{"as_of":"2026-08-09T19:51:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:0f1c9151b4849541347d5378a42e591a6e0d6c4db66e1a4e333b1e227537b31b","coverage":[{"denominator":35,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":35,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T15:08:03.997114Z","state":"measured"},{"denominator":35,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":35,"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/2505.16249/citation-record","integrity":"/paper/2505.16249/integrity","json":"/paper/2505.16249/citation-record.json","paper":"/paper/2505.16249"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:08:07.900067Z","title":"Learning foresightful dense visual affordance for de- formable object manipulation,","venue":null,"work_id":"52e543d4-094d-41ce-86bf-a3ce78e1643d","year":2023},"citing_paper":{"arxiv_id":"2505.16249","last_updated":"2025-05-23T03:16:57Z","snapshot_observed_at":"2026-08-09T05:27:59.436937Z","submitted_at":"2025-05-22T05:36:00Z","title":"Manipulating Elasto-Plastic Objects With 3D Occupancy and Learning-Based Predictive Control","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T15:08:00.117715Z"},"links":{"citing_paper":"/paper/2505.16249"},"observation_digest":"sha256:1cc58d7f41f901e577a250f9933b0f0d4be41cf7d44b0d36e66296752fbe4293","observation_id":"33d7eb5d-f0e8-402c-bde2-5b3151370cf0","resolution":{"observed_at":"2026-08-07T15:08:07.951056Z","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":"2026-08-07T15:08:07.814291Z","title":"Foldsformer: Learning sequential multi-step cloth ma- nipulation with space-time attention,","venue":null,"work_id":"f79a86cf-97de-425d-9684-396321a24056","year":2022},"citing_paper":{"arxiv_id":"2505.16249","last_updated":"2025-05-23T03:16:57Z","snapshot_observed_at":"2026-08-09T05:27:59.436937Z","submitted_at":"2025-05-22T05:36:00Z","title":"Manipulating Elasto-Plastic Objects With 3D Occupancy and Learning-Based Predictive Control","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T15:08:00.242368Z"},"links":{"citing_paper":"/paper/2505.16249"},"observation_digest":"sha256:557231d326d4ba983f50c08febf9ab81b915b159f7b2e48a9902f0e536bfcd58","observation_id":"55a0e4f9-eae9-44a1-8581-5f8a3037893d","resolution":{"observed_at":"2026-08-07T15:08:07.852864Z","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":"2026-08-07T15:08:07.675085Z","title":"Learning-based MPC with safety filter for constrained deformable linear object manipulation,","venue":null,"work_id":"a1c71900-be7e-4283-a98e-90ecc5445992","year":2024},"citing_paper":{"arxiv_id":"2505.16249","last_updated":"2025-05-23T03:16:57Z","snapshot_observed_at":"2026-08-09T05:27:59.436937Z","submitted_at":"2025-05-22T05:36:00Z","title":"Manipulating Elasto-Plastic Objects With 3D Occupancy and Learning-Based Predictive Control","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T15:08:00.369495Z"},"links":{"citing_paper":"/paper/2505.16249"},"observation_digest":"sha256:3434bfca6c41f4a75e628309c329b8e99b4037d55267fc9fdacf2e9f396cc1b7","observation_id":"a8db72be-5722-4a8c-8069-6d0a992acad7","resolution":{"observed_at":"2026-08-07T15:08:07.727284Z","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":"2026-08-07T15:08:07.553558Z","title":"RoboCraft: Learning to see, simulate, and shape elasto- plastic objects in 3D with graph networks,","venue":null,"work_id":"03e106bd-2637-4ef7-b495-4f2a83edf1be","year":2024},"citing_paper":{"arxiv_id":"2505.16249","last_updated":"2025-05-23T03:16:57Z","snapshot_observed_at":"2026-08-09T05:27:59.436937Z","submitted_at":"2025-05-22T05:36:00Z","title":"Manipulating