{"as_of":"2026-08-15T02:28:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:d68a6612bbc79a10c19e98b45c5aa55e0a8054cd133e1b7e8511c6e197434631","coverage":[{"denominator":62,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":62,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-08T10:08:46.117747Z","state":"measured"},{"denominator":62,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":62,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-14T06:32:32.682623+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2607.06319/citation-record","integrity":"/paper/2607.06319/integrity","json":"/paper/2607.06319/citation-record.json","paper":"/paper/2607.06319"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.349070Z","title":"Multipath: Multiple probabilistic anchor trajectory hypotheses for behavior prediction,","venue":null,"work_id":"a5ca183d-2cef-4606-836a-10d7a4790b63","year":2020},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:96f306df80bcac423808559ad96896109a1c3695505bb1980a3697a6178c08ba","observation_id":"7d0f92a7-08c5-4424-8cef-84b87df1b6d0","resolution":{"observed_at":"2026-07-08T10:14:52.352925Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.493203Z","title":"Pnpnet: End-to-end perception and prediction with tracking in the loop,","venue":null,"work_id":"17e5d228-8ddf-4135-803e-8799d8ca4aca","year":2020},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:d28a1d5a6870e8c7c9139fef0091544aefb515798c2d74f5b8b6b4ca53e7cc53","observation_id":"c5214226-9590-4295-96a9-949baa69dcba","resolution":{"observed_at":"2026-07-08T10:14:52.494658Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.474374Z","title":"Motionnet: Joint perception and motion prediction for autonomous driving based on bird’s eye view maps,","venue":null,"work_id":"099094ff-8bfe-4beb-8b11-5c31dac061d3","year":2020},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:07e1d798accd90b87acb183990206ec74a13c3cc590f7bebac9b471c6516c3e9","observation_id":"08ccb325-52c6-44cb-84ce-489440541a94","resolution":{"observed_at":"2026-07-08T10:14:52.475887Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.429681Z","title":"Be-sti: Spatial-temporal integrated network for class-agnostic motion prediction with bidirectional enhancement,","venue":null,"work_id":"131c0e8f-0e2f-4181-abf0-12eb96f25921","year":2022},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:346f59ffc09a4c44be012daed4bb3ff8bf5d2e1966944061fde0a0f700832ef6","observation_id":"33c27236-a3c4-4ee5-8973-902a1295c294","resolution":{"observed_at":"2026-07-08T10:14:52.432229Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.471936Z","title":"Sparse pedestrian character learning for trajectory prediction,","venue":null,"work_id":"d2fa5499-2fde-4512-a722-74facadd8935","year":2024},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:ef19f7adc73efeb271ffa6762a76870ff89847ca10fb20ef4aa7232268d9dac7","observation_id":"b708ecd8-217d-4ee8-96ce-2bf6dd61a7e4","resolution":{"observed_at":"2026-07-08T10:14:52.473531Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.318034Z","title":"Mean teachers are better role mod- els: Weight-averaged consistency targets improve semi-supervised deep learning results,","venue":null,"work_id":"fa02e6dc-06ca-4d2a-9864-b175414fe3ed","year":2017},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:558a6bbf1283af2c196f1c95fd0552c570f3fc64f31d73d79c24110aa1e7b689","observation_id":"e59e86c8-ab28-44d4-8d42-4f98f306c45c","resolution":{"observed_at":"2026-07-08T10:14:52.319427Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.476782Z","title":"Weakly supervised class- agnostic motion prediction for autonomous driving,","venue":null,"work_id":"90a6f047-c531-4bcc-8b54-2f4f7d06949f","year":2023},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:8ed620b6c536afacbe93f938258b8348c2a2f7f968c830fddcb509f6556265d9","observation_id":"bc240814-1207-4404-81d3-1619b6cbf513","resolution":{"observed_at":"2026-07-08T10:14:52.478246Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.483955Z","title":"Scalability in perception for autonomous driving: Waymo open