{"as_of":"2026-08-10T03:45:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:d08e2f2b10c9fe98550fa7a2ca13a9a271e5723200128d6a8eabda8133a16891","coverage":[{"denominator":33,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":33,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T13:14:40.943800Z","state":"measured"},{"denominator":33,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":33,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2505.22258/citation-record","integrity":"/paper/2505.22258/integrity","json":"/paper/2505.22258/citation-record.json","paper":"/paper/2505.22258"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:14:46.060887Z","title":"3d-mininet: Learning a 2d representation from point clouds for fast and efficient 3d lidar semantic segmentation.IEEE Robotics and Automation Letters, 5:5432–5439, 2020","venue":null,"work_id":"48ae3e29-f991-46d1-b50e-9719b69c32ca","year":2020},"citing_paper":{"arxiv_id":"2505.22258","last_updated":"2025-05-28T11:45:14Z","snapshot_observed_at":"2026-08-07T13:09:18.103550Z","submitted_at":"2025-05-28T11:45:14Z","title":"LiDAR Based Semantic Perception for Forklifts in Outdoor Environments","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T13:14:37.687951Z"},"links":{"citing_paper":"/paper/2505.22258"},"observation_digest":"sha256:63758ddf13d093564449bd6dc70c74d4341e11a08c8e429db31fc0aed77bffc6","observation_id":"5f634aac-19f6-4b6e-9ce4-b9b32cd862e2","resolution":{"observed_at":"2026-08-07T13:14:46.157963Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:14:45.810624Z","title":"Rangevit: Towards vision transformers for 3d semantic segmentation in autonomous driving","venue":null,"work_id":"707447ba-1f9c-4998-89e6-e99d4146f01e","year":2023},"citing_paper":{"arxiv_id":"2505.22258","last_updated":"2025-05-28T11:45:14Z","snapshot_observed_at":"2026-08-07T13:09:18.103550Z","submitted_at":"2025-05-28T11:45:14Z","title":"LiDAR Based Semantic Perception for Forklifts in Outdoor Environments","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T13:14:37.812721Z"},"links":{"citing_paper":"/paper/2505.22258"},"observation_digest":"sha256:9516f69e27629c2b54d22286ab4fd7b7b169d25a327e05c6e4cd8bb31b47b466","observation_id":"48db68a9-d939-4733-a005-f71ab6c9911d","resolution":{"observed_at":"2026-08-07T13:14:45.879134Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:14:45.654419Z","title":"Efficient human 3d localization and free space segmentation for human-aware mobile robots in warehouse facilities.Frontiers in Robotics and AI, 10:1283322, 10 2023","venue":null,"work_id":"660f5b72-5410-4b3b-8d97-ee1eb26899e0","year":2023},"citing_paper":{"arxiv_id":"2505.22258","last_updated":"2025-05-28T11:45:14Z","snapshot_observed_at":"2026-08-07T13:09:18.103550Z","submitted_at":"2025-05-28T11:45:14Z","title":"LiDAR Based Semantic Perception for Forklifts in Outdoor Environments","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T13:14:38.016658Z"},"links":{"citing_paper":"/paper/2505.22258"},"observation_digest":"sha256:e31a5d9fd9d97c9062841afdf766c8ffdaf30ca43548c4834fd7a46e1d4e3752","observation_id":"ccb836e5-ed1f-419c-9e63-efc9e5d38641","resolution":{"observed_at":"2026-08-07T13:14:45.730358Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:14:45.503954Z","title":"Behley, M","venue":null,"work_id":"4d5ef27c-33f1-4768-9d04-1fa3e232d38b","year":2019},"citing_paper":{"arxiv_id":"2505.22258","last_updated":"2025-05-28T11:45:14Z","snapshot_observed_at":"2026-08-07T13:09:18.103550Z","submitted_at":"2025-05-28T11:45:14Z","title":"LiDAR Based Semantic Perception for Forklifts in Outdoor