{"as_of":"2026-08-05T05:53:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:6c7aae8ad644cfc9e1a6cd7769ade59b88df40d234da4f737e86316cc7db2274","coverage":[{"denominator":31,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":31,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-01T16:07:27.138506Z","state":"measured"},{"denominator":31,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":31,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-04T06:34:03.388597+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2607.18112/citation-record","integrity":"/paper/2607.18112/integrity","json":"/paper/2607.18112/citation-record.json","paper":"/paper/2607.18112"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:07:27.004635Z","title":"Panoptic segmentation,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.18112","last_updated":"2026-07-21T06:57:25Z","snapshot_observed_at":"2026-08-01T16:07:26.591542Z","submitted_at":"2026-07-20T16:08:57Z","title":"Occlusion-Aware Panoptic Segmentation with Joint Position Embedding and Occlusion-Level Attention","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-01T16:07:27.004635Z"},"links":{"citing_paper":"/paper/2607.18112"},"observation_digest":"sha256:a311811b42afa8c35cdcb4ce1e06690af78d93df47e85c4ce29b03746f18c096","observation_id":"494e2fa9-915c-479e-bcfe-673ffe34be2c","resolution":{"observed_at":"2026-08-01T16:07:27.004635Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:07:27.009878Z","title":"Panoptic feature pyramid networks,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.18112","last_updated":"2026-07-21T06:57:25Z","snapshot_observed_at":"2026-08-01T16:07:26.591542Z","submitted_at":"2026-07-20T16:08:57Z","title":"Occlusion-Aware Panoptic Segmentation with Joint Position Embedding and Occlusion-Level Attention","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-01T16:07:27.009878Z"},"links":{"citing_paper":"/paper/2607.18112"},"observation_digest":"sha256:dab364f67b5296e83ac5a83fe609f3983c553c486ad1828caa4760662ec4313a","observation_id":"5ce67f92-6818-4fcf-be89-4a52d02b27bd","resolution":{"observed_at":"2026-08-01T16:07:27.009878Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:07:27.014858Z","title":"Panoptic-deeplab: A simple, strong, and fast baseline for bottom-up panoptic segmentation,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.18112","last_updated":"2026-07-21T06:57:25Z","snapshot_observed_at":"2026-08-01T16:07:26.591542Z","submitted_at":"2026-07-20T16:08:57Z","title":"Occlusion-Aware Panoptic Segmentation with Joint Position Embedding and Occlusion-Level Attention","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-01T16:07:27.014858Z"},"links":{"citing_paper":"/paper/2607.18112"},"observation_digest":"sha256:3a915461b446d18114bd93662d48372a3e95e823652f1662fd1924beda9131fc","observation_id":"f1cbd0a3-4c51-4372-803a-25320bd7b7f2","resolution":{"observed_at":"2026-08-01T16:07:27.014858Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:07:27.019630Z","title":"Fully convolutional networks for panoptic segmentation,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.18112","last_updated":"2026-07-21T06:57:25Z","snapshot_observed_at":"2026-08-01T16:07:26.591542Z","submitted_at":"2026-07-20T16:08:57Z","title":"Occlusion-Aware Panoptic Segmentation with Joint Position Embedding and Occlusion-Level Attention","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-01T16:07:27.019630Z"},"links":{"citing_paper":"/paper/2607.18112"},"observation_digest":"sha256:e812f34e5b443b380b51f50a6cb596f9a151b3ebb58967651407b06d3ec10add","observation_id":"6ec49d82-bca1-4a5b-9737-0521dbb677d8","resolution":{"observed_at":"2026-08-01T16:07:27.019630Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:07:27.024405Z","title":"Per-pixel classification is not all you need for semantic segmentation,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.18112","last_updated":"2026-07-21T06:57:25Z","snapshot_observed_at":"2026-08-01T16:07:26.591542Z","submitted_at":"2026-07-20T16:08:57Z","title":"Occlusion-Aware Panoptic Segmentation with Joint Position Embedding and Occlusion-Level