dataset,","venue":null,"work_id":"280c02e3-ba9d-473c-8702-f727aed40a85","year":2020},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:619c21762b252693c6c287ec1031ee201f4bb094d5e1610e5d36ada80f5bb707","observation_id":"3f9b806f-aee4-4ceb-89cc-d1681858e5ce","resolution":{"observed_at":"2026-07-08T10:14:52.485371Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.459653Z","title":"nuscenes: A multimodal dataset for autonomous driving,","venue":null,"work_id":"34991f90-7670-4567-afaa-fa8978db35e2","year":2020},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:937e1d036be4d1d41cac659c66d62beb9a2ca9efe8330c4942db1a8574a2867a","observation_id":"2d3ab580-2345-4fcc-b33e-3b39b757d7e2","resolution":{"observed_at":"2026-07-08T10:14:52.461158Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.333149Z","title":"St3d: Self-training for unsupervised domain adaptation on 3d object detection,","venue":null,"work_id":"570b39be-db09-42ef-8064-8376b7e4f2ef","year":2021},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:f0118de3c0fa22cbb40b5edbcf713ae4433159993d595678c50d2612d7d5003f","observation_id":"2ab286eb-1bf4-4511-92ff-d59bc5ee9042","resolution":{"observed_at":"2026-07-08T10:14:52.335127Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.352941Z","title":"St3d++: Denoised self-training for unsupervised domain adap- tation on 3d object detection,","venue":null,"work_id":"56c73d20-3e4f-4c88-89eb-afb0cc08f7fe","year":2022},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:2928449ef552cdf6d6fab01618957a718d167d5c3104d8362ccd0e2db6add0b7","observation_id":"394a9585-7a05-4d99-88b7-be4ab8c32290","resolution":{"observed_at":"2026-07-08T10:14:52.355200Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.328392Z","title":"Cross- domain contrastive learning for unsupervised domain adaptation,","venue":null,"work_id":"cab4ff91-d57e-4ab6-8035-3e58c25f5fb6","year":2022},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:be99d2c1da202c36459d09f70d623586e32f375120b647f1d6af1e199351c9cd","observation_id":"c5feac4b-dea4-414c-8bd0-f0c4bbdf4197","resolution":{"observed_at":"2026-07-08T10:14:52.330218Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.433128Z","title":"Deformation and corre- spondence aware unsupervised synthetic-to-real scene flow estimation for point clouds,","venue":null,"work_id":"e1863d34-efdf-4cc4-b54a-720000a6fd6f","year":2022},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:488a59fef52bd2276f664722765494f1466429a668208ee8295e8140363d40e5","observation_id":"1823cd44-94a3-4b54-b369-cc8f5d41cf35","resolution":{"observed_at":"2026-07-08T10:14:52.435543Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.450708Z","title":"C-sfda: A curriculum learning aided self-training framework for efficient source free domain adaptation,","venue":null,"work_id":"5b7a29c8-2017-4ac3-8ae0-9fdc02ee320b","year":2023},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:b738f69c84737fa329e6b95480e99d6bba4bfa473caf1f934ea7c995445aca7c","observation_id":"0d17d986-9780-4891-b94f-ad3a371f3d46","resolution":{"observed_at":"2026-07-08T10:14:52.452536Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.342397Z","title":"Proto- typical pseudo label denoising and target structure learning for domain adaptive semantic segmentation,","venue":null,"work_id":"9ff4317e-a939-4c46-aee1-2e81f2de8dba","year":2021},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:cd116e2072083d9208d87eadce7a316e3f9df3e1d60c88874e9642f7f8df74f2","observation_id":"c5dfe30f-3c23-4751-b50f-b33dcbdf8fbc","resolution":{"observed_at":"2026-07-08T10:14:52.344163Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.469144Z","title":"Pseudo label fusion with uncertainty estimation for semi-supervised cropping box regression,","venue":null,"work_id":"ffd4c8fb-b6a1-4ff3-b21f-88e5eadfd600","year":2024},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:a3955166d3f0af552d487773271bb84aa68e652818d452669869372056890b22","observation_id":"6641819a-4666-4f9f-a261-249a6140e626","resolution":{"observed_at":"2026-07-08T10:14:52.471054Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.488432Z","title":"Hybrid motion representation learning for prediction from raw sensor