Elasto-Plastic Objects With 3D Occupancy and Learning-Based Predictive Control","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T15:08:00.482063Z"},"links":{"citing_paper":"/paper/2505.16249"},"observation_digest":"sha256:29b7969161e48c301859513c2293691ea21195d31a4357d43efba47e77b8bfc9","observation_id":"4058a980-5908-41a8-942f-8ccd750c8861","resolution":{"observed_at":"2026-08-07T15:08:07.612526Z","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":"2026-08-07T15:08:07.347893Z","title":"DiffSRL: Learning dynamical state representation for deformable object manipulation with differentiable simulation,","venue":null,"work_id":"e9294350-86f2-4e71-a6f6-0889c5fe37ed","year":2022},"citing_paper":{"arxiv_id":"2505.16249","last_updated":"2025-05-23T03:16:57Z","snapshot_observed_at":"2026-08-09T05:27:59.436937Z","submitted_at":"2025-05-22T05:36:00Z","title":"Manipulating Elasto-Plastic Objects With 3D Occupancy and Learning-Based Predictive Control","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T15:08:00.616216Z"},"links":{"citing_paper":"/paper/2505.16249"},"observation_digest":"sha256:2a333782fb4110b5ad70b812e9b46ef3f381281b711ea0bce278be05396b86d3","observation_id":"a1856173-1b6d-42fd-8662-c0c4296420ee","resolution":{"observed_at":"2026-08-07T15:08:07.479891Z","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":"2026-08-07T15:08:07.182796Z","title":"Learning closed-loop dough manipulation using a differ- entiable reset module,","venue":null,"work_id":"def844b7-b2a1-408a-9d3f-6dd6a827ca12","year":2022},"citing_paper":{"arxiv_id":"2505.16249","last_updated":"2025-05-23T03:16:57Z","snapshot_observed_at":"2026-08-09T05:27:59.436937Z","submitted_at":"2025-05-22T05:36:00Z","title":"Manipulating Elasto-Plastic Objects With 3D Occupancy and Learning-Based Predictive Control","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T15:08:00.758641Z"},"links":{"citing_paper":"/paper/2505.16249"},"observation_digest":"sha256:5f15101b89e82d5dcb18700dda837875b8a8411ea515e2539f228f17ea5d916f","observation_id":"87a01bf2-ecbd-4ed3-8c3c-a1eb85ed3c5a","resolution":{"observed_at":"2026-08-07T15:08:07.231273Z","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":"2026-08-07T15:08:06.979601Z","title":"6-DoF GraspNet: Variational grasp generation for object manipulation,","venue":null,"work_id":"1946e0ed-af24-49ae-ac02-16ff084f2ace","year":2019},"citing_paper":{"arxiv_id":"2505.16249","last_updated":"2025-05-23T03:16:57Z","snapshot_observed_at":"2026-08-09T05:27:59.436937Z","submitted_at":"2025-05-22T05:36:00Z","title":"Manipulating Elasto-Plastic Objects With 3D Occupancy and Learning-Based Predictive Control","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T15:08:00.922530Z"},"links":{"citing_paper":"/paper/2505.16249"},"observation_digest":"sha256:01f5e9550bbf30fe363894a3b136824e27c0e8f36176fb5512f5c29a0de8aead","observation_id":"9e9bc65b-5fa5-45ee-8824-28228f4d79e4","resolution":{"observed_at":"2026-08-07T15:08:07.084437Z","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":"2026-08-07T15:08:06.842235Z","title":"Realtime simulation of thin-shell deformable materials using CNN-based mesh embedding,","venue":null,"work_id":"e9f82569-a0cb-4e14-9bbe-e86562863fc0","year":2020},"citing_paper":{"arxiv_id":"2505.16249","last_updated":"2025-05-23T03:16:57Z","snapshot_observed_at":"2026-08-09T05:27:59.436937Z","submitted_at":"2025-05-22T05:36:00Z","title":"Manipulating