-4b5b-874c-196722939d63","year":2026},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:6426bae901d79b00e02a4ef4347b30b2f1927ae327af70de17c072d24dafc36f","observation_id":"ff2411b4-f314-4f40-a638-892ea4cceb62","resolution":{"observed_at":"2026-07-05T06:20:45.109062Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.113593Z","title":"A vehicle counts by class framework using distinguished regions tracking at mul- tiple intersections","venue":null,"work_id":"29d9b58e-7b57-4936-9ab2-66fd796bf95e","year":2020},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:f623ab265d95f9ab9d8780d6996192a196a008aaf0076a7eb45ec169bff33b37","observation_id":"ef57db69-772f-41e6-a4f5-afa25d750442","resolution":{"observed_at":"2026-07-05T06:20:45.114824Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.113205Z","title":"Sam 3: Segment anything with concepts.The Fourteenth International Conference on Learning Representations., 2026","venue":null,"work_id":"febf20ba-e9e1-4615-ad99-52e32acc25d1","year":2026},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:f0bb86bd0db64de2eb2fa34c2bd946fd03623668e6c68e77aaab456c3429c5bc","observation_id":"20342661-5c84-4c7e-bc1d-5660cd219f12","resolution":{"observed_at":"2026-07-05T06:20:45.114410Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.140003Z","title":"Mind the prompt: A novel benchmark for prompt-based class-agnostic counting","venue":null,"work_id":"d73dbc41-4c11-40ee-b2f2-88ad966886bb","year":null},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:e254d9b1fa87ad1419bdf29ffac9a728d26181763a8bba183e540d2e71a223a2","observation_id":"e17237e3-3176-4c64-8bc2-103c07515737","resolution":{"observed_at":"2026-07-05T06:20:45.141376Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.109683Z","title":"Constructive distortion: Improving MLLMs with attention-guided image warping","venue":null,"work_id":"4ad155e6-73fd-4088-8284-7d7583d10749","year":null},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:65a81599b9a756384d0694fee72492d4a38cc48273cedd02d4d05a80ae1fb103","observation_id":"ee496ce2-ac0c-45c1-92d6-d0ae8a239534","resolution":{"observed_at":"2026-07-05T06:20:45.111045Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.105812Z","title":"Afreeca: Annotation-free counting for all","venue":null,"work_id":"10c3b907-f2f7-4305-9c5e-0dbc62ca6074","year":2024},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:3d483a785958cf7357a3b70619b03fedc0d7b6dd44c3a23b61e9b5beb8e5e5a5","observation_id":"121d8bfc-faa1-4fbe-abab-928923f2002c","resolution":{"observed_at":"2026-07-05T06:20:45.107227Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.030025Z","title":"Image retargeting using mesh parametrization","venue":null,"work_id":"868d2d01-f3c1-4f94-987f-82426a759967","year":2009},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:1825fbdefdd31b9d44a18ca43bc8a48676d4f3ba4a86f4e5807e06476bed1a37","observation_id":"dd740d65-9fb0-4b1c-9887-f764586245b2","resolution":{"observed_at":"2026-07-05T06:20:45.031555Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.032185Z","title":"Few-shot object counting with dynamic similarity-aware in latent space.IEEE Transactions on Geoscience and Remote Sensing, 62:1–14, 2024","venue":null,"work_id":"0368603b-e991-4408-b569-68e57e0375a4","year":2024},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:8c19895a5e3b48fe76d974258ec30d7e1464ebb6050153c766e9ae6001355974","observation_id":"48e43d99-0f2d-479e-aab0-4a9669fbe707","resolution":{"observed_at":"2026-07-05T06:20:45.034079Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.133797Z","title":"Learning to count anything: Reference-less class-agnostic counting with weak supervision.Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023","venue":null,"work_id":"8288f735-4108-45a4-8cdd-6729f6b49a62","year":2023},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:2e1d3b160cb144720b75590dedf550a8bf40033266807d239e40ea6769d52503","observation_id":"43819a5f-79e3-429f-bf23-4402189983b6","resolution":{"observed_at":"2026-07-05T06:20:45.135268Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.038869Z","title":"Drone- based object counting by spatially regularized regional pro- posal network","venue":null,"work_id":"7ecc7179-e357-4325-8cb6-8c19da7037a2","year":2017},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:91ffbbb07e7e8658fea67aeed4e06299b9eb16fe13a0b7412e8b0471a001716d","observation_id":"78c5153d-5bc4-48ed-8ed8-ba73f10c9fde","resolution":{"observed_at":"2026-07-05T06:20:45.040383Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.040964Z","title":"Interac- tive class-agnostic object counting","venue":null,"work_id":"85a155fe-7720-4fc2-b7d1-0cab552e2d9a","year":2023},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:aca57a6001b0323760e80473b7774757d7656cfbb3ddb03e21ef44e447d5fd5b","observation_id":"64a946c6-4030-47a8-b3fd-09257dbeed01","resolution":{"observed_at":"2026-07-05T06:20:45.042340Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.045356Z","title":"Point segment and count: A gener- alized framework for object counting","venue":null,"work_id":"d6d78c90-3ac8-46d5-be79-bee77d99ad8b","year":2024},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:b468757f389fbc13c3ce1b1324b2fae10b0c94298b07460750ad91927f3c604c","observation_id":"289da7dd-a355-4550-a4ae-5435fbb28b86","resolution":{"observed_at":"2026-07-05T06:20:45.046637Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.068622Z","title":"Class- agnostic object counting with text-to-image diffusion model","venue":null,"work_id":"10adfb46-4340-45fd-85ed-23ea40986186","year":2024},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:8e9f769af007758cb4453af9a218faa72bdd52a18138edc245df5d428e581fb1","observation_id":"237733e1-f3f9-4482-99bb-74266e887bf8","resolution":{"observed_at":"2026-07-05T06:20:45.070153Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.065032Z","title":"Clip- count: Towards text-guided zero-shot object counting","venue":null,"work_id":"013c35f4-4a97-4e50-bdbf-dceaf2c86e82","year":2023},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:a5fd19ce85667d78de3013e4b210700dacb31c3f7e67e5efa2e5fa8b0faa312e","observation_id":"1fc9836c-ce59-45b8-9546-57f4319920e2","resolution":{"observed_at":"2026-07-05T06:20:45.066202Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.100074Z","title":"Vlcounter: Text-aware visual representation for zero- shot object counting","venue":null,"work_id":"1a940a2d-4df9-48b1-b9b2-fc0d747bb2ed","year":2024},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:046a26248bbc0508edf242092b9f56b972a97361dd8009e9ea3a73f6ae5d1baf","observation_id":"edc5bfa0-2378-4c11-98e5-7544e2e87676","resolution":{"observed_at":"2026-07-05T06:20:45.101291Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.023146Z","title":"Energy- based image deformation","venue":null,"work_id":"0f968845-476d-4803-bc8b-994a5b06d61a","year":2009},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:26059c076b509c77ba745f1476a8d86f2dcd90080e399e35f8b1de6703414c67","observation_id":"e8750745-2477-4115-8903-8210d8a21ae5","resolution":{"observed_at":"2026-07-05T06:20:45.024811Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.025482Z","title":"Segment any- thing","venue":null,"work_id":"d9c849e9-bbd5-4296-b27e-5b201bc2cd9f","year":2023},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:83a8e4ebbde7a1eb9d232ad4b0550c3f4384f775a96b89dc8c1d8a76fcc53197","observation_id":"69a52b9b-73aa-4b15-a333-fe61586b88cf","resolution":{"observed_at":"2026-07-05T06:20:45.026885Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.065989Z","title":"Calibrating uncertainty for semi-supervised crowd