data","venue":null,"work_id":"3782ba56-fff5-4239-bd4f-c42074e1105a","year":2023},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:62a1c1bc804dd8d376a0991a123be0b404abca264d483fcc0371b6357341b057","observation_id":"e09e142f-d2b9-4d04-9ecf-81e74eafc95f","resolution":{"observed_at":"2026-07-08T10:14:52.489917Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.304984Z","title":"Footbots: A transformer-based architecture for motion prediction in soccer,","venue":null,"work_id":"a163fe3f-078a-4091-acc8-e9cc966704e8","year":2024},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:d8c1e01624343e7913c51e4abc1a6230501a4f5b1d126dbf9c0550e4fd8b4271","observation_id":"dc61826a-956c-406e-8de4-6846f83f999c","resolution":{"observed_at":"2026-07-08T10:14:52.306606Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.358901Z","title":"Pillarflow: End-to-end birds-eye-view flow estimation for autonomous driving,","venue":null,"work_id":"50cbc3c9-5fed-4965-bae5-df7ea9d57e2d","year":2020},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:a9faf535b204aad8b82632ae4f63223161fcefc86eea1e1d95f4fac72fd656c1","observation_id":"f94f4b64-14a2-4660-918c-abb7ff509d5f","resolution":{"observed_at":"2026-07-08T10:14:52.360503Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.338843Z","title":"Pwc-net: Cnns for optical flow using pyramid, warping, and cost volume,","venue":null,"work_id":"ed4ee2e1-93db-4334-9332-8ae8c8178a51","year":2018},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:cfce5f59e42ee9271a4cbd3cd8a9b26bc0b0f6d692e4ce0bcaf4371d4faea600","observation_id":"895ece86-6b3f-451a-8663-0eae2c3c0691","resolution":{"observed_at":"2026-07-08T10:14:52.340977Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.333427Z","title":"Smartrefine: A scenario-adaptive refinement framework for efficient motion prediction,","venue":null,"work_id":"467323b5-7954-4664-abe5-45090e777e1a","year":2024},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:a7b9b52830a0deabe79b6659e77ca0207d61d09b0173e2b9c5eb1378c7705b57","observation_id":"9087f64a-2c68-4f00-a93c-7f10b625b253","resolution":{"observed_at":"2026-07-08T10:14:52.335361Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.485929Z","title":"Semi-supervised class-agnostic motion prediction with pseudo label regeneration and bevmix,","venue":null,"work_id":"bb87c0d4-1815-4d00-aad0-c2fc283a485a","year":2024},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:f7899b319656258c97bfa7634950a30ef79df7f31c574769cc7f8206545a5b95","observation_id":"803d370b-b452-4bc3-8735-c66ea7b984d1","resolution":{"observed_at":"2026-07-08T10:14:52.487575Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.307269Z","title":"Self-supervised pillar motion learn- ing for autonomous driving,","venue":null,"work_id":"b9b011a8-611c-4d75-991d-d22470d36486","year":2021},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:393401258b22471dcf43d105cc135c5a90e8348679933a9f80af02b41017f2e3","observation_id":"e898132d-25ef-423d-8a36-c1c8f2c670fc","resolution":{"observed_at":"2026-07-08T10:14:52.308908Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.309574Z","title":"Self-supervised class-agnostic motion prediction with spatial and tem- poral consistency regularizations,","venue":null,"work_id":"4b8add85-0a55-4e44-b2ec-c19edb958672","year":2024},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:3e7245814d447b90127a52820ba48d3ee28e4c8b2f37a0226fff92669a332828","observation_id":"617de55b-c7e5-4ec4-b577-abc2548a16e6","resolution":{"observed_at":"2026-07-08T10:14:52.311126Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.345198Z","title":"Automated synthetic- to-real generalization,","venue":null,"work_id":"05b5e6de-bf04-4db0-876b-c9631d50f31f","year":2020},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:cbf1e182654b893d8d59e5a8fdcc92649244dd6fe72baef90be6bd08376bbc7d","observation_id":"4c0a6e9d-fe93-4fae-8d73-55906000e262","resolution":{"observed_at":"2026-07-08T10:14:52.347850Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.444593Z","title":"Synthetic-to-real pose estimation with geometric reconstruction,","venue":null,"work_id":"e070ef8a-c6f0-443c-b80f-98faebab8a66","year":2024},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:a5963f4b3aa52a0d050153fd65b8cd60eb93413086871c4954383838c1c9d3c5","observation_id":"b3eea4b8-cb87-4181-bbf1-efa4671022ca","resolution":{"observed_at":"2026-07-08T10:14:52.446476Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.477061Z","title":"From