Environments","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T13:14:38.134487Z"},"links":{"citing_paper":"/paper/2505.22258"},"observation_digest":"sha256:15b5f245b74f786106efd5347e33dab0f7cb3c8f98683df64bbcb9d18c49ae18","observation_id":"e8b8058a-3cc0-4739-8995-cfcea61f827c","resolution":{"observed_at":"2026-08-07T13:14:45.566310Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:14:45.361427Z","title":"Cenet: Toward concise and efficient lidar semantic segmentation for autonomous driv- ing","venue":null,"work_id":"75368621-dde2-4220-be82-9f164990e895","year":2022},"citing_paper":{"arxiv_id":"2505.22258","last_updated":"2025-05-28T11:45:14Z","snapshot_observed_at":"2026-08-07T13:09:18.103550Z","submitted_at":"2025-05-28T11:45:14Z","title":"LiDAR Based Semantic Perception for Forklifts in Outdoor Environments","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T13:14:38.255056Z"},"links":{"citing_paper":"/paper/2505.22258"},"observation_digest":"sha256:93d1b5a28cf4e09a439d8d9420cb0804acfbf398125d7fe995c0953272c29693","observation_id":"4936764c-50b4-4318-aa2c-1ea76b5d0d08","resolution":{"observed_at":"2026-08-07T13:14:45.425813Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2109.03805","last_updated":"2021-12-23T19:16:51Z","snapshot_observed_at":"2026-08-01T00:42:55.043956Z","submitted_at":"2021-09-08T17:45:37Z","title":"Panoptic nuScenes: A Large-Scale Benchmark for LiDAR Panoptic Segmentation and Tracking","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2109.03805","snapshot_observed_at":"2026-08-07T13:14:38.360907Z","title":"Panoptic nuscenes: A large-scale benchmark for lidar panoptic segmentation and tracking","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.22258","last_updated":"2025-05-28T11:45:14Z","snapshot_observed_at":"2026-08-07T13:09:18.103550Z","submitted_at":"2025-05-28T11:45:14Z","title":"LiDAR Based Semantic Perception for Forklifts in Outdoor Environments","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T13:14:38.360907Z"},"links":{"cited_paper":"/paper/2109.03805","citing_paper":"/paper/2505.22258"},"observation_digest":"sha256:612f9ac8d6ee73e2d72df21424c0b8469ba25975e0ab39cc9e9e437dcecd2226","observation_id":"029065da-ff36-4b8e-9b5a-23e671c60d32","resolution":{"observed_at":"2026-08-07T13:14:38.360907Z","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":"2026-08-07T13:14:45.184047Z","title":"Excavating in the wild: The goose-ex dataset for semantic segmentation","venue":null,"work_id":"710e7681-b572-4692-9f19-d30a270bc231","year":2024},"citing_paper":{"arxiv_id":"2505.22258","last_updated":"2025-05-28T11:45:14Z","snapshot_observed_at":"2026-08-07T13:09:18.103550Z","submitted_at":"2025-05-28T11:45:14Z","title":"LiDAR Based Semantic Perception for Forklifts in Outdoor Environments","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T13:14:38.470752Z"},"links":{"citing_paper":"/paper/2505.22258"},"observation_digest":"sha256:5ee0f86b7ce6109f8bfa8c652fa3c0232b064ef732326b953a21fe75e015ada7","observation_id":"c57cce68-6c6e-4d01-ae4f-5bdddd2acf32","resolution":{"observed_at":"2026-08-07T13:14:45.263400Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1803.11078","last_updated":"2018-12-13T22:02:18Z","snapshot_observed_at":"2026-07-06T06:30:53.584751Z","submitted_at":"2018-03-28T16:29:54Z","title":"Asymmetric Loss Functions and Deep Densely Connected Networks for Highly Imbalanced Medical Image Segmentation: Application to Multiple Sclerosis Lesion Detection","version":4},"cited_work":{"arxiv_id":"1803.11078","doi":null,"metadata_source":"pith","pith_arxiv_id":"1803.11078","snapshot_observed_at":"2026-08-07T13:14:41.085753Z","title":"Asymmetric Loss Functions and Deep Densely Connected Networks for Highly