Attention","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-01T16:07:27.024405Z"},"links":{"citing_paper":"/paper/2607.18112"},"observation_digest":"sha256:ca67d7cf395252552a25e452ebc8a59e8ab95175986da939e0cef78e2e7264fd","observation_id":"ac798c56-bd50-46bc-aead-e9e79a4f59e1","resolution":{"observed_at":"2026-08-01T16:07:27.024405Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:07:27.029790Z","title":"Masked-attention mask transformer for universal image segmentation,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.18112","last_updated":"2026-07-21T06:57:25Z","snapshot_observed_at":"2026-08-01T16:07:26.591542Z","submitted_at":"2026-07-20T16:08:57Z","title":"Occlusion-Aware Panoptic Segmentation with Joint Position Embedding and Occlusion-Level Attention","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-01T16:07:27.029790Z"},"links":{"citing_paper":"/paper/2607.18112"},"observation_digest":"sha256:cd65dd4e6e8163454e5cca92c1b0009b14f1cc0f1373faec8b1256172bea76bc","observation_id":"504f22f8-9a1c-456e-8275-c10a6b873c90","resolution":{"observed_at":"2026-08-01T16:07:27.029790Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:07:27.034993Z","title":"Mask dino: Towards a unified transformer- based framework for object detection and segmentation,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.18112","last_updated":"2026-07-21T06:57:25Z","snapshot_observed_at":"2026-08-01T16:07:26.591542Z","submitted_at":"2026-07-20T16:08:57Z","title":"Occlusion-Aware Panoptic Segmentation with Joint Position Embedding and Occlusion-Level Attention","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-01T16:07:27.034993Z"},"links":{"citing_paper":"/paper/2607.18112"},"observation_digest":"sha256:f171c159a4a4cbedcd163b35f201b08af8a696cc6baf0d9068d63cd63e42f65e","observation_id":"752c9ff3-48e7-49ef-a035-41e3975fc3de","resolution":{"observed_at":"2026-08-01T16:07:27.034993Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:07:27.039423Z","title":"You only segment once: Towards real-time panoptic segmentation,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.18112","last_updated":"2026-07-21T06:57:25Z","snapshot_observed_at":"2026-08-01T16:07:26.591542Z","submitted_at":"2026-07-20T16:08:57Z","title":"Occlusion-Aware Panoptic Segmentation with Joint Position Embedding and Occlusion-Level Attention","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-01T16:07:27.039423Z"},"links":{"citing_paper":"/paper/2607.18112"},"observation_digest":"sha256:7d33189755cadad12b39a8819a08d6d62404cbe3f615fbd47e31fd20f016feba","observation_id":"55bacfda-038f-4090-bb6c-e8167761aa0f","resolution":{"observed_at":"2026-08-01T16:07:27.039423Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:07:27.043855Z","title":"Maskconver: Revisiting pure convolution model for panoptic segmentation,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.18112","last_updated":"2026-07-21T06:57:25Z","snapshot_observed_at":"2026-08-01T16:07:26.591542Z","submitted_at":"2026-07-20T16:08:57Z","title":"Occlusion-Aware Panoptic Segmentation with Joint Position Embedding and Occlusion-Level Attention","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-01T16:07:27.043855Z"},"links":{"citing_paper":"/paper/2607.18112"},"observation_digest":"sha256:1d3beedf584d5f78a6781a30c140ca20d5b0d33fe6cafd593dc109ae342b4371","observation_id":"8c405986-1d01-4cb6-a70f-e39a5aa9f077","resolution":{"observed_at":"2026-08-01T16:07:27.043855Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:07:27.048143Z","title":null,"venue":null,"work_id":null,"year":2000},"citing_paper":{"arxiv_id":"2607.18112","last_updated":"2026-07-21T06:57:25Z","snapshot_observed_at":"2026-08-01T16:07:26.591542Z","submitted_at":"2026-07-20T16:08:57Z","title":"Occlusion-Aware Panoptic Segmentation with Joint Position Embedding and Occlusion-Level Attention","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-01T16:07:27.048143Z"},"links":{"citing_paper":"/paper/2607.18112"},"observation_digest":"sha256:f0b6a4c6e415f25aafb573d1f0b1ca2d77abdacc4f0ef9fabb3fc3969f568549","observation_id":"682b9237-f2e1-481f-9e4c-24d290ff72fb","resolution":{"observed_at":"2026-08-01T16:07:27.048143Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:07:27.052390Z","title":"Coco-olac: A benchmark for occluded panoptic segmentation and image understanding,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.18112","last_updated":"2026-07-21T06:57:25Z","snapshot_observed_at":"2026-08-01T16:07:26.591542Z","submitted_at":"2026-07-20T16:08:57Z","title":"Occlusion-Aware