counting","venue":null,"work_id":"1b0043c5-05d0-49f0-b0c8-eea82fb0322d","year":2023},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:b642ea0c5f11789976b9719c82a460631310681d9a0cdbb9400bbf5284e68539","observation_id":"b8fac23d-e4b9-4532-bf93-4028b4d2b4e2","resolution":{"observed_at":"2026-07-05T06:20:45.067353Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.079026Z","title":null,"venue":null,"work_id":"de624b51-616a-4311-aaa1-6c871a2335ee","year":2020},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:91cfb732e7758f9d72e7389f0ff0d695f990416c8116bc39f0b4e44b56b5c2cd","observation_id":"35753df3-1a94-4879-b094-d2384e7ccaa4","resolution":{"observed_at":"2026-07-05T06:20:45.080109Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.002593Z","title":"A simple-but-effective baseline for training-free class- agnostic counting","venue":null,"work_id":"95e52b2a-b99d-4895-b137-2eb4e5b24229","year":2025},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:3c6754fb72217444f19707c3394f0bc88b3884c8279098b46454bb95ca41f917","observation_id":"a76ca56b-956d-415f-a142-ef9afd668acf","resolution":{"observed_at":"2026-07-05T06:20:45.019763Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.001702Z","title":"Improved baselines with visual instruction tuning","venue":null,"work_id":"d181a7eb-c751-4c65-9d82-fe80982df2eb","year":2024},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:8778ef329c372bc5fe75ad2df5eecde96b3f8354c5ca8f3a9a0ba4c20845d5f4","observation_id":"881f2388-c8a4-4667-b041-65e87e25248b","resolution":{"observed_at":"2026-07-05T06:20:45.002973Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.020274Z","title":"Grounding dino: Marrying dino with grounded pre-training for open-set object detection","venue":null,"work_id":"5712ef8a-94b9-4f37-a031-fa7bebdd2048","year":2024},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:306da4353e85c72ad9d5300d3417036f4c3986519a7957b97aabf91853d6e170","observation_id":"836ede25-8154-430e-90f3-2b01005c22c4","resolution":{"observed_at":"2026-07-05T06:20:45.022244Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.027753Z","title":"Countse: Soft exemplar open-set object counting","venue":null,"work_id":"02b7b945-4f51-48e7-8684-50069ad675e0","year":2025},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:eb6365b4d16820981e1c0995899064253b4c0f16e788e6af2692775fe805eec8","observation_id":"de955be7-19c9-49f7-a400-b6572891d31d","resolution":{"observed_at":"2026-07-05T06:20:45.029322Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2304.10817","last_updated":"2023-04-21T08:59:48Z","snapshot_observed_at":"2026-08-09T16:09:18.347321Z","submitted_at":"2023-04-21T08:59:48Z","title":"Can SAM Count Anything? An Empirical Study on SAM Counting","version":1},"cited_work":{"arxiv_id":"2304.10817","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2304.10817","snapshot_observed_at":"2026-07-03T15:38:33.200825Z","title":"Can sam count anything? an empirical study on sam counting","venue":null,"work_id":"4d8030a8-8204-4d47-a749-fe900682ad35","year":2023},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"cited_paper":"/paper/2304.10817","citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:eae24c9d29182e23be2bd1a0979721cd6f16ac2bf72f8e740492c074042ed8f0","observation_id":"dcd3e726-532d-4c86-acd9-208d32cbcc49","resolution":{"observed_at":"2026-07-03T15:38:33.202530Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.114997Z","title":"Through the magnifying glass: Adaptive perception magnification for hallucination-free vlm decoding","venue":null,"work_id":"05d01bd5-5b7d-4df6-b9df-9e578e7ded6a","year":2026},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:91dbc0903e685e973b36038ecd222a7892f8f43ae801e4b3a6d17ec782f7c62c","observation_id":"85b54735-fbec-4666-a248-8e5eccd56c07","resolution":{"observed_at":"2026-07-05T06:20:45.131396Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.050183Z","title":"Omnicount: Multi-label object counting with semantic- geometric priors","venue":null,"work_id":"42802759-bd29-496f-a478-8a859c0bd19f","year":2025},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:f28f1450e9511009273ef2a8ba8c92af49ebe61d763ff19a2d8f03e7180665f7","observation_id":"66f8134f-2ba2-47c0-b41b-c1d7dd18c8ef","resolution":{"observed_at":"2026-07-05T06:20:45.051506Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.036843Z","title":"Few-shot