synthetic to real: Image dehazing collaborating with unlabeled real data,","venue":null,"work_id":"876f9835-97b4-4970-ac93-d87c6e670ea9","year":2021},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:7902436935b68814cfe4554f83e80936d78ae90bb97619564669062b00f9ddd5","observation_id":"62960cab-af8b-41d1-9f78-f7312a8e04a0","resolution":{"observed_at":"2026-07-08T10:14:52.479935Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.464102Z","title":"Textadapter: Self-supervised domain adaptation for cross-domain text recognition,","venue":null,"work_id":"b8fdc736-7016-4446-a365-7fe0cbc0261e","year":2024},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:8d984abfbd6b594bc2031865b55806826dcbb6bb7527bab714443e8462fa0847","observation_id":"4b42af8e-190b-4279-bd59-cdd040875866","resolution":{"observed_at":"2026-07-08T10:14:52.466173Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.467094Z","title":"Hardness-aware scene syn- thesis for semi-supervised 3d object detection,","venue":null,"work_id":"4dd13a7a-2c33-45bc-a3fd-040c5129f5af","year":2024},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:3e3525f9a10c23c2885b833bd668e6d11d1ef78cc64b415c97dcb6ffdc3d15a9","observation_id":"707a4066-fcb5-487b-971b-2222622439ce","resolution":{"observed_at":"2026-07-08T10:14:52.469238Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.473812Z","title":"Feature-aware adaptation and density alignment for crowd counting in video surveillance,","venue":null,"work_id":"986cc6e0-4adf-4780-8f08-41ebbf2311f9","year":2020},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:86f798952a3c1922dbcb789addc53dfacb6427522aeb7063ae571b33d4358e14","observation_id":"aa9adb43-6343-4e06-8275-1bd6b3e1a4ca","resolution":{"observed_at":"2026-07-08T10:14:52.475975Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.461669Z","title":"Audio–visual representation learning for anomaly events detection in crowds,","venue":null,"work_id":"2356faeb-1c70-47ab-8ec9-8c4e93d94246","year":2024},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:40f0fa08bf53b2713eba2fc40541f23d3b3174ef53f5b4e259c88c3c521604f3","observation_id":"074d148e-1eca-4424-8a37-14eb34c5babd","resolution":{"observed_at":"2026-07-08T10:14:52.463251Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.457298Z","title":"Pre-training on synthetic driving data for trajectory prediction,","venue":null,"work_id":"2a0afa7c-c4ca-4440-b502-a7bd96d8102d","year":2024},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:4a2e06472266c90ef2866673bfb09e73d8e52d66892d1b221e5f7b2513bdfd73","observation_id":"8e91a593-dded-4db6-b62d-4a65b8f268d0","resolution":{"observed_at":"2026-07-08T10:14:52.458874Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.464327Z","title":"Instance consistency regularization for semi-supervised 3d instance segmentation,","venue":null,"work_id":"c2bfc846-64c7-4d88-870b-45b80ea1acc4","year":2024},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:595f8afee86e7800bafdda31035b64bd03ec8138e1dd4abfd090e0b70efa31bc","observation_id":"128be677-58f2-4ae0-b25b-87db4f92789e","resolution":{"observed_at":"2026-07-08T10:14:52.465890Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.459207Z","title":"Reciprocal teacher-student learning via forward and feedback knowledge distilla- tion,","venue":null,"work_id":"48d397b5-3e13-4df3-ac24-4805755a84e9","year":2024},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:03a8e19c913d1a3554c4724a772bdd96e78a5b6f0ef0d2d67b71a23fb0ad3df2","observation_id":"9285eb22-2961-49a5-8753-971a9c14f52e","resolution":{"observed_at":"2026-07-08T10:14:52.460849Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.480872Z","title":"A large dataset to train convolutional networks for disparity, optical flow, and scene flow estimation,","venue":null,"work_id":"861a08a7-4654-4ba9-b963-2e32004385b7","year":2016},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:2778d3999d4cb32e475e69a8d0600a1c81c8bca2e625933d9e6c3683c3e66607","observation_id":"797d2ed9-655c-430f-afcb-a9ab75edce4e","resolution":{"observed_at":"2026-07-08T10:14:52.482834Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.440408Z","title":"Grand