Panoptic Segmentation with Joint Position Embedding and Occlusion-Level Attention","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-01T16:07:27.052390Z"},"links":{"citing_paper":"/paper/2607.18112"},"observation_digest":"sha256:95633aef9d7e67e98a6d0ea5b88d563c54d7e814e01e1ed7b8ec7e59d60df7a9","observation_id":"c138b326-bf70-47e4-b367-bcb1f264fbfa","resolution":{"observed_at":"2026-08-01T16:07:27.052390Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:07:27.056799Z","title":"Microsoft coco: Common objects in context,","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2607.18112","last_updated":"2026-07-21T06:57:25Z","snapshot_observed_at":"2026-08-01T16:07:26.591542Z","submitted_at":"2026-07-20T16:08:57Z","title":"Occlusion-Aware Panoptic Segmentation with Joint Position Embedding and Occlusion-Level Attention","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-01T16:07:27.056799Z"},"links":{"citing_paper":"/paper/2607.18112"},"observation_digest":"sha256:d17da6be37faea991ec278a7cc0c778362afaf3e6f6fae57f61648555b39c4cd","observation_id":"cf8c963d-7ed9-4e2d-ba4c-9f569645a016","resolution":{"observed_at":"2026-08-01T16:07:27.056799Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:07:27.060965Z","title":"Imagenet: A large-scale hierarchical image database,","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2607.18112","last_updated":"2026-07-21T06:57:25Z","snapshot_observed_at":"2026-08-01T16:07:26.591542Z","submitted_at":"2026-07-20T16:08:57Z","title":"Occlusion-Aware Panoptic Segmentation with Joint Position Embedding and Occlusion-Level Attention","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-01T16:07:27.060965Z"},"links":{"citing_paper":"/paper/2607.18112"},"observation_digest":"sha256:fc0deae0bb6ef81b5708e360d4fa0d9cbbf3ba1c75f68859b17b422b4ee3f4ab","observation_id":"c531e20b-ef45-4740-b2bd-f11e1fce68a2","resolution":{"observed_at":"2026-08-01T16:07:27.060965Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:07:27.065119Z","title":"The cityscapes dataset for semantic urban scene understanding,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2607.18112","last_updated":"2026-07-21T06:57:25Z","snapshot_observed_at":"2026-08-01T16:07:26.591542Z","submitted_at":"2026-07-20T16:08:57Z","title":"Occlusion-Aware Panoptic Segmentation with Joint Position Embedding and Occlusion-Level Attention","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-01T16:07:27.065119Z"},"links":{"citing_paper":"/paper/2607.18112"},"observation_digest":"sha256:1e8bf0eaf903bcd99835d7e3c5f1c7451d8bd0ac458df4270b9660fdb6cdf51e","observation_id":"debcc9df-87e9-4671-b91c-4b402206c5d7","resolution":{"observed_at":"2026-08-01T16:07:27.065119Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:07:27.069537Z","title":"Amodal instance segmentation with kins dataset,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.18112","last_updated":"2026-07-21T06:57:25Z","snapshot_observed_at":"2026-08-01T16:07:26.591542Z","submitted_at":"2026-07-20T16:08:57Z","title":"Occlusion-Aware Panoptic Segmentation with Joint Position Embedding and Occlusion-Level Attention","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-01T16:07:27.069537Z"},"links":{"citing_paper":"/paper/2607.18112"},"observation_digest":"sha256:9dbbf18dbabc0df9dfd2a341ccb27d2ed6668753233bdadb5c5510ef546baab0","observation_id":"8c9e7507-7c1d-42b8-be80-dae6877f1530","resolution":{"observed_at":"2026-08-01T16:07:27.069537Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:07:27.073601Z","title":"Semantic amodal segmentation,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.18112","last_updated":"2026-07-21T06:57:25Z","snapshot_observed_at":"2026-08-01T16:07:26.591542Z","submitted_at":"2026-07-20T16:08:57Z","title":"Occlusion-Aware Panoptic Segmentation with Joint Position Embedding and Occlusion-Level Attention","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-01T16:07:27.073601Z"},"links":{"citing_paper":"/paper/2607.18112"},"observation_digest":"sha256:03bfce960acbcae268fa7a0d74489e9fd909863bb8dfeb46c38d290f8d8252b1","observation_id":"44ce7c52-605d-4c10-9145-6cc002366266","resolution":{"observed_at":"2026-08-01T16:07:27.073601Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1603.00831","last_updated":"2016-05-03T23:55:38Z","snapshot_observed_at":"2026-08-03T05:59:06.882015Z","submitted_at":"2016-03-02T19:07:56Z","title":"MOT16: A Benchmark for Multi-Object Tracking","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1603.00831","snapshot_observed_at":"2026-08-01T16:07:27.077596Z","title":"Mot16: A benchmark for multi-object tracking,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2607.18112","last_updated":"2026-07-21T06:57:25Z","snapshot_observed_at":"2026-08-01T16:07:26.591542Z","submitted_at":"2026-07-20T16:08:57Z","title":"Occlusion-Aware Panoptic Segmentation with Joint Position Embedding and Occlusion-Level Attention","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-01T16:07:27.077596Z"},"links":{"cited_paper":"/paper/1603.00831","citing_paper":"/paper/2607.18112"},"observation_digest":"sha256:f5615779590d82bcf174798036793f71a10a2a49091d7be09aab5e98425b95aa","observation_id":"75eea44e-a0cc-4121-998d-4442495487cc","resolution":{"observed_at":"2026-08-01T16:07:27.077596Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:07:27.082262Z","title":"Attention is all you need,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.18112","last_updated":"2026-07-21T06:57:25Z","snapshot_observed_at":"2026-08-01T16:07:26.591542Z","submitted_at":"2026-07-20T16:08:57Z","title":"Occlusion-Aware Panoptic Segmentation with Joint Position Embedding and Occlusion-Level Attention","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-01T16:07:27.082262Z"},"links":{"citing_paper":"/paper/2607.18112"},"observation_digest":"sha256:2692651ef30bb36dd1ee4adecf1819e3a910c828af47bfde99ebadbea8de8e13","observation_id":"4e760896-06b4-4f44-9d47-e57b8b278b75","resolution":{"observed_at":"2026-08-01T16:07:27.082262Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1803.02155","last_updated":"2018-04-12T18:51:33Z","snapshot_observed_at":"2026-07-06T06:26:51.386842Z","submitted_at":"2018-03-06T13:13:11Z","title":"Self-Attention with Relative Position Representations","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1803.02155","snapshot_observed_at":"2026-08-01T16:07:27.086550Z","title":"Self-attention with relative position representations,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.18112","last_updated":"2026-07-21T06:57:25Z","snapshot_observed_at":"2026-08-01T16:07:26.591542Z","submitted_at":"2026-07-20T16:08:57Z","title":"Occlusion-Aware Panoptic Segmentation with Joint Position Embedding and Occlusion-Level Attention","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-01T16:07:27.086550Z"},"links":{"cited_paper":"/paper/1803.02155","citing_paper":"/paper/2607.18112"},"observation_digest":"sha256:a5d1ea4339b5e44f912fd4e4326d9ce25d095f1035f5cfe2e35985f62be4c372","observation_id":"feaacbdc-f3ff-48e6-985b-1b8a28cf4101","resolution":{"observed_at":"2026-08-01T16:07:27.086550Z","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":"2026-08-01T16:07:27.091288Z","title":"An image is worth 16x16 words: Transformers for image recognition at scale,","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2607.18112","last_updated":"2026-07-21T06:57:25Z","snapshot_observed_at":"2026-08-01T16:07:26.591542Z","submitted_at":"2026-07-20T16:08:57Z","title":"Occlusion-Aware Panoptic Segmentation with Joint Position Embedding and Occlusion-Level Attention","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-01T16:07:27.091288Z"},"links":{"cited_paper":"/paper/2010.11929","citing_paper":"/paper/2607.18112"},"observation_digest":"sha256:266478ebc7f04080cea13e5acb9f3858a61f626e29b354571f307620f63b57c5","observation_id":"dfe06377-c289-4bc6-8f0c-b43f7f931509","resolution":{"observed_at":"2026-08-01T16:07:27.091288Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:07:27.095706Z","title":"End-to-end object detection with transformers,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.18112","last_updated":"2026-07-21T06:57:25Z","snapshot_observed_at":"2026-08-01T16:07:26.591542Z","submitted_at":"2026-07-20T16:08:57Z","title":"Occlusion-Aware Panoptic Segmentation with Joint Position Embedding and Occlusion-Level