object counting and detection","venue":null,"work_id":"0bbfca7c-f613-4c41-9484-ae5f9c74d8ae","year":2022},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:8f31277aabd882deb02bdb47bb063faaa1591d2a2223d46c21c5d91be0015869","observation_id":"3042ea3c-c5af-415e-99ca-d8ed8841a6d2","resolution":{"observed_at":"2026-07-05T06:20:45.038260Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.090001Z","title":"Sam3count for zero-shot open vocabulary counting in images and videos","venue":null,"work_id":"5885820d-0f6e-40d7-b7e1-fe35c17a8bf0","year":2026},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:cffbaddc1d557f1830e1a6798acc8d2e9029a8adf069fb8ca5dc5bd4d220bbb4","observation_id":"29a537a9-118e-4fe9-b8fe-2295c38a2d74","resolution":{"observed_at":"2026-07-05T06:20:45.091549Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.087988Z","title":"Count- ingdino: A training-free pipeline for class-agnostic count- ing using unsupervised backbones","venue":null,"work_id":"953fadd3-1343-43de-990e-d0ce6d4333d9","year":2026},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:e17de942693de3a9be774cae3d375cff53293b0b36a27488be775c0c0d96a9ea","observation_id":"a9769e15-c59c-4cf7-ac5e-fb4979b3be6a","resolution":{"observed_at":"2026-07-05T06:20:45.089200Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.096030Z","title":"Count-ception: Counting by fully convolutional redundant counting","venue":null,"work_id":"bbee3d68-d48f-4ccc-9089-8c978225b0b4","year":2017},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:98ec1debe8a4d1c5fc6e58b55f673084bba474c21c75b790930c27b9ecc9633d","observation_id":"27c3d686-7e3c-4753-8013-ff6950ea9c27","resolution":{"observed_at":"2026-07-05T06:20:45.097485Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.094996Z","title":"A novel unified architecture for low-shot counting by detection and segmentation.Advances in Neural Information Processing Systems, 37:66260–66282, 2024","venue":null,"work_id":"fd9f95a9-6268-4080-8d69-5be695d8a2ed","year":2024},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:9d692bf4740d88120527a9ffd935d4b14f350b2348743186f3c2b97ae389ad9f","observation_id":"dc89f42b-39d0-4134-beff-14897faaecb5","resolution":{"observed_at":"2026-07-05T06:20:45.096680Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.076639Z","title":"Dave-a detect-and-verify paradigm for low-shot counting","venue":null,"work_id":"c2b39033-a71d-4928-ae1d-8a97316b510c","year":2024},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:eb8a16127bf0ba537b53a42f76bfd39ebadf4d06cd75a6d10ea9559e99a40e89","observation_id":"984593da-9093-45da-a36a-f6c9c0cb5657","resolution":{"observed_at":"2026-07-05T06:20:45.078137Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.080689Z","title":"T2icount: Enhancing cross-modal understanding for zero-shot counting","venue":null,"work_id":"7031b878-8731-45ed-a521-d0740a094411","year":null},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:dc0ac53b3996e8316629b7012df2a806f4c295f3f1fffeb60928c7c31e766b45","observation_id":"e11e9c31-486c-4759-8cd9-2b59c35f9b5a","resolution":{"observed_at":"2026-07-05T06:20:45.082067Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.097481Z","title":"Deep count: fruit counting based on deep simulated learning.Sensors, 17(4): 905, 2017","venue":null,"work_id":"1669cd84-6e14-45a5-bcd5-e35f8e551a74","year":2017},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:9336361285d7ac947e32d3a365be84b7f231762f69e69bb4cb8e1056fa1d622c","observation_id":"0fcba8f3-f2fb-4bb9-a590-cfe35ecbe5b5","resolution":{"observed_at":"2026-07-05T06:20:45.099015Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.075816Z","title":"Learning to count everything","venue":null,"work_id":"3e40e8a2-8e26-4220-a990-a80876f02a61","year":2021},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:2630b20469b5431debff573c3f84e4a753016eee06afbd9b507c5241d5ff54ce","observation_id":"c5ce4282-60fd-4d94-8353-edabadcf387e","resolution":{"observed_at":"2026-07-05T06:20:45.076958Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.109677Z","title":"A