theft auto v,","venue":null,"work_id":"2fc6dcd0-a2d0-46fd-bb07-05469e778c21","year":null},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:dccc17134fbba1fa1dac4aeb2fd298b92a7ff7736427b7ae0152f7f685c3365e","observation_id":"7efe09f5-c011-44b5-b1c0-227086ca06b1","resolution":{"observed_at":"2026-07-08T10:14:52.443649Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.483654Z","title":"Spectral-gans for high-resolution 3d point-cloud generation,","venue":null,"work_id":"a060bf33-dad9-4199-8755-c27a04e52335","year":2020},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:c8c05687abac576c52cd74501ab7defc7b64f8944ba4a5e4cc40726f63acd469","observation_id":"a3e81dc2-7c66-4fb2-a336-2b14192f5c82","resolution":{"observed_at":"2026-07-08T10:14:52.485152Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.461890Z","title":"Generation for unsupervised domain adaptation: A gan-based approach for object classification with 3d point cloud data,","venue":null,"work_id":"7280ec15-cb44-49f1-96be-b5a8e1fddd12","year":2022},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:ff690fd1d49411bcaf789114af05c3110026df5ed726b69ccb4c0f3c88fc5ee1","observation_id":"450536bf-b99b-416b-9025-09e910b7a03a","resolution":{"observed_at":"2026-07-08T10:14:52.463458Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.478923Z","title":"Lidardm: Generative lidar simulation in a generated world,","venue":null,"work_id":"93a0e304-1dec-40b9-afe4-73f749f2f532","year":2025},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:3911fdc47c1bd661783f9459ea62a257d6cb5c37136df00be18588d59b260777","observation_id":"8da6a515-3ddf-4f0d-9855-d035cbec1d88","resolution":{"observed_at":"2026-07-08T10:14:52.480272Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.490772Z","title":"Ai models collapse when trained on recursively generated data","venue":null,"work_id":"44c4640c-31ae-40a5-b685-5c83ee368611","year":2024},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:3f9240163b28c2e5297b772361ba28a7774e937aed5b98abc2a7671d78bece5a","observation_id":"f6a67394-53ca-44b2-95a0-4441fefc037e","resolution":{"observed_at":"2026-07-08T10:14:52.492335Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T11:37:03.462466Z","title":"Aads: Augmented autonomous driving simulation using data-driven algorithms,","venue":null,"work_id":"6ea31084-bc60-4836-b67c-8e66f52f8dca","year":2019},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:0e173980299507ad00f6eda69e3fc9bf2e3e7eba18ee07fb8f73790463804aa3","observation_id":"d8839ae6-a9f5-474a-9ac9-f5cb723fe4de","resolution":{"observed_at":"2026-07-08T10:14:52.390074Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.391165Z","title":"Augmented lidar simulator for autonomous driving,","venue":null,"work_id":"b51e38f8-c735-4b9d-841c-406e3008f12f","year":1931},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:2e8f51979cd61a54ab6872db1ecc0eb2762cbc9b68d205aab0e1a14cf12a7c0d","observation_id":"b0c5adb6-6266-4478-aa34-a4254c38842b","resolution":{"observed_at":"2026-07-08T10:14:52.392648Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.423805Z","title":"Lidar- aug: A general rendering-based augmentation framework for 3d object detection,","venue":null,"work_id":"605279af-2c0a-4ee5-b17f-c50a62e63de7","year":2021},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:9dc839dbc1170803027b064f7e9f7475cba01bd75b4057c8a9d266c74dc69894","observation_id":"d1cd70a9-021b-43c4-97ab-428ffe652fb8","resolution":{"observed_at":"2026-07-08T10:14:52.430986Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.400151Z","title":"Blainder—a blender ai add- on for generation of semantically labeled depth-sensing data,","venue":null,"work_id":"f4274abe-da06-4941-b0f5-e2e685fcb04e","year":2021},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:de36bf4ce375bd873d0592ee4f4ff09847f61133fbfabd90981d6e2cbcf24b86","observation_id":"d234f28d-f897-41d2-9ced-cfd1890769b9","resolution":{"observed_at":"2026-07-08T10:14:52.402745Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.385974Z","title":"Lidarsim: Realistic lidar simulation by leveraging the real