Elasto-Plastic Objects With 3D Occupancy and Learning-Based Predictive Control","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T15:08:01.021629Z"},"links":{"citing_paper":"/paper/2505.16249"},"observation_digest":"sha256:3317eaec5f9dbf81d42fb406632dadcf71c7498e7970ec3c1bffb7d41091cc85","observation_id":"6c084dcd-3dcc-4999-94df-2eec1a893539","resolution":{"observed_at":"2026-08-07T15:08:06.903641Z","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":"2026-08-07T15:08:06.588780Z","title":"Sim-to-real reinforcement learning for deformable object manipulation,","venue":null,"work_id":"5040538d-4952-444d-b559-29dd58178c8e","year":2018},"citing_paper":{"arxiv_id":"2505.16249","last_updated":"2025-05-23T03:16:57Z","snapshot_observed_at":"2026-08-09T05:27:59.436937Z","submitted_at":"2025-05-22T05:36:00Z","title":"Manipulating Elasto-Plastic Objects With 3D Occupancy and Learning-Based Predictive Control","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T15:08:01.143624Z"},"links":{"citing_paper":"/paper/2505.16249"},"observation_digest":"sha256:9aa6a473cbe52c5941b88438f563f7b7989845ea9016495f416a18a716e14251","observation_id":"5b6720d5-99f8-4094-80af-ac7457f174d0","resolution":{"observed_at":"2026-08-07T15:08:06.737026Z","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":"2026-08-07T15:08:06.370250Z","title":"Learning visual-based deformable object rearrangement with local graph neural networks,","venue":null,"work_id":"70b5331b-58a2-48a0-abdf-d9e8aec4202f","year":2023},"citing_paper":{"arxiv_id":"2505.16249","last_updated":"2025-05-23T03:16:57Z","snapshot_observed_at":"2026-08-09T05:27:59.436937Z","submitted_at":"2025-05-22T05:36:00Z","title":"Manipulating Elasto-Plastic Objects With 3D Occupancy and Learning-Based Predictive Control","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T15:08:01.232627Z"},"links":{"citing_paper":"/paper/2505.16249"},"observation_digest":"sha256:1b84f867b277006a46f9527711d413a26d75e1070aada3759ff96aabf7b89135","observation_id":"8e779df0-1c59-49e3-b26e-709fae0fec01","resolution":{"observed_at":"2026-08-07T15:08:06.463310Z","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":"1810.01566","last_updated":"2019-04-18T00:37:03Z","snapshot_observed_at":"2026-08-02T02:17:27.273861Z","submitted_at":"2018-10-03T02:10:16Z","title":"Learning Particle Dynamics for Manipulating Rigid Bodies, Deformable Objects, and Fluids","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1810.01566","snapshot_observed_at":"2026-08-07T15:08:01.312030Z","title":"Learning particle dynamics for manipulating rigid bodies, deformable objects, and fluids,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2505.16249","last_updated":"2025-05-23T03:16:57Z","snapshot_observed_at":"2026-08-09T05:27:59.436937Z","submitted_at":"2025-05-22T05:36:00Z","title":"Manipulating Elasto-Plastic Objects With 3D Occupancy and Learning-Based Predictive Control","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T15:08:01.312030Z"},"links":{"cited_paper":"/paper/1810.01566","citing_paper":"/paper/2505.16249"},"observation_digest":"sha256:fa308a5c38248cc36183a13526d623c49c6c9f1dae0d982638311b9298865f9a","observation_id":"c4b0cad6-29af-4384-a6dd-ba08dc468040","resolution":{"observed_at":"2026-08-07T15:08:01.312030Z","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":"2026-08-07T15:08:06.187197Z","title":"DefGoalNet: Contextual goal learning from demonstra- tions for deformable object