Imbalanced Medical Image Segmentation: Application to Multiple Sclerosis Lesion Detection","venue":"cs.CV","work_id":"feddab9a-59c5-4f00-b20d-8a84837a807e","year":2018},"citing_paper":{"arxiv_id":"2505.22258","last_updated":"2025-05-28T11:45:14Z","snapshot_observed_at":"2026-08-07T13:09:18.103550Z","submitted_at":"2025-05-28T11:45:14Z","title":"LiDAR Based Semantic Perception for Forklifts in Outdoor Environments","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T13:14:38.614533Z"},"links":{"cited_paper":"/paper/1803.11078","citing_paper":"/paper/2505.22258"},"observation_digest":"sha256:2a4b67f70661036827f7ca5b1209445857d7358376241fd2fc5205a662f95a9f","observation_id":"aa0e2c7b-c0d8-4f08-9ea2-09a7de259f89","resolution":{"observed_at":"2026-08-07T13:14:41.140248Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:14:44.960076Z","title":"Zhang, Shaoqing Ren, and Jian Sun","venue":null,"work_id":"1defef98-3d7e-4646-ba37-2ae8c50f274c","year":2016},"citing_paper":{"arxiv_id":"2505.22258","last_updated":"2025-05-28T11:45:14Z","snapshot_observed_at":"2026-08-07T13:09:18.103550Z","submitted_at":"2025-05-28T11:45:14Z","title":"LiDAR Based Semantic Perception for Forklifts in Outdoor Environments","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T13:14:38.783636Z"},"links":{"citing_paper":"/paper/2505.22258"},"observation_digest":"sha256:c2d77008d6ef964c2d9694b565c4785b5b57a93a55163ec352b4d43f64b7fbc7","observation_id":"af3737c6-ab94-42ca-ab96-0b1375e6bee5","resolution":{"observed_at":"2026-08-07T13:14:45.079993Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:14:44.816592Z","title":"ISO 8855:2011 Road vehicles — Vehicle dynamics and road-holding ability — V ocabulary","venue":null,"work_id":"011be3cf-c3fb-4253-b435-040b3076547c","year":2011},"citing_paper":{"arxiv_id":"2505.22258","last_updated":"2025-05-28T11:45:14Z","snapshot_observed_at":"2026-08-07T13:09:18.103550Z","submitted_at":"2025-05-28T11:45:14Z","title":"LiDAR Based Semantic Perception for Forklifts in Outdoor Environments","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T13:14:38.910643Z"},"links":{"citing_paper":"/paper/2505.22258"},"observation_digest":"sha256:9157baa0c5d02bec5ee8b7a56233b3e651fee5a3bddc84c76d26b0465104e28a","observation_id":"3873c130-3e73-485e-a94f-f90ad12ae4dc","resolution":{"observed_at":"2026-08-07T13:14:44.877576Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:14:44.625697Z","title":"Lidarnet: A boundary-aware domain adaptation model for lidar point cloud semantic, 2020","venue":null,"work_id":"8f2fc1fc-6249-4c16-b6f4-8f71186e2a3c","year":2020},"citing_paper":{"arxiv_id":"2505.22258","last_updated":"2025-05-28T11:45:14Z","snapshot_observed_at":"2026-08-07T13:09:18.103550Z","submitted_at":"2025-05-28T11:45:14Z","title":"LiDAR Based Semantic Perception for Forklifts in Outdoor Environments","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T13:14:39.059210Z"},"links":{"citing_paper":"/paper/2505.22258"},"observation_digest":"sha256:b49826454041ce6ece4f48f1edf02626fa471e04fe46ba3606b716862cdb5ded","observation_id":"2e2bed68-900c-4806-8fef-9a10f9c66109","resolution":{"observed_at":"2026-08-07T13:14:44.697416Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1412.6980","last_updated":"2017-01-30T01:27:54Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2014-12-22T13:54:29Z","title":"Adam: A Method for Stochastic Optimization","version":9},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.6980","snapshot_observed_at":"2026-08-07T13:14:39.131408Z","title":"Kingma and Jimmy Ba","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2505.22258","last_updated":"2025-05-28T11:45:14Z","snapshot_observed_at":"2026-08-07T13:09:18.103550Z","submitted_at":"2025-05-28T11:45:14Z","title":"LiDAR