{"as_of":"2026-08-09T02:56:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:d2010ba57ba0de932922aebe2010192cf73fde276138b7a592845dd071c2aaa7","coverage":[{"denominator":95,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":95,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T18:36:36.379783Z","state":"measured"},{"denominator":95,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":95,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2507.07831/citation-record","integrity":"/paper/2507.07831/integrity","json":"/paper/2507.07831/citation-record.json","paper":"/paper/2507.07831"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:35.694365Z","title":"Decomposed knowledge distilla- tion for class-incremental semantic segmentation","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:35.694365Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:4896c56e2ef675a7fc7abf3d817fa90b02c42d90d1cf720fb42413a5ccff3cde","observation_id":"40e208ad-a221-43de-b9ae-0d2be061eefb","resolution":{"observed_at":"2026-08-06T18:36:35.694365Z","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":"2026-08-06T18:36:35.774350Z","title":"Cascade r-cnn: Delv- ing into high quality object detection","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:35.774350Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:70be7b175581d002275207c33ff42daffe85c9d493ff1ceca989469e4fb66777","observation_id":"ddb6d150-a12d-4f8b-8f55-c0aab543f571","resolution":{"observed_at":"2026-08-06T18:36:35.774350Z","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":"2026-08-06T18:36:35.855936Z","title":"End-to- end object detection with transformers","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:35.855936Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:6d5e84cf791fdf3d1a49d591396f1ab696069336ee2687504452032eb011b916","observation_id":"33a35e18-5fd6-48af-815f-e39fa2758703","resolution":{"observed_at":"2026-08-06T18:36:35.855936Z","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":"2026-08-06T18:36:35.905619Z","title":"End-to-end incre- mental learning","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:35.905619Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:580774052803eff8cf424a2c908da1d20cee0456fc9e62406f8fe49818565f43","observation_id":"173ccf18-1b81-4ace-b830-f930340f071c","resolution":{"observed_at":"2026-08-06T18:36:35.905619Z","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":"2026-08-06T18:36:35.912791Z","title":"Modeling the background for incremental learning in semantic segmentation","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:35.912791Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:4da12816f88f0be8f8684d99399a123d71706a62bd7c4eaacdfe3d49bd145919","observation_id":"636e035a-7e7a-4af2-8466-5a2b892637ae","resolution":{"observed_at":"2026-08-06T18:36:35.912791Z","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":"2026-08-06T18:36:35.918387Z","title":"Com- former: Continual learning in semantic and panoptic seg- mentation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:35.918387Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:cda6a955ed4b663f20df185c232f69564f1ba147c8825a79f4a6087f690c34cd","observation_id":"d8806aef-810e-4d51-9413-6aeb1799c8bc","resolution":{"observed_at":"2026-08-06T18:36:35.918387Z","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":"2026-08-06T18:36:35.922792Z","title":"Ssul: Semantic segmentation with unknown label for exemplar- based class-incremental learning","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:35.922792Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:5b900e8949dadce485da316d3f874bb3308ad9b2dfdbf3ab78b5022f6f61eabd","observation_id":"75fd31cb-3903-4460-b625-3d25076a45f7","resolution":{"observed_at":"2026-08-06T18:36:35.922792Z","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":"2026-08-06T18:36:35.928252Z","title":"Ssul: Semantic segmentation with unknown label for exemplar- based class-incremental learning","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:35.928252Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:5bda1ff07ee5f2eb9a398f058d576cb3c49141ff5a6095396388657d67d94adb","observation_id":"a521d222-cfaa-4b7c-be33-449e2a423571","resolution":{"observed_at":"2026-08-06T18:36:35.928252Z","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":"2026-08-06T18:36:35.932916Z","title":"Riemannian walk for incremen- tal learning: Understanding forgetting and intransigence","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:35.932916Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:50752eb4c0f7fdee9dcd97fcd0211e2a4cd65fca985af5d394b297c37aa04eea","observation_id":"fac3a53d-67f5-44e5-9c0f-6925dd5a33de","resolution":{"observed_at":"2026-08-06T18:36:35.932916Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1812.00420","last_updated":"2019-01-09T11:11:47Z","snapshot_observed_at":"2026-07-06T07:18:30.039631Z","submitted_at":"2018-12-02T16:39:19Z","title":"Efficient Lifelong Learning with A-GEM","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1812.00420","snapshot_observed_at":"2026-08-06T18:36:35.937533Z","title":"Efficient lifelong learning with a- gem","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:35.937533Z"},"links":{"cited_paper":"/paper/1812.00420","citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:bb461469b513a70c9d95231cb65ef6a61e4876a615dbde0cfff2a37d17bbc2b0","observation_id":"152be923-460e-4cb8-a1a2-ba21bc2f59b1","resolution":{"observed_at":"2026-08-06T18:36:35.937533Z","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":"2026-08-06T18:36:35.942852Z","title":"A survey on graph neural networks and graph transformers in computer vision: A task-oriented perspective","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:35.942852Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:b70ab9b27503939ff16cd94a388b00d148ed30032dcd34bdc75a3d484ea7cbee","observation_id":"9a45ca4c-4832-416c-bf15-abec2351943b","resolution":{"observed_at":"2026-08-06T18:36:35.942852Z","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":"2026-08-06T18:36:35.947313Z","title":"Strike a balance in continual panoptic segmentation, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:35.947313Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:9ea4db6b5698707fda257ede5fb71f997f9ea81e3d829709c6f4ed8b80aa35d3","observation_id":"a1f6419d-c9f6-4ab6-a765-302f38314f0f","resolution":{"observed_at":"2026-08-06T18:36:35.947313Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1412.7062","last_updated":"2016-06-07T04:00:08Z","snapshot_observed_at":"2026-07-06T04:04:27.398466Z","submitted_at":"2014-12-22T17:18:33Z","title":"Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.7062","snapshot_observed_at":"2026-08-06T18:36:35.951683Z","title":"Semantic