manipulation,","venue":null,"work_id":"3668ee20-9575-4c4c-abbb-08ba329ffb4a","year":2024},"citing_paper":{"arxiv_id":"2505.16249","last_updated":"2025-05-23T03:16:57Z","snapshot_observed_at":"2026-08-09T05:27:59.436937Z","submitted_at":"2025-05-22T05:36:00Z","title":"Manipulating Elasto-Plastic Objects With 3D Occupancy and Learning-Based Predictive Control","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T15:08:01.389154Z"},"links":{"citing_paper":"/paper/2505.16249"},"observation_digest":"sha256:3a3cffb2bd12a7bd28c3134157770ed2690b0c08044bcc692650a288d49a1c3c","observation_id":"cae5d214-7b1a-42dc-ae29-661243d1203d","resolution":{"observed_at":"2026-08-07T15:08:06.266643Z","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":"2305.04449","last_updated":"2024-02-19T09:09:46Z","snapshot_observed_at":"2026-07-06T15:24:22.647773Z","submitted_at":"2023-05-08T04:08:06Z","title":"DeformerNet: Learning Bimanual Manipulation of 3D Deformable Objects","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.04449","snapshot_observed_at":"2026-08-07T15:08:01.475323Z","title":"DeformerNet: Learning bimanual manipulation of 3D deformable objects,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.16249","last_updated":"2025-05-23T03:16:57Z","snapshot_observed_at":"2026-08-09T05:27:59.436937Z","submitted_at":"2025-05-22T05:36:00Z","title":"Manipulating Elasto-Plastic Objects With 3D Occupancy and Learning-Based Predictive Control","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T15:08:01.475323Z"},"links":{"cited_paper":"/paper/2305.04449","citing_paper":"/paper/2505.16249"},"observation_digest":"sha256:a543cefcb3994fc65a8f90b2943e34c4444a7e8f0ed63a4b674ab744f4f913cc","observation_id":"1e8fa1b1-39fc-4abf-be95-9bd5fc0a64f1","resolution":{"observed_at":"2026-08-07T15:08:01.475323Z","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":"2026-08-07T15:08:05.992503Z","title":"SculptDiff: Learning robotic clay sculpting from humans with goal conditioned diffusion policy,","venue":null,"work_id":"b5a4375b-041c-4ed6-af64-2f35332ed641","year":2024},"citing_paper":{"arxiv_id":"2505.16249","last_updated":"2025-05-23T03:16:57Z","snapshot_observed_at":"2026-08-09T05:27:59.436937Z","submitted_at":"2025-05-22T05:36:00Z","title":"Manipulating Elasto-Plastic Objects With 3D Occupancy and Learning-Based Predictive Control","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T15:08:01.575542Z"},"links":{"citing_paper":"/paper/2505.16249"},"observation_digest":"sha256:89849d1d5128791ca75dee34ea81db6cdadf4a3797d668db94a728f0897682f7","observation_id":"8021f901-be94-4e6b-a96d-c57633979e97","resolution":{"observed_at":"2026-08-07T15:08:06.100740Z","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":"2402.07648","last_updated":"2024-02-12T13:42:53Z","snapshot_observed_at":"2026-07-06T17:28:52.196375Z","submitted_at":"2024-02-12T13:42:53Z","title":"DeformNet: Latent Space Modeling and Dynamics Prediction for Deformable Object Manipulation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.07648","snapshot_observed_at":"2026-08-07T15:08:01.642708Z","title":"DeformNet: Latent space modeling and dynamics predic- tion for deformable object manipulation,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.16249","last_updated":"2025-05-23T03:16:57Z","snapshot_observed_at":"2026-08-09T05:27:59.436937Z","submitted_at":"2025-05-22T05:36:00Z","title":"Manipulating Elasto-Plastic Objects With 3D Occupancy and Learning-Based Predictive