Based Semantic Perception for Forklifts in Outdoor Environments","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T13:14:39.131408Z"},"links":{"cited_paper":"/paper/1412.6980","citing_paper":"/paper/2505.22258"},"observation_digest":"sha256:658780b1c2801046860dd1b2c4272355d1209eb4fd540c7b4af60bf7dd5fdf9a","observation_id":"0f024f81-cfd0-4a8c-a6fc-a52150f992ec","resolution":{"observed_at":"2026-08-07T13:14:39.131408Z","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":"2026-08-07T13:14:44.463470Z","title":"Rethinking range view representation for lidar segmentation","venue":null,"work_id":"87af1baa-92db-4c63-9991-692b0fdd67b7","year":2023},"citing_paper":{"arxiv_id":"2505.22258","last_updated":"2025-05-28T11:45:14Z","snapshot_observed_at":"2026-08-07T13:09:18.103550Z","submitted_at":"2025-05-28T11:45:14Z","title":"LiDAR Based Semantic Perception for Forklifts in Outdoor Environments","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T13:14:39.215962Z"},"links":{"citing_paper":"/paper/2505.22258"},"observation_digest":"sha256:037afa0b6a404c234511fcc4edcfc3aff5d40a08d27cc16f1ff73fbaaabac91a","observation_id":"90b36b27-b655-4167-99f2-c38ebe60a550","resolution":{"observed_at":"2026-08-07T13:14:44.542519Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:14:44.284430Z","title":"Spherical transformer for lidar-based 3d recognition","venue":null,"work_id":"72fe7e03-b661-4ef8-9a1e-5ed64dc0e373","year":2023},"citing_paper":{"arxiv_id":"2505.22258","last_updated":"2025-05-28T11:45:14Z","snapshot_observed_at":"2026-08-07T13:09:18.103550Z","submitted_at":"2025-05-28T11:45:14Z","title":"LiDAR Based Semantic Perception for Forklifts in Outdoor Environments","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T13:14:39.287674Z"},"links":{"citing_paper":"/paper/2505.22258"},"observation_digest":"sha256:10466a315d22e4fe3128e0f57342f9141309c6397205732d7a7148d307afae1c","observation_id":"a722527e-767b-4dae-afe1-a9bec9823867","resolution":{"observed_at":"2026-08-07T13:14:44.400801Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:14:44.083677Z","title":"Feature pyramid networks for object detection","venue":null,"work_id":"3ac9bc89-5f0c-448d-9c2e-74383623a5c0","year":2017},"citing_paper":{"arxiv_id":"2505.22258","last_updated":"2025-05-28T11:45:14Z","snapshot_observed_at":"2026-08-07T13:09:18.103550Z","submitted_at":"2025-05-28T11:45:14Z","title":"LiDAR Based Semantic Perception for Forklifts in Outdoor Environments","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T13:14:39.366778Z"},"links":{"citing_paper":"/paper/2505.22258"},"observation_digest":"sha256:37e68d05259a4529b8bdd89f5fe6fc0d8c36af75e03c902d30a73645dd8c6811","observation_id":"1b63fede-3e46-4723-bc78-1c36a876e767","resolution":{"observed_at":"2026-08-07T13:14:44.183043Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:14:43.940988Z","title":null,"venue":null,"work_id":"9f2fe6c0-9745-4620-8e05-3a39d06681b4","year":2023},"citing_paper":{"arxiv_id":"2505.22258","last_updated":"2025-05-28T11:45:14Z","snapshot_observed_at":"2026-08-07T13:09:18.103550Z","submitted_at":"2025-05-28T11:45:14Z","title":"LiDAR Based Semantic Perception for Forklifts in Outdoor Environments","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T13:14:39.440969Z"},"links":{"citing_paper":"/paper/2505.22258"},"observation_digest":"sha256:d197d9edca10182f23c3e27b5a151b91156c4adf48c4db9655995f57e4bde268","observation_id":"8c6afe03-68d7-49ba-841c-e773a6546357","resolution":{"observed_at":"2026-08-07T13:14:43.997163Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:14:43.770232Z","title":"Semanticposs: A point cloud dataset with large quantity of dynamic instances, 2020","venue":null,"work_id":"b0ddf492-0e84-463f-a985-27c3677078f0","year":2020},"citing_paper":{"arxiv_id":"2505.22258","last_updated":"2025-05-28T11:45:14Z","snapshot_observed_at":"2026-08-07T13:09:18.103550Z","submitted_at":"2025-05-28T11:45:14Z","title":"LiDAR Based Semantic Perception for Forklifts in Outdoor Environments","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T13:14:39.513900Z"},"links":{"citing_paper":"/paper/2505.22258"},"observation_digest":"sha256:e6f421fe3a37bbf5c196a79e7192176f7bfe47abcf99912b7e3794f4ad31b89f","observation_id":"efeebf45-86e2-4191-917a-151d3e5a4d08","resolution":{"observed_at":"2026-08-07T13:14:43.851163Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:14:43.609280Z","title":"Sensor equivariance by lidar projection images","venue":null,"work_id":"71458441-bbc0-42b4-91f1-f2dacff0ff9d","year":2023},"citing_paper":{"arxiv_id":"2505.22258","last_updated":"2025-05-28T11:45:14Z","snapshot_observed_at":"2026-08-07T13:09:18.103550Z","submitted_at":"2025-05-28T11:45:14Z","title":"LiDAR Based Semantic Perception for Forklifts in Outdoor Environments","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T13:14:39.597735Z"},"links":{"citing_paper":"/paper/2505.22258"},"observation_digest":"sha256:1b364b58556e9b2f93d7a4a31e43c5ee458a64b6c04b9e4aa31daca7da037687","observation_id":"1464bc40-1c18-4028-8d7c-ba4bee2f28c4","resolution":{"observed_at":"2026-08-07T13:14:43.679943Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:14:43.441493Z","title":"Semanticthab: A high resolution lidar dataset, Feb","venue":null,"work_id":"9abf5318-a38a-4d9a-a240-fd5471bf7f8e","year":2025},"citing_paper":{"arxiv_id":"2505.22258","last_updated":"2025-05-28T11:45:14Z","snapshot_observed_at":"2026-08-07T13:09:18.103550Z","submitted_at":"2025-05-28T11:45:14Z","title":"LiDAR Based Semantic Perception for Forklifts in Outdoor Environments","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T13:14:39.683706Z"},"links":{"citing_paper":"/paper/2505.22258"},"observation_digest":"sha256:63d183f574511e44423193c49e3baf7531e7fcedfb73c671dd7dedcbe8627f49","observation_id":"3f546949-e124-4fb3-9e59-d2e87b54f8fb","resolution":{"observed_at":"2026-08-07T13:14:43.523570Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:14:43.204334Z","title":"Real time semantic segmentation of high resolution automotive lidar scans, 2025","venue":null,"work_id":"c9b74c68-078f-42a1-81b0-b61c5a2e8745","year":2025},"citing_paper":{"arxiv_id":"2505.22258","last_updated":"2025-05-28T11:45:14Z","snapshot_observed_at":"2026-08-07T13:09:18.103550Z","submitted_at":"2025-05-28T11:45:14Z","title":"LiDAR Based Semantic Perception for Forklifts in Outdoor Environments","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T13:14:39.780547Z"},"links":{"citing_paper":"/paper/2505.22258"},"observation_digest":"sha256:f93394673ed84e540c97f5f7ef4282de5bc564c20d3a5b722c87a2234ec47cac","observation_id":"4f8f03cf-410e-41ac-a50d-41f55d42cc0c","resolution":{"observed_at":"2026-08-07T13:14:43.358270Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:14:43.011503Z","title":"Height change feature based free space detection","venue":null,"work_id":"49e7ba28-a4f1-4e6b-a443-2b56fb33bd79","year":2023},"citing_paper":{"arxiv_id":"2505.22258","last_updated":"2025-05-28T11:45:14Z","snapshot_observed_at":"2026-08-07T13:09:18.103550Z","submitted_at":"2025-05-28T11:45:14Z","title":"LiDAR Based Semantic Perception for Forklifts in Outdoor