comparative study of image retargeting","venue":null,"work_id":"73cf9099-8803-4c16-bbca-cffd9b0481b2","year":2010},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:53b126eb978235fa14ff513b74f797b0faa14b7b1e5b9a093fdf3a667d70176d","observation_id":"2bb26f41-074b-4f5c-a6a6-3e65cc27c2a4","resolution":{"observed_at":"2026-07-05T06:20:45.110882Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.068068Z","title":"Training-free ob- ject counting with prompts","venue":null,"work_id":"753bb0df-ce8d-43c1-8809-2db26cfbf6fb","year":2024},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:4d687c66881cfa25677fad4d47e1c316fe73f487f3d323008f0750d9cbf800fe","observation_id":"df73f4f4-1a64-4ebb-a007-9d0a6b883d6f","resolution":{"observed_at":"2026-07-05T06:20:45.069259Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.103845Z","title":"Persense: Training-free personalized instance segmentation in dense images.BMVC, 2025","venue":null,"work_id":"03e63148-c643-4e0d-81a0-f6651f19f738","year":2025},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:18870ef76ca772ff3f4dd49a88e34374870fbf15b746f25b3206e24cefd69596","observation_id":"c9c083a9-4283-4696-b5a3-17cc6213ed4a","resolution":{"observed_at":"2026-07-05T06:20:45.105235Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.074351Z","title":"Learning to resize images for computer vision tasks","venue":null,"work_id":"0d2fe252-0565-441f-9480-b398702573b1","year":2021},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:8911a67726a5b375e9274e2bad529cae358b17b0cdc6f9f4c285969569f28bb9","observation_id":"3b46efa2-df28-4850-82aa-d1f0c10028b7","resolution":{"observed_at":"2026-07-05T06:20:45.076026Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.107771Z","title":"Degpr: Deep guided posterior regularization for multi-class cell de- tection and counting","venue":null,"work_id":"39e6fc7d-2d9c-47a7-ae27-a58da72fca30","year":2023},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:ac9ab5c8f751767a3f7cbb7ab587f8190dcf921afa909883c85b1819e8bb65e1","observation_id":"d924b1a4-063b-4b8d-b3e7-5b620fdb0050","resolution":{"observed_at":"2026-07-05T06:20:45.109057Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.101896Z","title":"Zero-shot object counting","venue":null,"work_id":"5fd16850-78b8-4a28-a0d9-2eb964a3aa54","year":2023},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:35c1e86c048756d0c8a35f4415272894b41f31ae3ec2c39d8e3c5faa78e65ec2","observation_id":"028bf547-5c90-4426-a0b8-97968c230a30","resolution":{"observed_at":"2026-07-05T06:20:45.103067Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.138157Z","title":"Class-agnostic few-shot object counting","venue":null,"work_id":"a57565cc-5d24-43eb-88d6-01ccf218977f","year":2021},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:c7414dbff811d4fa3405d634fd229c97c568b60dcb7616714702cb4107ba3fc9","observation_id":"b27b18f9-ff21-49dc-b91c-f2ce4d2dee4c","resolution":{"observed_at":"2026-07-05T06:20:45.139436Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.046143Z","title":"Content-driven retargeting of stereoscopic images.IEEE Signal Processing Letters, 20(5):519–522, 2013","venue":null,"work_id":"fecbd2e9-61fc-463b-b4ee-47d0e99d8ddc","year":2013},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:b7857e7bd4b9aa42a5f00d716e3a93689f36f797fd6186345a218a1677d6ac0a","observation_id":"688b2573-f074-448f-806c-4c8b866bbe5c","resolution":{"observed_at":"2026-07-05T06:20:45.047625Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.060350Z","title":"Few-shot object counting with similarity-aware feature enhancement","venue":null,"work_id":"ec0bfb14-5aea-465c-b8e6-719f43f855be","year":2023},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:a11eea99f9ac80b4168d865b24f1fba9da8cbf57e9460c714de9216a92608741","observation_id":"b18ed4a6-b762-4895-a185-eb0fe9e48002","resolution":{"observed_at":"2026-07-05T06:20:45.061599Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.062169Z","title":"Yolo-count: Differentiable object counting for text-to-image generation","venue":null,"work_id":"4850d254-5369-44b6-9371-541c41bc3e34","year":2025},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:942f80a7dfad5635b7538b9afa6fd876ffba3d6d3cec62115847b0c421a5e006","observation_id":"346a6398-5c44-49d0-8e02-2d436ec09294","resolution":{"observed_at":"2026-07-05T06:20:45.063359Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.061341Z","title":"Zero-shot object counting with vision-language prior guid- ance network.IEEE Transactions on Circuits and Systems for Video Technology, 2024","venue":null,"work_id":"89e047b8-14b8-4b0c-936d-2072a750733b","year":2024},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:4d569f139d409c578fd748aa318c2bc87d3561bb68ab61f88800c3688369c1b3","observation_id":"7ccd8ff5-9350-4ed6-b628-89a5f79d8970","resolution":{"observed_at":"2026-07-05T06:20:45.062623Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.054160Z","title":"Boosting quantitive and spatial awareness for zero-shot object counting","venue":null,"work_id":"753dea8a-3197-4839-915c-7edc43a30985","year":2026},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:f9f80c384776c7abaf4ea92d9508c493e583639a5d56494b159ab2d5117c3166","observation_id":"f30b24cf-f2b8-4221-ac29-b5021892d32b","resolution":{"observed_at":"2026-07-05T06:20:45.055705Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.044266Z","title":"Personalize segment anything model with one shot","venue":null,"work_id":"d28d1bb2-2c8e-495b-b1cf-5764d984f728","year":2024},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:38f96127a1a0c42ca0ece26252650e993993430f5ebdaaa8dd4b8812028a627a","observation_id":"21314167-eb40-43fd-8168-56fa9a723471","resolution":{"observed_at":"2026-07-05T06:20:45.045529Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.040023Z","title":"Enhancing zero-shot object counting via text-guided local ranking and number- evoked global attention","venue":null,"work_id":"370a93be-c908-4b6c-8a78-abb72732513a","year":2025},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:46aef849db85783b29cdab47552e586c14b89c06c74de22e55ed40e84027f0e1","observation_id":"3981cc35-d880-4cee-8c3d-9f5d4ab9d81c","resolution":{"observed_at":"2026-07-05T06:20:45.041586Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.052093Z","title":"Instance-warp: Saliency guided image warping for unsuper- vised domain adaptation","venue":null,"work_id":"36c3b935-71ae-40b9-bc81-86daf755ad8d","year":null},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:f27bda3cf0a4d9222aad7b5c60ffd26c2906c272f2a8be9f9711aa87b81c4b90","observation_id":"73fa001c-d8cb-44a5-99d8-c274029dc62f","resolution":{"observed_at":"2026-07-05T06:20:45.053596Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T06:20:45.056340Z","title":"apple” , GT:157 Count: 141 Spatial WarpingSimilarity Map Count: 159“stamp","venue":null,"work_id":"233da53f-e12e-4b93-aa1a-4f10efa046f0","year":2024},"citing_paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-07-03T15:29:40.807911Z"},"links":{"citing_paper":"/paper/2607.02139"},"observation_digest":"sha256:8b81102a6b5e932d60b60834515a6e6a7cd2e6c2e86a5248d381ef58df0fa90c","observation_id":"432aa6b1-e4c3-47be-9208-b21f82ddacbe","resolution":{"observed_at":"2026-07-05T06:20:45.057789Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}}],"paper":{"arxiv_id":"2607.02139","last_updated":"2026-07-02T13:16:04Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-07-07T00:07:37.820438Z","submitted_at":"2026-07-02T13:16:04Z","title":"AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting"},"reference_resolution":{"displayed":57,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":1,"verified_exact":1,"verified_fuzzy":55},"total_outbound_references":57},"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 10 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 0 inbound Pith citation observations for arXiv:2607.02139."}