Attention","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-01T16:07:27.095706Z"},"links":{"citing_paper":"/paper/2607.18112"},"observation_digest":"sha256:060471b9317e9cfc2ca0c6e5fc737d29d6f3ae0941cf2d9bb1af85a2a2f884fe","observation_id":"f16b9378-4b45-4cf9-b90d-da1e438f00ca","resolution":{"observed_at":"2026-08-01T16:07:27.095706Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2203.03605","last_updated":"2022-07-11T10:30:29Z","snapshot_observed_at":"2026-08-04T22:53:41.491205Z","submitted_at":"2022-03-07T18:55:26Z","title":"DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.03605","snapshot_observed_at":"2026-08-01T16:07:27.100322Z","title":"Dino: Detr with improved denoising anchor boxes for end-to-end object detection,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.18112","last_updated":"2026-07-21T06:57:25Z","snapshot_observed_at":"2026-08-01T16:07:26.591542Z","submitted_at":"2026-07-20T16:08:57Z","title":"Occlusion-Aware Panoptic Segmentation with Joint Position Embedding and Occlusion-Level Attention","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-01T16:07:27.100322Z"},"links":{"cited_paper":"/paper/2203.03605","citing_paper":"/paper/2607.18112"},"observation_digest":"sha256:0e46b1876c0ad77377befc6b78cac87aabcc5d04e28221a5c8f2b6e7008d3004","observation_id":"f1614a84-a8e5-41fb-a921-1a0a6688bb46","resolution":{"observed_at":"2026-08-01T16:07:27.100322Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:07:27.104854Z","title":"Deep occlusion-aware instance segmentation with overlapping bilayers,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.18112","last_updated":"2026-07-21T06:57:25Z","snapshot_observed_at":"2026-08-01T16:07:26.591542Z","submitted_at":"2026-07-20T16:08:57Z","title":"Occlusion-Aware Panoptic Segmentation with Joint Position Embedding and Occlusion-Level Attention","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-01T16:07:27.104854Z"},"links":{"citing_paper":"/paper/2607.18112"},"observation_digest":"sha256:3329098f1cc95be2b236ea5adefba6d95a77dc34dce006e317bb49c291313586","observation_id":"9af2f7bd-7e6c-4c63-a2ca-3abe1d69edfb","resolution":{"observed_at":"2026-08-01T16:07:27.104854Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:07:27.109118Z","title":"Compositional convolutional neural networks: A robust and interpretable model for object recognition under occlusion,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.18112","last_updated":"2026-07-21T06:57:25Z","snapshot_observed_at":"2026-08-01T16:07:26.591542Z","submitted_at":"2026-07-20T16:08:57Z","title":"Occlusion-Aware Panoptic Segmentation with Joint Position Embedding and Occlusion-Level Attention","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-01T16:07:27.109118Z"},"links":{"citing_paper":"/paper/2607.18112"},"observation_digest":"sha256:a87c8f734cbf2a06d9b2b384684612020e8a43267cdf240856a18f6138845bbd","observation_id":"c4ccff36-fcea-423b-888c-1a31cad27951","resolution":{"observed_at":"2026-08-01T16:07:27.109118Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:07:27.113315Z","title":"Occluded video instance segmentation: A benchmark,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.18112","last_updated":"2026-07-21T06:57:25Z","snapshot_observed_at":"2026-08-01T16:07:26.591542Z","submitted_at":"2026-07-20T16:08:57Z","title":"Occlusion-Aware Panoptic Segmentation with Joint Position Embedding and Occlusion-Level Attention","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-01T16:07:27.113315Z"},"links":{"citing_paper":"/paper/2607.18112"},"observation_digest":"sha256:98271dc5dde9f62b75ccf13f478b0f11f297ef881992b4a606603a2e0b99fefd","observation_id":"54aa2d87-b448-43db-85cd-38644b13aa74","resolution":{"observed_at":"2026-08-01T16:07:27.113315Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:07:27.117375Z","title":"Mose: A new dataset for video object segmentation in complex scenes,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.18112","last_updated":"2026-07-21T06:57:25Z","snapshot_observed_at":"2026-08-01T16:07:26.591542Z","submitted_at":"2026-07-20T16:08:57Z","title":"Occlusion-Aware Panoptic Segmentation with Joint Position Embedding and Occlusion-Level Attention","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-01T16:07:27.117375Z"},"links":{"citing_paper":"/paper/2607.18112"},"observation_digest":"sha256:8694e190ab13c27d6753569b274ea5c15ce5296d9d8f634bc2b79efc309e168b","observation_id":"c2cd3287-4344-4bb9-b11a-9b111710f89f","resolution":{"observed_at":"2026-08-01T16:07:27.117375Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:07:27.121598Z","title":"Mosev2: A more challenging dataset for video object segmentation