Control","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T15:08:01.642708Z"},"links":{"cited_paper":"/paper/2402.07648","citing_paper":"/paper/2505.16249"},"observation_digest":"sha256:8785640d78aea3bdda152ffd4260481258eae6d8e19dafdaab28844dc272acad","observation_id":"b786e768-b70f-470a-b7b7-e8aec14e3840","resolution":{"observed_at":"2026-08-07T15:08:01.642708Z","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":"2026-08-07T15:08:05.870018Z","title":"The surprising effectiveness of linear models for visual foresight in object pile manipulation,","venue":null,"work_id":"0e44bdc4-6c3e-41b8-be65-b6a0576ec696","year":2021},"citing_paper":{"arxiv_id":"2505.16249","last_updated":"2025-05-23T03:16:57Z","snapshot_observed_at":"2026-08-09T05:27:59.436937Z","submitted_at":"2025-05-22T05:36:00Z","title":"Manipulating Elasto-Plastic Objects With 3D Occupancy and Learning-Based Predictive Control","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T15:08:01.722978Z"},"links":{"citing_paper":"/paper/2505.16249"},"observation_digest":"sha256:520b1a679ec0eb8570daf98d293a2ab8135276b54616b29800bf3d86b612aa90","observation_id":"30b6ff54-d95c-4c45-bad2-4f398ed980b2","resolution":{"observed_at":"2026-08-07T15:08:05.957476Z","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":"2026-08-07T15:08:05.674863Z","title":"Neural field dynamics model for granular object piles manipulation,","venue":null,"work_id":"4f9f5261-7065-4402-8fe8-dec35ed8a36c","year":2023},"citing_paper":{"arxiv_id":"2505.16249","last_updated":"2025-05-23T03:16:57Z","snapshot_observed_at":"2026-08-09T05:27:59.436937Z","submitted_at":"2025-05-22T05:36:00Z","title":"Manipulating Elasto-Plastic Objects With 3D Occupancy and Learning-Based Predictive Control","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T15:08:01.820960Z"},"links":{"citing_paper":"/paper/2505.16249"},"observation_digest":"sha256:3f89fd367ac77e454e4fa0ece431063d9bfe21d283f0eb90abd1132603454140","observation_id":"f1b0274d-3a51-450b-93a0-1b33c85f5e63","resolution":{"observed_at":"2026-08-07T15:08:05.763609Z","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":"2306.16700","last_updated":"2023-06-30T02:24:08Z","snapshot_observed_at":"2026-08-05T00:39:44.380478Z","submitted_at":"2023-06-29T05:51:44Z","title":"Dynamic-Resolution Model Learning for Object Pile Manipulation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.16700","snapshot_observed_at":"2026-08-07T15:08:01.906280Z","title":"Dynamic-resolution model learning for object pile manipulation,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.16249","last_updated":"2025-05-23T03:16:57Z","snapshot_observed_at":"2026-08-09T05:27:59.436937Z","submitted_at":"2025-05-22T05:36:00Z","title":"Manipulating Elasto-Plastic Objects With 3D Occupancy and Learning-Based Predictive Control","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T15:08:01.906280Z"},"links":{"cited_paper":"/paper/2306.16700","citing_paper":"/paper/2505.16249"},"observation_digest":"sha256:74a075b3611f3101590257fb72128e024548d90465c24843ca07f9b45f77ec2c","observation_id":"a8ad3dfd-6a91-4473-ba13-35704ecc78ae","resolution":{"observed_at":"2026-08-07T15:08:01.906280Z","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":"2026-08-07T15:08:05.507984Z","title":"Transporter networks: Rearranging the visual world for robotic manipulation,","venue":null,"work_id":"ad39a8c6-ba8f-4c99-ba6b-563b2f2e9294","year":2021},"citing_paper":{"arxiv_id":"2505.16249","last_updated":"2025-05-23T03:16:57Z","snapshot_observed_at":"2026-08-09T05:27:59.436937Z","submitted_at":"2025-05-22T05:36:00Z","title":"Manipulating