image segmentation with deep convolutional nets and fully connected crfs","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:35.951683Z"},"links":{"cited_paper":"/paper/1412.7062","citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:ffca15f61fe995fca455312d35592afbceca761621255582f4c7858c9c53c6b3","observation_id":"a43bb1f0-3eb2-4201-828b-1039508b34b9","resolution":{"observed_at":"2026-08-06T18:36:35.951683Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1706.05587","last_updated":"2017-12-05T18:06:21Z","snapshot_observed_at":"2026-08-07T13:44:53.690521Z","submitted_at":"2017-06-17T22:48:57Z","title":"Rethinking Atrous Convolution for Semantic Image Segmentation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1706.05587","snapshot_observed_at":"2026-08-06T18:36:35.956257Z","title":"Rethinking atrous convolution for semantic image segmentation","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:35.956257Z"},"links":{"cited_paper":"/paper/1706.05587","citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:d8ce98cf78a721035892c42c1946d97f98edd683edd11f4fa711a9361134927b","observation_id":"a8cf8d44-5dc5-41e6-b004-3e4c8e92748f","resolution":{"observed_at":"2026-08-06T18:36:35.956257Z","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":"2026-08-06T18:36:35.960777Z","title":"Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolu- tion, and fully connected crfs","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:35.960777Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:ce7cd384ae818f26027a6c0a26109fa6e35aa05cdc05d0b94dede74ba5adfbbc","observation_id":"bc78d4fb-7d7d-4af6-8d72-55be8525d694","resolution":{"observed_at":"2026-08-06T18:36:35.960777Z","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":"2026-08-06T18:36:35.965161Z","title":"Spgnet: Semantic prediction guidance for scene parsing","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:35.965161Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:e352ca5f2f932de5c1c57053619d613deb986bfb9f86ed2a111cc55266c7b2a0","observation_id":"50d64d28-dbd8-4a36-ba39-be1365dff3af","resolution":{"observed_at":"2026-08-06T18:36:35.965161Z","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":"2026-08-06T18:36:35.969955Z","title":"Per- pixel classification is not all you need for semantic segmen- tation","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:35.969955Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:fce56c7040c366a5bdb3caa94eca66ba77b10b9a7acc3c6e13beb332e64de30e","observation_id":"bd60be66-b83e-4a72-a79f-133b6bc17231","resolution":{"observed_at":"2026-08-06T18:36:35.969955Z","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":"2026-08-06T18:36:35.974831Z","title":"Masked-attention mask transformer for universal image segmentation","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:35.974831Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:f9146d67692a8417726fd0f27c26a23a2f039f58485b31ab7300a2e48b1f3913","observation_id":"77019db9-c662-4d20-ba1d-9e7e1a6311cc","resolution":{"observed_at":"2026-08-06T18:36:35.974831Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:37.780122Z","title":"Curriculum point prompting for weakly-supervised referring image segmentation","venue":null,"work_id":"fb296dd1-e321-455a-9e7c-eecd55cc424b","year":2024},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:35.980661Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:63ea9846a88970ec27edb04f0ca4fb7831aa4132e0662ad1b962847dff10aa3f","observation_id":"96468f65-08ac-4645-ad88-4e34b31fcf96","resolution":{"observed_at":"2026-08-06T18:36:37.784934Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:37.763240Z","title":"Learning without mem- orizing","venue":null,"work_id":"baa7e1f4-5b05-4da3-8fff-5e5c530e124c","year":null},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:35.985871Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:3a2e301851b9c853d860270b40e7bf2c4a3d3cb07a7d4e293158a051b184138f","observation_id":"9f7da49b-c131-44fd-a1eb-f03288ef8c6d","resolution":{"observed_at":"2026-08-06T18:36:37.768858Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:37.746323Z","title":"Podnet: Pooled outputs dis- tillation for small-tasks incremental learning","venue":null,"work_id":"d16e0c4e-a38a-4e79-9036-8f570e2579bc","year":2020},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:35.990638Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:b60d2947be8a0938393a04a7c2ef5c915b5c23a30791e0e0ddb7c0ea0f09cf6b","observation_id":"1b9e0971-86ba-4505-b13a-bcd10f7171b0","resolution":{"observed_at":"2026-08-06T18:36:37.751267Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:37.729487Z","title":"Plop: Learning without forgetting for contin- ual semantic segmentation","venue":null,"work_id":"d872d768-985a-44bd-9f92-357c88e6c7ac","year":2021},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:35.996049Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:00c795ef5b5e58c71ed099aa2753eb00ae249975124d780dfc66f25a93004e85","observation_id":"7c3c7f39-742a-44ed-bce6-878223160538","resolution":{"observed_at":"2026-08-06T18:36:37.734815Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:36.000479Z","title":"Dytox: Transformers for continual learning with dynamic token expansion","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.000479Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:ad39d84888b488322ac2758b1ba5995008d5e1f66fbfacb1344a27eb24c4660a","observation_id":"8ecaebe8-66d6-4c26-ae1d-51c542a3dad4","resolution":{"observed_at":"2026-08-06T18:36:36.000479Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.13148","last_updated":"2024-04-19T19:25:26Z","snapshot_observed_at":"2026-08-06T18:17:26.976886Z","submitted_at":"2024-04-19T19:25:26Z","title":"BACS: Background Aware Continual Semantic Segmentation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.13148","snapshot_observed_at":"2026-08-06T18:36:36.005949Z","title":"Bacs: Background aware continual semantic segmentation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.005949Z"},"links":{"cited_paper":"/paper/2404.13148","citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:c0a653da37ef7f41a938ef4791f6235d72973eeafce5aabb14269a65ae21c767","observation_id":"1efe9c69-bc29-4ceb-8265-be4b693c62c8","resolution":{"observed_at":"2026-08-06T18:36:36.005949Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:37.692499Z","title":"The