in complex scenes,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.18112","last_updated":"2026-07-21T06:57:25Z","snapshot_observed_at":"2026-08-01T16:07:26.591542Z","submitted_at":"2026-07-20T16:08:57Z","title":"Occlusion-Aware Panoptic Segmentation with Joint Position Embedding and Occlusion-Level Attention","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-01T16:07:27.121598Z"},"links":{"citing_paper":"/paper/2607.18112"},"observation_digest":"sha256:d75cafe754ff5270aa73b1f26689509a36c48fc5c3f9869492860be61f21af26","observation_id":"058e396d-566a-4603-9147-4f05c8400f51","resolution":{"observed_at":"2026-08-01T16:07:27.121598Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:07:27.125750Z","title":"Swin transformer: Hierarchical vision transformer using shifted windows,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.18112","last_updated":"2026-07-21T06:57:25Z","snapshot_observed_at":"2026-08-01T16:07:26.591542Z","submitted_at":"2026-07-20T16:08:57Z","title":"Occlusion-Aware Panoptic Segmentation with Joint Position Embedding and Occlusion-Level Attention","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-01T16:07:27.125750Z"},"links":{"citing_paper":"/paper/2607.18112"},"observation_digest":"sha256:c7db02031b2c3433be1bb080477bd8f3fbb7af648da7676fcb61f78a4f945cf3","observation_id":"569c2f4b-86a5-4671-a841-e907b295991d","resolution":{"observed_at":"2026-08-01T16:07:27.125750Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:07:27.129961Z","title":"Roformer: Enhanced transformer with rotary position embedding,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.18112","last_updated":"2026-07-21T06:57:25Z","snapshot_observed_at":"2026-08-01T16:07:26.591542Z","submitted_at":"2026-07-20T16:08:57Z","title":"Occlusion-Aware Panoptic Segmentation with Joint Position Embedding and Occlusion-Level Attention","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-01T16:07:27.129961Z"},"links":{"citing_paper":"/paper/2607.18112"},"observation_digest":"sha256:49cf636436362d32fa0e1e440f0b115e4dda0c761fdd3d55d07426e498dcaf24","observation_id":"650a3a55-8393-4e57-a776-6d1aee0966b3","resolution":{"observed_at":"2026-08-01T16:07:27.129961Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:07:27.134385Z","title":"Deep residual learning for image recognition,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2607.18112","last_updated":"2026-07-21T06:57:25Z","snapshot_observed_at":"2026-08-01T16:07:26.591542Z","submitted_at":"2026-07-20T16:08:57Z","title":"Occlusion-Aware Panoptic Segmentation with Joint Position Embedding and Occlusion-Level Attention","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-01T16:07:27.134385Z"},"links":{"citing_paper":"/paper/2607.18112"},"observation_digest":"sha256:e8445c14fbfb1443af3832ca3073455e61c3512fa8f854b5b85ecbae129dc49a","observation_id":"ace1dd1b-47b9-4090-9163-92b0e840783a","resolution":{"observed_at":"2026-08-01T16:07:27.134385Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T16:07:27.138506Z","title":"Grad-cam: Visual explanations from deep networks via gradient-based localization,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.18112","last_updated":"2026-07-21T06:57:25Z","snapshot_observed_at":"2026-08-01T16:07:26.591542Z","submitted_at":"2026-07-20T16:08:57Z","title":"Occlusion-Aware Panoptic Segmentation with Joint Position Embedding and Occlusion-Level Attention","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-01T16:07:27.138506Z"},"links":{"citing_paper":"/paper/2607.18112"},"observation_digest":"sha256:6897078e950a7b0ae191504dd36baf61e1812c8a4be3c2c4afa0c16e43ef45ae","observation_id":"1d256145-254f-4576-a273-ee7bee1347d7","resolution":{"observed_at":"2026-08-01T16:07:27.138506Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.18112","last_updated":"2026-07-21T06:57:25Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-01T16:07:26.591542Z","submitted_at":"2026-07-20T16:08:57Z","title":"Occlusion-Aware Panoptic Segmentation with Joint Position Embedding and Occlusion-Level Attention"},"reference_resolution":{"displayed":31,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":31,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":31},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"thesis":"As of 5 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2607.18112."}