Elasto-Plastic Objects With 3D Occupancy and Learning-Based Predictive Control","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T15:08:02.089934Z"},"links":{"citing_paper":"/paper/2505.16249"},"observation_digest":"sha256:f50d4d4e26c45e4c4c2750076d028f26096f558d612c42f3e49fa8d5d85a4524","observation_id":"890d28d4-e2cd-4edb-8e4a-849815121862","resolution":{"observed_at":"2026-08-07T15:08:05.574239Z","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":"1910.08264","last_updated":"2020-04-27T17:09:47Z","snapshot_observed_at":"2026-07-06T08:30:30.156068Z","submitted_at":"2019-10-18T05:11:16Z","title":"Learning Compositional Koopman Operators for Model-Based Control","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.08264","snapshot_observed_at":"2026-08-07T15:08:02.249093Z","title":"Learning compositional Koopman operators for model- based control,","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2505.16249","last_updated":"2025-05-23T03:16:57Z","snapshot_observed_at":"2026-08-09T05:27:59.436937Z","submitted_at":"2025-05-22T05:36:00Z","title":"Manipulating Elasto-Plastic Objects With 3D Occupancy and Learning-Based Predictive Control","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T15:08:02.249093Z"},"links":{"cited_paper":"/paper/1910.08264","citing_paper":"/paper/2505.16249"},"observation_digest":"sha256:5ab97a680776d6ce046d14e52ef488a5c19914d63598be0311163e384231258a","observation_id":"5d5593d0-06cb-4e0b-80b9-b57cfbf6d792","resolution":{"observed_at":"2026-08-07T15:08:02.249093Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.14447","last_updated":"2023-10-17T18:05:32Z","snapshot_observed_at":"2026-07-06T15:46:36.421593Z","submitted_at":"2023-06-26T06:30:29Z","title":"RoboCook: Long-Horizon Elasto-Plastic Object Manipulation with Diverse Tools","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.14447","snapshot_observed_at":"2026-08-07T15:08:02.336082Z","title":"RoboCook: Long-horizon elasto-plastic object manipula- tion with diverse tools,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.16249","last_updated":"2025-05-23T03:16:57Z","snapshot_observed_at":"2026-08-09T05:27:59.436937Z","submitted_at":"2025-05-22T05:36:00Z","title":"Manipulating Elasto-Plastic Objects With 3D Occupancy and Learning-Based Predictive Control","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T15:08:02.336082Z"},"links":{"cited_paper":"/paper/2306.14447","citing_paper":"/paper/2505.16249"},"observation_digest":"sha256:8ec87a8a6ea0aa66c4d9053ecc5f3f3940499d630d63697cb4ab93e89062bc81","observation_id":"6ad243d1-2a0e-4656-bfeb-ed35e8c1dd4e","resolution":{"observed_at":"2026-08-07T15:08:02.336082Z","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":"2026-08-07T15:08:05.302500Z","title":"Sculptbot: Pre-trained models for 3D deformable object manipulation,","venue":null,"work_id":"417ae993-0826-4322-877a-5b0da1bcc4de","year":2024},"citing_paper":{"arxiv_id":"2505.16249","last_updated":"2025-05-23T03:16:57Z","snapshot_observed_at":"2026-08-09T05:27:59.436937Z","submitted_at":"2025-05-22T05:36:00Z","title":"Manipulating Elasto-Plastic Objects With 3D Occupancy and Learning-Based Predictive Control","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T15:08:02.496086Z"},"links":{"citing_paper":"/paper/2505.16249"},"observation_digest":"sha256:2fe2ab087a01e7d6b7f6e14d70783fff5dc1a3931b68bb00280a36be98afe947","observation_id":"5c47d065-ace5-4118-9b06-606daf61fb5e","resolution":{"observed_at":"2026-08-07T15:08:05.392512Z","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":"2026-08-07T15:08:05.179086Z","title":"Fast