Environments","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T13:14:39.878778Z"},"links":{"citing_paper":"/paper/2505.22258"},"observation_digest":"sha256:011790621389717a37157b971ee62dfe3d9acad5a2980ba6163ffe3a9982aa47","observation_id":"46d4406a-5946-42db-9ec7-c5a61477f89f","resolution":{"observed_at":"2026-08-07T13:14:43.115942Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:14:42.856041Z","title":"Scalability in perception for autonomous driving: Waymo open dataset","venue":null,"work_id":"2456d2d7-5f0f-40a4-9835-f401429a8a76","year":2020},"citing_paper":{"arxiv_id":"2505.22258","last_updated":"2025-05-28T11:45:14Z","snapshot_observed_at":"2026-08-07T13:09:18.103550Z","submitted_at":"2025-05-28T11:45:14Z","title":"LiDAR Based Semantic Perception for Forklifts in Outdoor Environments","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T13:14:39.950416Z"},"links":{"citing_paper":"/paper/2505.22258"},"observation_digest":"sha256:89416405253e4f84541d0989e0c9ebf7832f5ff77fb6163828d00dab4de330cf","observation_id":"39d93e33-84e1-4f16-a186-f9bb3e6040ee","resolution":{"observed_at":"2026-08-07T13:14:42.932566Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:14:42.702467Z","title":"Efficientnetv2: Smaller models and faster training","venue":null,"work_id":"6466b726-651c-4b74-9c4e-3fc498d3d9a0","year":2021},"citing_paper":{"arxiv_id":"2505.22258","last_updated":"2025-05-28T11:45:14Z","snapshot_observed_at":"2026-08-07T13:09:18.103550Z","submitted_at":"2025-05-28T11:45:14Z","title":"LiDAR Based Semantic Perception for Forklifts in Outdoor Environments","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T13:14:40.038620Z"},"links":{"citing_paper":"/paper/2505.22258"},"observation_digest":"sha256:a5c7f31e3214bb09af0090f6d696e6f0dde70de1ac5deb4b85c1cd2f2f2f3e5b","observation_id":"5b36e867-d5f3-466a-9fd0-3f16abdc7f52","resolution":{"observed_at":"2026-08-07T13:14:42.762719Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:14:42.573638Z","title":"Searching efficient 3d architectures with sparse point-voxel convolution","venue":null,"work_id":"c3a2039c-0ced-4d56-925e-5ad26d708321","year":null},"citing_paper":{"arxiv_id":"2505.22258","last_updated":"2025-05-28T11:45:14Z","snapshot_observed_at":"2026-08-07T13:09:18.103550Z","submitted_at":"2025-05-28T11:45:14Z","title":"LiDAR Based Semantic Perception for Forklifts in Outdoor Environments","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T13:14:40.129217Z"},"links":{"citing_paper":"/paper/2505.22258"},"observation_digest":"sha256:3118a5b06b14f1685dd51d2688b3796b1680631216cee5a1b9007db6290557d4","observation_id":"978077f8-0e2a-4592-8f51-616f2cb61642","resolution":{"observed_at":"2026-08-07T13:14:42.629703Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:14:42.433471Z","title":"Attention is all you need","venue":null,"work_id":"90977e9d-e293-4b46-bd93-452f6451d713","year":null},"citing_paper":{"arxiv_id":"2505.22258","last_updated":"2025-05-28T11:45:14Z","snapshot_observed_at":"2026-08-07T13:09:18.103550Z","submitted_at":"2025-05-28T11:45:14Z","title":"LiDAR Based Semantic Perception for Forklifts in Outdoor Environments","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T13:14:40.212131Z"},"links":{"citing_paper":"/paper/2505.22258"},"observation_digest":"sha256:a639af20f661bb449073d25483eb25b763d294a753b183c947774fd369d76cb0","observation_id":"232e181b-6678-4dd4-843f-cdfd41f3dc87","resolution":{"observed_at":"2026-08-07T13:14:42.510051Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:14:42.243333Z","title":"Vdbfusion: Flexible and efficient tsdf integration of range sensor data","venue":null,"work_id":"bc6e2e66-2b77-40e0-9e31-f01856daaef4","year":2022},"citing_paper":{"arxiv_id":"2505.22258","last_updated":"2025-05-28T11:45:14Z","snapshot_observed_at":"2026-08-07T13:09:18.103550Z","submitted_at":"2025-05-28T11:45:14Z","title":"LiDAR