world,","venue":null,"work_id":"f21f3468-8b88-4cb1-9fa7-e5a68d4d44fb","year":2020},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:854db6b205e4eb30a81ca324de5d87c968a21326cc1e252115fbf9ee64417046","observation_id":"c273e26f-b451-4591-a40d-488572c59ad9","resolution":{"observed_at":"2026-07-08T10:14:52.387624Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-09T05:46:01.868366Z","title":"Carla: An open urban driving simulator","venue":null,"work_id":"3223d02c-9999-4b69-937f-5543f5ca592e","year":2017},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:a6227e0861777bc9e00c900be7cd45bb76759dfbd5feb17e27056e371c502db5","observation_id":"4be1734c-cdb9-47e4-836e-d24a6faef61e","resolution":{"observed_at":"2026-07-08T10:14:52.406556Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.466726Z","title":"Tang, “Cubvh,” https://github.com/ashawkey/cubvh, 2022","venue":null,"work_id":"efa6eff1-00c3-44b4-841a-235ff7ec05a4","year":2022},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:d530032ec16488fbdf659d3ce73966507d5910d9fb1d1c21fe9f10cb085decd2","observation_id":"fa05b25e-d453-4df1-9163-c2182ed3c652","resolution":{"observed_at":"2026-07-08T10:14:52.468226Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.419879Z","title":"Bevformer: learning bird’s-eye-view representation from lidar-camera via spatiotemporal transformers","venue":null,"work_id":"24c5accb-9595-470a-8ae0-1b06630e30cd","year":2024},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:55e30283b10368ff73475d1c98cfdaa21b93c7f92415de6747150da8ad11088e","observation_id":"26f6c7bb-0db5-49f4-b5fe-32fec47aca39","resolution":{"observed_at":"2026-07-08T10:14:52.425209Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.407752Z","title":"Bevformer v2: Adapting modern image backbones to bird’s-eye-view recognition via perspective supervision,","venue":null,"work_id":"90a90e44-ac04-446f-af4e-ea3c469f9f8e","year":2023},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:9abbbd314618de0df2496cb85f6ba8e4d70412b1d83118ddc5d0f6c1b62c1914","observation_id":"47ae0573-a037-447a-8769-1f11b926f257","resolution":{"observed_at":"2026-07-08T10:14:52.410473Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.380848Z","title":"Multitask learning,","venue":null,"work_id":"3a755228-080f-4d5c-8235-5e93415416d9","year":1997},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:46f1af6ebd0246801a490213f8da9dde528b8eba9ea6cdd0cc47d3b5df174f17","observation_id":"98192fa9-e7a6-4451-a192-816c38a0224a","resolution":{"observed_at":"2026-07-08T10:14:52.382569Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.397876Z","title":"A survey on multi-task learning,","venue":null,"work_id":"b9581ddf-58bd-42ff-9a0c-865ae2fd8d25","year":2021},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:b16c6e4c7914fc4fcefa60997dc4fe69e4f5ab8e72ab2e970b34f798085290c1","observation_id":"ce99ca3e-80e5-4e4f-9d15-92bcc6841388","resolution":{"observed_at":"2026-07-08T10:14:52.399367Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.455942Z","title":"Center-based 3d object detection and tracking,","venue":null,"work_id":"9ad4a2c1-d118-4928-88a1-7eb4ed2f178e","year":2021},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:d9e59b27c58bc503a9cc89338dd41d4c253e3ee48242cf4230c513a93d1bc152","observation_id":"602968e4-6a2a-479e-960f-2819f21ba2a8","resolution":{"observed_at":"2026-07-08T10:14:52.457626Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.453399Z","title":"Deep hough voting for 3d object detection in point clouds,","venue":null,"work_id":"55573256-39db-468e-9dd6-7c90fbb61440","year":2019},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:6059c1f27a82e784de2cd8b93cc991f4168cb288f788c079d4506054f29361af","observation_id":"c2b8b11a-c2b1-49bf-91bc-ebd5c46ef2f7","resolution":{"observed_at":"2026-07-08T10:14:52.454991Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.446231Z","title":"Pointgroup: Dual-set point grouping for 3d instance segmentation,","venue":null,"work_id":"7b5ee5a9-686d-4299-a9a8-e244d1c3d472","year":2020},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:c6e713a8034ced9cc5176b93c958345765797f5e6f2f683f7beea24ddc56c46e","observation_id":"f09dc2bf-d7c5-4c9b-aa66-29d80e148b73","resolution":{"observed_at":"2026-07-08T10:14:52.448373Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.384512Z","title":"3d instances as 1d