marching farthest point sampling,","venue":null,"work_id":"f80687eb-538c-4e39-a795-f8f88f6ddaf8","year":2003},"citing_paper":{"arxiv_id":"2505.16249","last_updated":"2025-05-23T03:16:57Z","snapshot_observed_at":"2026-08-09T05:27:59.436937Z","submitted_at":"2025-05-22T05:36:00Z","title":"Manipulating Elasto-Plastic Objects With 3D Occupancy and Learning-Based Predictive Control","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T15:08:02.697373Z"},"links":{"citing_paper":"/paper/2505.16249"},"observation_digest":"sha256:e1634858cf5b990484185d76b93b8ab98e5b0a29adb1a897dcf0d5228eeb7d12","observation_id":"9869c7f8-5f29-4253-ac68-e7d8d802a228","resolution":{"observed_at":"2026-08-07T15:08:05.239163Z","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":"2026-08-07T15:08:05.069666Z","title":"Deep residual learning for image recognition,","venue":null,"work_id":"d0f8f9e3-7bcc-4641-984c-0d9d701fdd9b","year":2016},"citing_paper":{"arxiv_id":"2505.16249","last_updated":"2025-05-23T03:16:57Z","snapshot_observed_at":"2026-08-09T05:27:59.436937Z","submitted_at":"2025-05-22T05:36:00Z","title":"Manipulating Elasto-Plastic Objects With 3D Occupancy and Learning-Based Predictive Control","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T15:08:02.800832Z"},"links":{"citing_paper":"/paper/2505.16249"},"observation_digest":"sha256:77e33888a396f33192bcb33ffe9a64c2c2329cdb0558b441ec17fbc42ed80051","observation_id":"495af4e3-0363-4650-bcf6-04b6cc4159e4","resolution":{"observed_at":"2026-08-07T15:08:05.113448Z","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":"2026-08-07T15:08:04.918886Z","title":"SurroundOcc: Multi-camera 3D occupancy prediction for autonomous driving,","venue":null,"work_id":"5ff5417a-c917-488f-93ab-8a9bd119ad51","year":2023},"citing_paper":{"arxiv_id":"2505.16249","last_updated":"2025-05-23T03:16:57Z","snapshot_observed_at":"2026-08-09T05:27:59.436937Z","submitted_at":"2025-05-22T05:36:00Z","title":"Manipulating Elasto-Plastic Objects With 3D Occupancy and Learning-Based Predictive Control","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T15:08:02.953389Z"},"links":{"citing_paper":"/paper/2505.16249"},"observation_digest":"sha256:478de178142ee98e6049802410fe12b56fc915cd594fe5a7a2240914ab96f995","observation_id":"9b4d84b5-e6ab-4b4e-bab7-74dfff1744d4","resolution":{"observed_at":"2026-08-07T15:08:04.993714Z","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":"2026-08-07T15:08:04.810865Z","title":"PV-RCNN: Point-voxel feature set abstraction for 3D object detection,","venue":null,"work_id":"f664c25d-d596-4729-a445-8d0f7f5cbad9","year":2020},"citing_paper":{"arxiv_id":"2505.16249","last_updated":"2025-05-23T03:16:57Z","snapshot_observed_at":"2026-08-09T05:27:59.436937Z","submitted_at":"2025-05-22T05:36:00Z","title":"Manipulating Elasto-Plastic Objects With 3D Occupancy and Learning-Based Predictive Control","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T15:08:03.106064Z"},"links":{"citing_paper":"/paper/2505.16249"},"observation_digest":"sha256:fa6d3fe33b5cd51c83cf9f3345708f2e486f3155e09b755d6c64409dcc9e9599","observation_id":"e0b4bb80-7a84-4b31-9c8e-a16ce150c67a","resolution":{"observed_at":"2026-08-07T15:08:04.850082Z","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":"2026-08-07T15:08:04.673277Z","title":"A metric for distributions with applications to image