pascal visual object classes (voc) challenge","venue":null,"work_id":"62b5525b-a2c3-492c-baf2-cb714961547b","year":2010},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.011752Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:f6f6d4a8baf097a5a4a31d210496d51ffec5ec75c9d8cc8442ff3cd8a4346887","observation_id":"14105e74-6b7b-4645-87f0-885efea68cef","resolution":{"observed_at":"2026-08-06T18:36:37.698604Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:37.675126Z","title":"Catastrophic forgetting in connectionist networks","venue":null,"work_id":"47db5028-30ae-40d0-9199-f2b6afb11b6b","year":1999},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.021694Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:d893887311f1c7e9dedffe8b594c69dc99cc27fefb7a53724a2bc191c1c67efe","observation_id":"62de6410-35b5-433d-bab9-1e4314218492","resolution":{"observed_at":"2026-08-06T18:36:37.680538Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:37.653860Z","title":"Multi-evidence filtering and fusion for multi-label classification, object de- tection and semantic segmentation based on weakly super- vised learning","venue":null,"work_id":"a1368a09-b85f-411a-91a4-528d3f2f0af6","year":null},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.027913Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:c633ebef5b5e482c8d7392d2ab2c7e0b765dcb0d5ac8b70e04cf9a6665a239a5","observation_id":"e7ee954e-b006-4e01-ad8a-52904098cb78","resolution":{"observed_at":"2026-08-06T18:36:37.659347Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:37.637126Z","title":"Continual segmentation with disentangled objectness learn- ing and class recognition","venue":null,"work_id":"6cbc410c-4e32-4bc3-8fe3-74e220ca5467","year":2024},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.033384Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:a1d78faa5650a2f77bfd096071e964c437967becb4a88c1ac4f474bd858bc7fd","observation_id":"9461a43e-4678-4537-bdac-2bf99de81294","resolution":{"observed_at":"2026-08-06T18:36:37.642657Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:37.615667Z","title":"Attribution-aware weight transfer: A warm- start initialization for class-incremental semantic segmenta- tion","venue":null,"work_id":"7004396f-de9a-4c9c-8a9d-c96e3340c02a","year":2023},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.038916Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:8c780982d39674559380f4213268375dcb45c83c5239046fe9e0be4ec2dfc9ba","observation_id":"279f0f74-acc2-4225-8f8b-3654cb870747","resolution":{"observed_at":"2026-08-06T18:36:37.625322Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:37.597845Z","title":"Simultaneous detection and segmentation","venue":null,"work_id":"3f4fbd9b-c878-4cbe-838f-209d5ca88868","year":2014},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.044570Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:04885cc7b2258baf0364b80cffe8bcde06477ad8404c291e687c76c770287525","observation_id":"0d2a24d5-f09e-465f-bd3d-3b47370e60c5","resolution":{"observed_at":"2026-08-06T18:36:37.603477Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:37.581517Z","title":"Clustering algorithms","venue":null,"work_id":"45ed0080-d44f-4664-8ab5-d219884b6c74","year":1975},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.049583Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:f5c9770d870f5a1917dff6e88e47c86c30d055bda9245015643149edab840e47","observation_id":"50f4dc4e-0d99-482d-9045-db091c9325b1","resolution":{"observed_at":"2026-08-06T18:36:37.586183Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:36.055137Z","title":"Deep residual learning for image recognition","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.055137Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:8aa8ffe548b254a014edf6a1ef0b1f7de8bc4becfbc00343e88b38609d960fac","observation_id":"98675c59-8718-4541-941f-83ad42b29ae5","resolution":{"observed_at":"2026-08-06T18:36:36.055137Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:37.553387Z","title":"Mask r-cnn","venue":null,"work_id":"b90a2d21-2ee8-4bbc-b7f3-bea5b1ecc522","year":2017},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.059884Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:905f73507f4609aa1978e7c7f51dd53609934e8e6442114ededdcdc2be5d2e55","observation_id":"ff736a3f-0aa1-44f6-8179-f64a916d5a2f","resolution":{"observed_at":"2026-08-06T18:36:37.558250Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:36.065625Z","title":"Non-local context encoder: Robust biomedical image segmentation against adversarial attacks","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.065625Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:7bba998bc3880f85c1ba88c1a96ef79d4fa12e0b85fa1578106b9e1ca3209670","observation_id":"b57cffa0-1b11-4d18-bba1-b18cbde2657d","resolution":{"observed_at":"2026-08-06T18:36:36.065625Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:37.526527Z","title":"Distilling the knowledge in a neural network","venue":null,"work_id":"fdb90c33-a4d0-4bbb-8147-d4717639eb4e","year":2015},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.070808Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:c18cce5109f54f3337e12c02dee87855cc9b641d4e2a60645ca90d5e7af71f2b","observation_id":"ab75a7f0-53d7-4da0-b210-252bddbdb82a","resolution":{"observed_at":"2026-08-06T18:36:37.531425Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:36.075820Z","title":"Learning a unified classifier incrementally via rebalancing","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.075820Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:c70ee8d9e0b522c2e92b08c9c7a951419244047145b57413e1059b4bbdd4e2ff","observation_id":"3d921752-defa-4451-ac12-c0c4ff90333b","resolution":{"observed_at":"2026-08-06T18:36:36.075820Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:37.484808Z","title":"Free-bloom: Zero-shot text-to-video gener- ator with llm director and ldm animator","venue":null,"work_id":"33462a46-f8f5-4753-b36c-318df6761b03","year":2023},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.081574Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:e5724a0459e0e4ff0fcfcf3abac55e98968871c48d119e1612859ab9ead169db","observation_id":"9330a01c-fe3a-466e-adad-324d98755e06","resolution":{"observed_at":"2026-08-06T18:36:37.490948Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.11697","last_updated":"2025-02-17T11:34:58Z","snapshot_observed_at":"2026-08-07T18:12:52.430250Z","submitted_at":"2025-02-17T11:34:58Z","title":"MVTokenFlow: High-quality 4D Content Generation using Multiview Token Flow","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.11697","snapshot_observed_at":"2026-08-06T18:36:36.086858Z","title":"Mvtokenflow: High-quality 4d content generation using multiview token flow","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.086858Z"},"links":{"cited_paper":"/paper/2502.11697","citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:997a079c92cb5feebcb11a15443f3194ee4e7282e0db36f5ba95a496ddd894df","observation_id":"80d581a5-8ed9-420d-89ee-4eb1727a1bb3","resolution":{"observed_at":"2026-08-06T18:36:36.086858Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:37.468949Z","title":"Ccnet: Criss-cross attention for semantic segmentation","venue":null,"work_id":"42f49107-bff7-4d38-9a63-519098c9c2be","year":2019},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.093316Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:eba1ba5c93f5a92c210ee1d2b2498a9faeeadf0ac3665c5519fa1d8f4afccef1","observation_id":"2bdb4819-7d0d-4ad8-97f2-dde2a1ff07b6","resolution":{"observed_at":"2026-08-06T18:36:37.474064Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:37.449563Z","title":"Oneformer: One transformer to rule universal image segmentation","venue":null,"work_id":"fe6a3df1-49d9-4683-96b2-151012e17c5d","year":2023},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.099796Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:b2f82caf61b24ae8d0c7f8aea1684fa8f528c7937d81fae575e2ba96b081ca02","observation_id":"dea15fa6-0e64-4511-8768-e83736e2c6eb","resolution":{"observed_at":"2026-08-06T18:36:37.456443Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:37.428231Z","title":"Vi- sual prompt tuning","venue":null,"work_id":"a8967dc6-a236-4bc4-aa98-9e847c26b470","year":2022},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.107023Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:e963831da0ae0223fba5356fe0ad46c11f0b9fc6b6f18fd42407fe54e38a215f","observation_id":"445658d4-5312-494e-9e2c-9b85a0ebbae8","resolution":{"observed_at":"2026-08-06T18:36:37.432790Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:37.411534Z","title":"Eclipse: Efficient continual learning in panoptic segmen- tation with visual prompt tuning","venue":null,"work_id":"9ccbcbe0-4c92-4d1f-b351-8135fda2df3c","year":2024},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.112419Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:025a03c0805e2e3e0f9474317ed9b8a8860e44c931a599f7a488a81a50652643","observation_id":"dff27aee-911b-4e2c-bcd4-b91507090bf1","resolution":{"observed_at":"2026-08-06T18:36:37.416695Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:37.393876Z","title":"Mask dino: Towards a unified transformer-based framework for object detection and segmentation","venue":null,"work_id":"7aa9f836-946a-4881-95ac-51b806795a26","year":2023},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.120908Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:5ffc75a7a0ea884b257fc1e6d533564522a8e174e625d7f43f6ba90f0dfa3dd3","observation_id":"b3184ffe-6b53-409f-a0db-aa723b6ed022","resolution":{"observed_at":"2026-08-06T18:36:37.399928Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:37.371545Z","title":"Learning without forgetting","venue":null,"work_id":"f16aff31-b21a-46fa-9b89-378cff6de5b1","year":2017},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.126703Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:e61192072d22fbbb60a19b120ed35c437f88dbb769c941029ba516aad0c5e11b","observation_id":"d3273682-b248-4f4c-a630-fe73764745bf","resolution":{"observed_at":"2026-08-06T18:36:37.376759Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:37.353328Z","title":"Structured attention network for re- ferring image segmentation","venue":null,"work_id":"82880c37-1611-4086-b1bb-2e29084b1915","year":1922},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.131566Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:9e8e26f46a77402002034f0b015de0171fe2a23740232fa018474dba1bea73f1","observation_id":"2a84e261-5387-42f1-8322-4b4bcd4a0404","resolution":{"observed_at":"2026-08-06T18:36:37.358958Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:37.333472Z","title":"Gradient episodic memory for continual learning","venue":null,"work_id":"dce1c009-2147-47ed-b522-2f5c9cfca512","year":2017},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.137316Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:b45f39e0f858b487eff021bff8655f434699957963ccc14be7317941d48e973c","observation_id":"4447ae72-c72c-4295-9bf0-757dcf439056","resolution":{"observed_at":"2026-08-06T18:36:37.339378Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:37.316833Z","title":"Packnet: Adding mul- tiple tasks to a single network by iterative pruning","venue":null,"work_id":"bf25d818-82ef-465f-9df4-f8cbada04544","year":2018},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.141601Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:be909a9c5893d99be44ad943bd67b55166e63354dada3ac893aa27b6e15a3d3c","observation_id":"d4a2e9d3-a1d2-4b96-856d-f156542049ce","resolution":{"observed_at":"2026-08-06T18:36:37.321835Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:37.299431Z","title":"Piggy- back: Adapting a single network to multiple tasks by learn- ing to mask weights","venue":null,"work_id":"5818f5d1-f56f-4493-a9e4-9369adb51f8e","year":2018},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.146184Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:4b1cc657d027eaec86f5b189ca9d2cc0e8e982a3f57f45b75dde1357660b7226","observation_id":"371b18fe-f275-40de-a01d-344a6320feac","resolution":{"observed_at":"2026-08-06T18:36:37.304887Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:37.281642Z","title":"Incremental learn- ing techniques for semantic segmentation","venue":null,"work_id":"272f8fee-93c0-4d4e-8ad0-eb6dd8bb939c","year":2019},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.150493Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:ceeee9edcc4e217deed36c567516152159e829206844366a1e11b6016e85c6db","observation_id":"66cce570-d1fe-481c-a927-5b344b871c41","resolution":{"observed_at":"2026-08-06T18:36:37.286810Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:37.263987Z","title":"Continual semantic segmentation via repulsion-attraction of sparse and disentan- gled latent