kernels,","venue":null,"work_id":"0ab1f547-1bcf-4d69-bf93-a7afab7eab16","year":2022},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:a6c322191dc489589984eb8c7b141342f568c35aaa866416c2846cf84f63efe0","observation_id":"9ba6ba1b-8c38-48de-8924-14fb78c20e79","resolution":{"observed_at":"2026-07-08T10:14:52.386851Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.426466Z","title":"Centerlps: Segment instances by centers for lidar panoptic segmenta- tion,","venue":null,"work_id":"7abfb724-89f9-40cc-8614-576514b74d6d","year":2023},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:721ad09e5b23bc96a2a240dbd4cf848cb07539333e50af946a0459e1357c7001","observation_id":"29e854c1-feb2-4e14-ac78-bd27b064b1e0","resolution":{"observed_at":"2026-07-08T10:14:52.428574Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.416332Z","title":"Large scale interactive motion forecasting for autonomous driving: The waymo open motion dataset,","venue":null,"work_id":"8794dfc2-9af0-407d-80b6-5f27a3ad0c11","year":2021},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:394164d69e0f22c1cbf8a6d051d6262ee166eaa57917807e510b9c666240d0dd","observation_id":"815c6cc5-9cfa-4ffb-8aa7-0803dc989145","resolution":{"observed_at":"2026-07-08T10:14:52.421003Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.406107Z","title":null,"venue":null,"work_id":"4bda0b85-6267-4db0-a2bb-528d19936fa6","year":2018},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:ea9e992704c77ec2d9a11342f3088f59398815875c111c48b35db98c1a8f8306","observation_id":"e3c29ab8-836c-4309-830d-7c50b22fd692","resolution":{"observed_at":"2026-07-08T10:14:52.407851Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.411567Z","title":"Patchwork++: Fast and robust ground segmentation solving partial under-segmentation using 3d point cloud","venue":null,"work_id":"963001ce-9dc5-45c4-bfbe-28634e5fef11","year":2022},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:243050e9d153924d5e40f1743a32a785fe7318e5c56a9ad1c0392597bcb1c73d","observation_id":"120f75de-3217-403a-9a6e-832f9eb9a84f","resolution":{"observed_at":"2026-07-08T10:14:52.413979Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.415383Z","title":"3d people,","venue":null,"work_id":"871056a6-c9d6-4ae7-8f8b-fe9923172d92","year":2022},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:8fd883d011493095a5b6b73e5e1bc7c34cd385b84e5a6c8141042c303a7d661c","observation_id":"1a779274-35f4-4934-9c80-467e854f7fa7","resolution":{"observed_at":"2026-07-08T10:14:52.418464Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.443421Z","title":"Unsupervised domain adaptation by back- propagation,","venue":null,"work_id":"a23dcd41-bd52-4ae2-bcf1-7739410d1780","year":2015},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:9e06f24f3d9532d0227cc5934683d0f850e0e87eda26fb256c6494d67d46dc59","observation_id":"6953fc2d-1e05-493a-8559-de552dc87aa3","resolution":{"observed_at":"2026-07-08T10:14:52.445247Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T10:14:52.364338Z","title":"Glenet: Boosting 3d object detectors with generative label uncertainty estimation,","venue":null,"work_id":"585c5790-fed9-44a0-97e8-4104f39682af","year":2023},"citing_paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-07-08T10:08:46.117747Z"},"links":{"citing_paper":"/paper/2607.06319"},"observation_digest":"sha256:94a29a9297d38666ff625fabd2b2cdcd328181c07cdaaa2fca872697df6b3a4d","observation_id":"e2ae4e50-2194-4cfc-bbbe-bba7830a7ded","resolution":{"observed_at":"2026-07-08T10:14:52.366736Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2607.06319","last_updated":"2026-07-07T14:19:22Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-08T05:35:47.383151Z","submitted_at":"2026-07-07T14:19:22Z","title":"Synthetic-to-Real Translation for Class-Agnostic Motion Prediction"},"reference_resolution":{"displayed":62,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":1,"verified_exact":0,"verified_fuzzy":61},"total_outbound_references":62},"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":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"thesis":"As of 15 August 2026, this Paper Citation Record lists 62 of 62 outbound references and 0 inbound Pith citation observations for arXiv:2607.06319."}