Based Semantic Perception for Forklifts in Outdoor Environments","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T13:14:40.321236Z"},"links":{"citing_paper":"/paper/2505.22258"},"observation_digest":"sha256:39a9488f1cb3fa0f16998441d2333e4524534b91b113d72d3f14fd1e339159a5","observation_id":"1a5c1601-3b08-421e-9706-94554e1ea464","resolution":{"observed_at":"2026-08-07T13:14:42.332362Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:14:42.006786Z","title":"KISS-ICP: In Defense of Point-to- Point ICP – Simple, Accurate, and Robust Registration If Done the Right Way.IEEE Robotics and Automation Letters (RA-L), 8(2):1029–1036,","venue":null,"work_id":"19c7898b-ad43-4ec5-8a0b-eac026818678","year":null},"citing_paper":{"arxiv_id":"2505.22258","last_updated":"2025-05-28T11:45:14Z","snapshot_observed_at":"2026-08-07T13:09:18.103550Z","submitted_at":"2025-05-28T11:45:14Z","title":"LiDAR Based Semantic Perception for Forklifts in Outdoor Environments","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T13:14:40.398199Z"},"links":{"citing_paper":"/paper/2505.22258"},"observation_digest":"sha256:484cba5718ece1233bda4901094ad29e716a6980250799fddbeed7c04a5b2a1c","observation_id":"00ff9f2e-99c4-4ea6-889a-bc85a9b7c336","resolution":{"observed_at":"2026-08-07T13:14:42.112954Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:14:41.847802Z","title":"Sfpnet: Sparse focal point network for semantic segmentation on general lidar point clouds","venue":null,"work_id":"d8454190-640c-4e7c-8e9d-5928f1430f24","year":2024},"citing_paper":{"arxiv_id":"2505.22258","last_updated":"2025-05-28T11:45:14Z","snapshot_observed_at":"2026-08-07T13:09:18.103550Z","submitted_at":"2025-05-28T11:45:14Z","title":"LiDAR Based Semantic Perception for Forklifts in Outdoor Environments","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T13:14:40.498484Z"},"links":{"citing_paper":"/paper/2505.22258"},"observation_digest":"sha256:7991bc641e1e301fc8f401dbe325f2fa75d689b9d6c8322425f3df120fec0100","observation_id":"245b6d59-9db5-49d8-9af0-80e5f1119670","resolution":{"observed_at":"2026-08-07T13:14:41.918013Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:14:41.636468Z","title":"Point transformer v3: Simpler, faster, stronger","venue":null,"work_id":"d66fd597-d5f2-4ed0-aaeb-592a7dba5358","year":2024},"citing_paper":{"arxiv_id":"2505.22258","last_updated":"2025-05-28T11:45:14Z","snapshot_observed_at":"2026-08-07T13:09:18.103550Z","submitted_at":"2025-05-28T11:45:14Z","title":"LiDAR Based Semantic Perception for Forklifts in Outdoor Environments","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T13:14:40.586099Z"},"links":{"citing_paper":"/paper/2505.22258"},"observation_digest":"sha256:f973f32f24b4112f186a48c1c6efa03b2861a3e0cda664749b58f2dcfd3ce996","observation_id":"f8927fd1-aea3-4102-bb1c-89c297d2c19a","resolution":{"observed_at":"2026-08-07T13:14:41.742078Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.04484","last_updated":"2025-03-06T14:06:24Z","snapshot_observed_at":"2026-08-09T05:53:09.558126Z","submitted_at":"2023-12-07T17:59:53Z","title":"FRNet: Frustum-Range Networks for Scalable LiDAR Segmentation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.04484","snapshot_observed_at":"2026-08-07T13:14:40.682365Z","title":"Fr- net: Frustum-range networks for scalable lidar segmentation.ArXiv, abs/2312.04484, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.22258","last_updated":"2025-05-28T11:45:14Z","snapshot_observed_at":"2026-08-07T13:09:18.103550Z","submitted_at":"2025-05-28T11:45:14Z","title":"LiDAR Based Semantic Perception