representations","venue":null,"work_id":"ba9a502d-0bc2-44e9-8463-15097ab31db7","year":2021},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.155370Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:35a83f24916a98fb22e4f2cebea17d3b37996750b97e574b096606c24929e28f","observation_id":"9c081e59-ca9b-4d24-a42d-70667117e748","resolution":{"observed_at":"2026-08-06T18:36:37.270399Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:36.160873Z","title":"Learning to remember: A synaptic plasticity driven framework for continual learning","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.160873Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:464133ca696b3e4fad5b6537ff510ff6e154865eda8624b3456970f4bf2b2311","observation_id":"ec3bace0-a0f5-4232-abd9-daadfc4137e3","resolution":{"observed_at":"2026-08-06T18:36:36.160873Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:37.237405Z","title":"Class similarity weighted knowl- edge distillation for continual semantic segmentation","venue":null,"work_id":"6142cf6e-7e05-49e6-8410-93e29b24846f","year":2022},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.165407Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:1a0fb1446b67ea4aae2d7b2fa760f0ceb6004cbad05e0b8fe4c5d27d21b4d9dd","observation_id":"604b216c-1b0b-42ca-87f5-49282d5d67f0","resolution":{"observed_at":"2026-08-06T18:36:37.242244Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:37.220159Z","title":"icarl: Incremental classifier and representation learning","venue":null,"work_id":"bf99af46-db46-478a-ab1f-54a0a39d8431","year":2001},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.170526Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:12da88c84b61ad5e4e1ee9fa61ea03cfeb255786020666ba013dac728f04b3d7","observation_id":"a341a00d-76ee-4aca-903f-9888ae416d6c","resolution":{"observed_at":"2026-08-06T18:36:37.225171Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:37.201584Z","title":"Catastrophic forgetting, rehearsal and pseudorehearsal","venue":null,"work_id":"e303cc5a-db57-4d3f-9700-69e7beeca5d7","year":1995},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.175677Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:8d14aed540ada71fd8911c7f979ae4a79f22c0cea55222eb7c39eecae98a4950","observation_id":"9979b817-da93-4e8d-88fd-d109eecd34ca","resolution":{"observed_at":"2026-08-06T18:36:37.206809Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:37.184065Z","title":"Incremental learning for robust visual tracking","venue":null,"work_id":"e83c4f25-9984-45eb-9d0d-88f7d55631fc","year":2008},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.180902Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:74602e5797e4b411d55a5fc7e47bc8758ad51fe86747b7a1ae9af7212a9eac7b","observation_id":"1c2dea7e-0736-43d5-95bb-998fdd16ee61","resolution":{"observed_at":"2026-08-06T18:36:37.188981Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:37.165542Z","title":"Learning representations by back-propagating er- rors","venue":null,"work_id":"5c37874a-98cd-4b52-b1e1-ade632f1007f","year":1986},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.186148Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:a170b9dee519d88ec06ba50a846d77808c9f67adc14ccfd498888374a5a60aef","observation_id":"f3db8ff0-f20f-4557-a421-4d4d88faf776","resolution":{"observed_at":"2026-08-06T18:36:37.171066Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1606.04671","last_updated":"2022-10-22T14:34:44Z","snapshot_observed_at":"2026-08-05T07:46:46.355580Z","submitted_at":"2016-06-15T08:20:51Z","title":"Progressive Neural Networks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1606.04671","snapshot_observed_at":"2026-08-06T18:36:36.196729Z","title":"Progressive neural networks","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.196729Z"},"links":{"cited_paper":"/paper/1606.04671","citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:534e4a1645f7a1e6fc4fb9d27c6d24504d526ad1820a9606d576fe7b25a08439","observation_id":"6cf738ba-b762-49c1-9a02-09e20d11c649","resolution":{"observed_at":"2026-08-06T18:36:36.196729Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:37.147738Z","title":"Incrementer: Transformer for class-incremental semantic segmentation with knowl- edge distillation focusing on old class","venue":null,"work_id":"d677402e-7b63-4057-8cab-2f4ff03e1861","year":2023},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.201506Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:1b9809fc3bdd3db9cb897d6827901de5360e54fbaa81c3a3df5cbf535608ad67","observation_id":"260bee3d-7ef8-406d-a45d-370326e5ef49","resolution":{"observed_at":"2026-08-06T18:36:37.152700Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:36.206809Z","title":"Edadet: Open-vocabulary object detection using early dense alignment","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.206809Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:b1fc562e102dc9645bfc577335342a37d1c8d0b09a60cacea14ceb0db41cc1c1","observation_id":"bcb838c1-579c-4638-80be-2429d33795b5","resolution":{"observed_at":"2026-08-06T18:36:36.206809Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:37.118514Z","title":"Logoprompt: Synthetic text im- ages can be good visual prompts for vision-language models","venue":null,"work_id":"7b043b17-6ad6-4843-9cf0-4afe79e4800a","year":2023},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.211152Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:98d3a8368a4b837e340809e84003f9203a1f0693e9b74235e2d7fbf931a70d77","observation_id":"d9e00c9f-ab8f-4900-898f-4e33072ef505","resolution":{"observed_at":"2026-08-06T18:36:37.123403Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.11957","last_updated":"2024-04-18T07:22:38Z","snapshot_observed_at":"2026-07-06T18:02:02.384288Z","submitted_at":"2024-04-18T07:22:38Z","title":"The devil is in the object boundary: towards annotation-free instance segmentation using Foundation Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.11957","snapshot_observed_at":"2026-08-06T18:36:36.215682Z","title":"The devil is in the object bound- ary: Towards annotation-free instance segmentation using foundation models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.215682Z"},"links":{"cited_paper":"/paper/2404.11957","citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:c0ea008da618d0b912fde348830d1ac77c7ae3a66c4c3b5357ed9737210afde3","observation_id":"fd07def1-b17b-48a2-8eff-3e2d96bff023","resolution":{"observed_at":"2026-08-06T18:36:36.215682Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:37.101861Z","title":"Part2object: Hierarchical unsupervised 3d instance segmentation","venue":null,"work_id":"bc1dfe8a-f937-4ffe-9464-c8ce160daf98","year":2024},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.220433Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:aeb41ae2ca85871ac3895f43bbff65952d5ed3ea93e1560f147043445d06d38d","observation_id":"7b4b3e25-c353-42cd-8c9f-b97a5d1bea47","resolution":{"observed_at":"2026-08-06T18:36:37.106741Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:36.224797Z","title":"Plain-det: A plain multi-dataset object detector","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.224797Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:079b5ac483368d08af31019d6ee837645bf7eb0f2f1818a3b284522ab57a427d","observation_id":"44997287-b5d1-4563-83d4-d2d2c882cf9a","resolution":{"observed_at":"2026-08-06T18:36:36.224797Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:37.073529Z","title":"Continual learning with deep generative replay","venue":null,"work_id":"b1462775-7ae9-4b1c-9c4a-8bcc3e7f2746","year":2017},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.229299Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:9210cb25164086a28e1e948cfd72f4fd093026d0131b94f0b8932b85d6021b11","observation_id":"a3e2976f-2ca8-4aad-b8e7-6b22ec59a603","resolution":{"observed_at":"2026-08-06T18:36:37.079065Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:37.058475Z","title":"Calibrating cnns for life- long learning","venue":null,"work_id":"a6ea89ff-b63d-4149-a5d1-0e25a8155ff6","year":2020},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.233555Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:7e4c54aeda8e3db6744e47fe9f902718d1f00412c8ae07d378d4e03fd7e239a4","observation_id":"8b17c32c-9f39-4b49-823c-48bdd9eb92b2","resolution":{"observed_at":"2026-08-06T18:36:37.063146Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:37.042722Z","title":"Segmenter: Transformer for semantic segmenta- tion","venue":null,"work_id":"a6bf0106-0737-418d-aa55-5b5758a2ae39","year":2021},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.238271Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:3b00a3148d892461635cc0e24f89c278b703e3426de087974a99e38bef0f3a65","observation_id":"041f39ef-3af6-493d-87f3-27572d914320","resolution":{"observed_at":"2026-08-06T18:36:37.047560Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:36.242526Z","title":"Con- trastive grouping with transformer for referring image seg- mentation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.242526Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:794c0e8517ecac282accd857c1b07689fbcf97b93e3dc8e93cf86e158be8d697","observation_id":"c25fc1f2-d6fc-4d0f-938d-74983743b0f8","resolution":{"observed_at":"2026-08-06T18:36:36.242526Z","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":"2026-08-06T18:36:36.248785Z","title":"Temporal collection and distribution for referring video object segmentation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.248785Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:120e85e5a3bb49cb9888e03249350fb14343414bad32363ff5cc7358544fc6ba","observation_id":"c3a40bd4-2d8b-458e-94e4-9035e0e54520","resolution":{"observed_at":"2026-08-06T18:36:36.248785Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:37.004690Z","title":"Lifelong learning algorithms","venue":null,"work_id":"42fcf13b-0aca-47aa-8a37-a26009376759","year":1998},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.253917Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:6dd26205206bdebb25a37ffecaef0d966dd4d9c7d2340305657ed446f8b37c2e","observation_id":"a9211e1e-5f48-4fce-8926-b0ffa084a4d0","resolution":{"observed_at":"2026-08-06T18:36:37.009936Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:36.988650Z","title":"Learning to prompt for continual learning","venue":null,"work_id":"9000856b-c199-4abc-9e6b-93fc9d63cc39","year":null},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.258448Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:dd812c5d052e161b646fabd2984a61008aa50dc92a6bface8ccc9506d0ccf1cb","observation_id":"3473fa20-a580-45e8-bf8c-36a33596c190","resolution":{"observed_at":"2026-08-06T18:36:36.993623Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:36.972275Z","title":"Memory replay gans: Learning to generate new categories without forgetting","venue":null,"work_id":"c595338c-2fa4-4f95-9488-86bec5542932","year":2018},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.265292Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:568be600266410733fe6e2e42147b6ddad8e313896151632f16aa4df77c5b79d","observation_id":"b866e38c-80d3-4b41-a0b4-498375b8b2e4","resolution":{"observed_at":"2026-08-06T18:36:36.977877Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:36.270021Z","title":"Large scale incre- mental learning","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.270021Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:d3e337d51a1d0e48841ee44a6c8930b81b62b5d787cb7b49bcbcbcf9a0659975","observation_id":"55fdc7d1-78af-4298-aaa2-17cfd12e47c4","resolution":{"observed_at":"2026-08-06T18:36:36.270021Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:36.946130Z","title":"Endpoints weight fusion for class incremental semantic segmentation","venue":null,"work_id":"65f8c4c1-1ff7-4203-9254-2a043b5fb817","year":null},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.274821Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:2e7143eec5cae8c981def63365015c1d01f72099abf99de8949dc930227ce983","observation_id":"4a072444-52ff-46f8-afed-a062b6a426de","resolution":{"observed_at":"2026-08-06T18:36:36.950848Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:36.280125Z","title":"Segformer: Simple and efficient design for semantic segmentation with transform- ers","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":76,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.280125Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:d94b8efe8bc9061068789a4521fe3a437ac4793f6b72a6f12ace7df5a3bd04c4","observation_id":"736d4be6-76de-470e-8eec-be3942f935bb","resolution":{"observed_at":"2026-08-06T18:36:36.280125Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.14142","last_updated":"2024-07-19T09:19:29Z","snapshot_observed_at":"2026-07-06T18:48:53.833921Z","submitted_at":"2024-07-19T09:19:29Z","title":"Early Preparation Pays Off: New Classifier Pre-tuning for Class Incremental Semantic