for Forklifts in Outdoor Environments","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T13:14:40.682365Z"},"links":{"cited_paper":"/paper/2312.04484","citing_paper":"/paper/2505.22258"},"observation_digest":"sha256:960fb5fd34fd1b987ffff0a1115722fc9a939f421976629e42777a7797998bd0","observation_id":"1204b442-bed2-4898-8507-c80d5ebf42fd","resolution":{"observed_at":"2026-08-07T13:14:40.682365Z","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":"2026-08-07T13:14:41.399442Z","title":"Shufflenet: An extremely efficient convolutional neural network for mobile devices","venue":null,"work_id":"77694e2a-d7c8-45ec-9eb3-a233b84647da","year":2018},"citing_paper":{"arxiv_id":"2505.22258","last_updated":"2025-05-28T11:45:14Z","snapshot_observed_at":"2026-08-07T13:09:18.103550Z","submitted_at":"2025-05-28T11:45:14Z","title":"LiDAR Based Semantic Perception for Forklifts in Outdoor Environments","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T13:14:40.780542Z"},"links":{"citing_paper":"/paper/2505.22258"},"observation_digest":"sha256:830ebe00185c2def85dfaf20f6e18d83759517e118e8cd48d7713ea96089eb18","observation_id":"1c7f85c5-fd8b-492a-b609-d709ccf82d56","resolution":{"observed_at":"2026-08-07T13:14:41.545185Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:14:41.212676Z","title":null,"venue":null,"work_id":"f7f2141f-2e2a-49fc-87f7-6d8d9a8e9dc9","year":2021},"citing_paper":{"arxiv_id":"2505.22258","last_updated":"2025-05-28T11:45:14Z","snapshot_observed_at":"2026-08-07T13:09:18.103550Z","submitted_at":"2025-05-28T11:45:14Z","title":"LiDAR Based Semantic Perception for Forklifts in Outdoor Environments","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T13:14:40.849037Z"},"links":{"citing_paper":"/paper/2505.22258"},"observation_digest":"sha256:72c611930399c9b67aa1a3257f2c9fa423751b1ba54a0ab15f56987317ee8eff","observation_id":"0377501f-e603-4cb0-b769-987804a59bb0","resolution":{"observed_at":"2026-08-07T13:14:41.275195Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2011.10033","last_updated":"2020-11-19T18:53:11Z","snapshot_observed_at":"2026-08-08T11:47:40.062549Z","submitted_at":"2020-11-19T18:53:11Z","title":"Cylindrical and Asymmetrical 3D Convolution Networks for LiDAR Segmentation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2011.10033","snapshot_observed_at":"2026-08-07T13:14:40.943800Z","title":"Cylindrical and asymmetri- cal 3d convolution networks for lidar segmentation.arXiv preprint arXiv:2011.10033, 2020","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2505.22258","last_updated":"2025-05-28T11:45:14Z","snapshot_observed_at":"2026-08-07T13:09:18.103550Z","submitted_at":"2025-05-28T11:45:14Z","title":"LiDAR Based Semantic Perception for Forklifts in Outdoor Environments","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T13:14:40.943800Z"},"links":{"cited_paper":"/paper/2011.10033","citing_paper":"/paper/2505.22258"},"observation_digest":"sha256:90a2f4fa2800246c883d8375d7c2db338a6cd8fa338a92f1d4281c40ada66fd4","observation_id":"92869673-745d-4f5b-aa7c-3c598d3568e7","resolution":{"observed_at":"2026-08-07T13:14:40.943800Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2505.22258","last_updated":"2025-05-28T11:45:14Z","latest_version":1,"primary_category":"cs.RO","snapshot_observed_at":"2026-08-07T13:09:18.103550Z","submitted_at":"2025-05-28T11:45:14Z","title":"LiDAR Based Semantic Perception for Forklifts in Outdoor Environments"},"reference_resolution":{"displayed":33,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":6,"verified_exact":1,"verified_fuzzy":26},"total_outbound_references":33},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2505.22258."}