Segmentation","version":1},"cited_work":{"arxiv_id":"2407.14142","doi":null,"metadata_source":"pith","pith_arxiv_id":"2407.14142","snapshot_observed_at":"2026-08-06T18:36:36.446764Z","title":"Early Preparation Pays Off: New Classifier Pre-tuning for Class Incremental Semantic Segmentation","venue":"cs.CV","work_id":"c755e1b6-0a0b-4590-a92f-a8d787325987","year":2024},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.285029Z"},"links":{"cited_paper":"/paper/2407.14142","citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:d85a814ce81eaf893655f8d2bf416a8c336ab81b12f1623e9541850038de63c3","observation_id":"d2ede4b1-1f8c-4728-82ab-e3ca5c81bfcc","resolution":{"observed_at":"2026-08-06T18:36:36.453997Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:36.920441Z","title":"Early preparation pays off: New classifier pre-tuning for class incremental semantic segmen- tation","venue":null,"work_id":"53955eb0-ee8d-410f-9436-3ffd76dbda8f","year":2025},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":78,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.289947Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:b829212a8e0415536264c44298024dc37e952f3bff6fdb7b21fefb431cc5d2b1","observation_id":"889afb32-c9d5-40f5-bde7-ad425c612389","resolution":{"observed_at":"2026-08-06T18:36:36.925339Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:36.295124Z","title":"Der: Dy- namically expandable representation for class incremental learning","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":79,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.295124Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:6b83edb9ea80d00cbc39c5d7fcfb3818428ce21f8f08258e950e971b61fd3802","observation_id":"d957fa93-0c7c-46e3-aa4b-c30215f080f8","resolution":{"observed_at":"2026-08-06T18:36:36.295124Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:36.893559Z","title":"Bottom-up shift and reasoning for referring im- age segmentation","venue":null,"work_id":"fd57bac4-75b5-4f0a-833f-0825f8766e4a","year":2021},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":80,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.299567Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:0808e98e54cd235786c2691dc16b4a8180c0c6478995bf124625655f9305c1cc","observation_id":"43f32cb1-b068-40a3-bdd0-2f88cc4d089a","resolution":{"observed_at":"2026-08-06T18:36:36.898316Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1809.00916","last_updated":"2021-03-15T03:27:54Z","snapshot_observed_at":"2026-07-06T06:59:02.864276Z","submitted_at":"2018-09-04T12:22:10Z","title":"OCNet: Object Context Network for Scene Parsing","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1809.00916","snapshot_observed_at":"2026-08-06T18:36:36.304138Z","title":"Ocnet: Object context network for scene parsing","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":81,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.304138Z"},"links":{"cited_paper":"/paper/1809.00916","citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:4772567e42efe324e446dd828ffe09d6caab628229196584fdd19be7334de086","observation_id":"09982b3b-e781-4bac-b812-1d7195e5fb0c","resolution":{"observed_at":"2026-08-06T18:36:36.304138Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:36.878183Z","title":"Representation compensation networks for continual semantic segmentation","venue":null,"work_id":"8f2b6519-8219-4e29-8f7f-8ea34103a63b","year":2022},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":82,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.308678Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:2b8cf21306cf16894b5699a5915b5b6cfddd98ea6634f1ebfaf001eee4d24ec8","observation_id":"f9ebdb2a-b2e8-431f-a849-613443c2380b","resolution":{"observed_at":"2026-08-06T18:36:36.882782Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:36.862831Z","title":"Slca: Slow learner with classifier align- ment for continual learning on a pre-trained model","venue":null,"work_id":"ca72f6ec-9bbf-4951-a902-3a05e30ea0da","year":2023},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":83,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.313180Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:50328228ccab8aa9afef73326cc5e493569614384cfb9c07a03c2e5f0b6eef98","observation_id":"c8d6f319-8ce4-4c9f-a252-ab8860952236","resolution":{"observed_at":"2026-08-06T18:36:36.867526Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:36.847016Z","title":"Mining unseen classes via regional object- ness: A simple baseline for incremental segmentation","venue":null,"work_id":"7a919c5c-5762-471e-a454-e83db01989e7","year":2022},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":84,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.318133Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:559f42af694d9269f6edb0126db25882f1f2df345fd2e805fa81fbd281d71600","observation_id":"ff301541-b06a-4c70-8f12-06c1d54c02aa","resolution":{"observed_at":"2026-08-06T18:36:36.851963Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:36.832236Z","title":"Coinseg: Contrast inter-and intra-class representations for incremental segmentation","venue":null,"work_id":"e5075e99-a504-45db-951b-a51ec0e88277","year":2023},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":85,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.323249Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:252434aa4361bfb096d7bc6e498fadce9516d91c79a252d1690fb2eb1fed068b","observation_id":"9e51bf89-670f-4efb-b364-2a6cd2f2668f","resolution":{"observed_at":"2026-08-06T18:36:36.836879Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:36.328134Z","title":"Pyramid scene parsing network","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":86,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.328134Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:d7e8e1609575c2e70eb5866cd7b6dea537868d39c3356cf1fc605957d068949b","observation_id":"58410483-043d-4620-86e0-509aea21d5a8","resolution":{"observed_at":"2026-08-06T18:36:36.328134Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:36.803338Z","title":"Ddcot: Duty-distinct chain-of-thought prompting for multimodal reasoning in language models.Advances in Neu- ral Information Processing Systems, 36:5168–5191, 2023","venue":null,"work_id":"b3437572-c06f-43e5-b8a7-1b0b4f8eaae7","year":2023},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":87,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.332790Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:8f95e9c52862f9353f4df622cd1ce2768793643fcb5beb679e083096f94fced2","observation_id":"3439cc88-5a09-48c6-8df8-a51de2fe7ca5","resolution":{"observed_at":"2026-08-06T18:36:36.809147Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:36.337996Z","title":"Scene parsing through ade20k dataset","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":88,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.337996Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:d9b9bcca9fc0c47073b94712faf25b8b9913d74f677884cc53753eab81d8ddc4","observation_id":"c35b9e9d-af14-438c-84d7-18dcfa842c49","resolution":{"observed_at":"2026-08-06T18:36:36.337996Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:36.774648Z","title":"Continual semantic segmentation with automatic memory sample selection","venue":null,"work_id":"f79dc213-9e5a-484d-b64f-a7d69b0298d9","year":2023},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":89,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.342397Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:b1adbc81e4e5d8e1b798f8503b00ad6f5f70555979a16b949928fdd345f42ee2","observation_id":"6d47f25a-bce9-4d96-b0d3-ab058c7b30ab","resolution":{"observed_at":"2026-08-06T18:36:36.780055Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:36.753672Z","title":null,"venue":null,"work_id":"53105ca9-a086-415e-ac35-dcb38e587e69","year":null},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":90,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.346874Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:39b11cc0cfb78da4f120d8ca0a5909b88e232fbf38e3da57049b8b1b597caefd","observation_id":"c215e2c0-4098-4f05-a80c-13c6d10e4b91","resolution":{"observed_at":"2026-08-06T18:36:36.759718Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:36.736624Z","title":"Following previous works [7, 29, 43], we use ADE20k [88] to train and evaluate our model for both continual panoptic segmentation and continual se- mantic segmentation tasks","venue":null,"work_id":"c6d02a54-00c7-41ae-adfc-35c6dfd43d50","year":null},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":91,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.351283Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:d97055a4fa0eeb12069ce2e7651938a8f54866dbafed7b388eb8d084b0078d45","observation_id":"0c9a31df-2380-4ae2-b65a-8a14f6596124","resolution":{"observed_at":"2026-08-06T18:36:36.742789Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:36.718132Z","title":"As shown in Tab","venue":null,"work_id":"0dce62c0-9c37-4cad-8a4a-e382a4be9aad","year":null},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":92,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.356597Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:2743386dec8d2599fc083649ce8019711195876864ed359ef8fcb47a658e14d4","observation_id":"8182eaf0-420c-4a68-89c7-7bcef4ecb869","resolution":{"observed_at":"2026-08-06T18:36:36.724264Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:36.697253Z","title":"As shown in the Tab","venue":null,"work_id":"77606e98-7960-4355-8710-c7e5b7e39b6e","year":null},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":93,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.361457Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:962d31050247d10f04183b6737b4e2f5c632de7e80f9d61bf8bf1b5d09016a53","observation_id":"6b440d09-edbd-4df1-ac84-6ab0b015212b","resolution":{"observed_at":"2026-08-06T18:36:36.702831Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:36.677307Z","title":"7, we additionally compare our SimCIS with BalConpas [13] in the 100-5 continual semantic seg- mentation task","venue":null,"work_id":"64570019-9a8e-464d-af47-95dd344f99bd","year":null},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":94,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.366648Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:65766ddde4158f33d03fe34f4a2256e0a51c1b658fe0b01aa442ff2ae27a1ecf","observation_id":"6955f669-72eb-44c9-aeec-ff4fe405db1d","resolution":{"observed_at":"2026-08-06T18:36:36.682909Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:36.659033Z","title":"In the multi-scale feature generated by the pixel decoder, we choose the fea- ture with the highest resolution for clustering","venue":null,"work_id":"6f31d7d7-64f5-4614-b20e-21bb9e71d302","year":null},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":95,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.371009Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:d44e4e6af006f1d9d8465de6838f2a719db70bb9b80475b754ecca03742e8562","observation_id":"e9c94c54-6231-48ef-aa4d-6d2087abe71f","resolution":{"observed_at":"2026-08-06T18:36:36.663961Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:36.642288Z","title":"However, in our proposed Lazy Query Pre-alignment strategy, the query features have rich information","venue":null,"work_id":"17b6fe7d-8e4a-48b0-8ef7-9ae500fc027b","year":null},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":96,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.375371Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:f1204c73e72fc9d1f5d08bdef55a6aa7a5dcff911e885a5d7b5fdec76acf1029","observation_id":"0521e9cb-91e2-4277-94f7-f6f404d6a607","resolution":{"observed_at":"2026-08-06T18:36:36.647399Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:36:36.622802Z","title":"To ensure a fair comparison, we adopt the same Mask2Former [19] as our meta-architecture for im- age segmentation","venue":null,"work_id":"bed3fc56-3193-41ec-b69d-7d55677f18bc","year":null},"citing_paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation","version":1},"reference_index":97,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:36.379783Z"},"links":{"citing_paper":"/paper/2507.07831"},"observation_digest":"sha256:7eb10255a644334d7701911c85ee4b81661c7e10103df0a8d2344e669a26479f","observation_id":"26737a08-5774-433b-aac4-7f47cf10636d","resolution":{"observed_at":"2026-08-06T18:36:36.629435Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2507.07831","last_updated":"2025-07-10T15:03:10Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-07T12:32:26.784897Z","submitted_at":"2025-07-10T15:03:10Z","title":"Rethinking Query-based Transformer for Continual Image Segmentation"},"reference_resolution":{"displayed":95,"state_counts":{"malformed_identifier":2,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":38,"verified_exact":1,"verified_fuzzy":54},"total_outbound_references":95},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 95 of 95 outbound references and 0 inbound Pith citation observations for arXiv:2507.07831."}