databases,","venue":null,"work_id":"c3b737fd-a3ff-4735-8f62-712bf5ccab0e","year":1998},"citing_paper":{"arxiv_id":"2505.16249","last_updated":"2025-05-23T03:16:57Z","snapshot_observed_at":"2026-08-09T05:27:59.436937Z","submitted_at":"2025-05-22T05:36:00Z","title":"Manipulating Elasto-Plastic Objects With 3D Occupancy and Learning-Based Predictive Control","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T15:08:03.246141Z"},"links":{"citing_paper":"/paper/2505.16249"},"observation_digest":"sha256:a20ab3eb29dee95f56ba85bfa1aee14a5e175c1404c1a51f35be688979bf27bf","observation_id":"ea0d8263-50d1-4609-b38a-59d242c1a9b8","resolution":{"observed_at":"2026-08-07T15:08:04.746050Z","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":"2111.12702","last_updated":"2021-11-24T18:56:27Z","snapshot_observed_at":"2026-07-06T12:11:56.886534Z","submitted_at":"2021-11-24T18:56:27Z","title":"Density-aware Chamfer Distance as a Comprehensive Metric for Point Cloud Completion","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2111.12702","snapshot_observed_at":"2026-08-07T15:08:03.356236Z","title":"Density-aware Chamfer Distance as a comprehensive metric for point cloud completion,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.16249","last_updated":"2025-05-23T03:16:57Z","snapshot_observed_at":"2026-08-09T05:27:59.436937Z","submitted_at":"2025-05-22T05:36:00Z","title":"Manipulating Elasto-Plastic Objects With 3D Occupancy and Learning-Based Predictive Control","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T15:08:03.356236Z"},"links":{"cited_paper":"/paper/2111.12702","citing_paper":"/paper/2505.16249"},"observation_digest":"sha256:6dfe383ebd607d985b9d71147454a7677f567b079ddaffdc8e976eeb27317ff9","observation_id":"877d9db4-944e-4662-9f24-3c4bc68e8c58","resolution":{"observed_at":"2026-08-07T15:08:03.356236Z","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":"2026-08-07T15:08:04.577441Z","title":"Practical Methods of Optimization,","venue":null,"work_id":"e9cdb63a-31ca-4ae3-83e9-1ed5817457df","year":2013},"citing_paper":{"arxiv_id":"2505.16249","last_updated":"2025-05-23T03:16:57Z","snapshot_observed_at":"2026-08-09T05:27:59.436937Z","submitted_at":"2025-05-22T05:36:00Z","title":"Manipulating Elasto-Plastic Objects With 3D Occupancy and Learning-Based Predictive Control","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T15:08:03.506381Z"},"links":{"citing_paper":"/paper/2505.16249"},"observation_digest":"sha256:1e119dd5bd84d15d10c1464186498cc1e99091c6dee9f2e6248e9f824f4983bf","observation_id":"be8feeee-fa63-40f1-bca6-66f428cbfe30","resolution":{"observed_at":"2026-08-07T15:08:04.628239Z","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":"2409.17124","last_updated":"2024-09-25T17:38:20Z","snapshot_observed_at":"2026-07-06T19:22:14.655041Z","submitted_at":"2024-09-25T17:38:20Z","title":"PokeFlex: Towards a Real-World Dataset of Deformable Objects for Robotic Manipulation","version":1},"cited_work":{"arxiv_id":"2409.17124","doi":null,"metadata_source":"pith","pith_arxiv_id":"2409.17124","snapshot_observed_at":"2026-08-07T15:08:04.186017Z","title":"PokeFlex: Towards a Real-World Dataset of Deformable Objects for Robotic Manipulation","venue":"cs.RO","work_id":"a0f045a1-7871-46e7-886a-d0f693ff4cbd","year":2024},"citing_paper":{"arxiv_id":"2505.16249","last_updated":"2025-05-23T03:16:57Z","snapshot_observed_at":"2026-08-09T05:27:59.436937Z","submitted_at":"2025-05-22T05:36:00Z","title":"Manipulating Elasto-Plastic Objects With 3D Occupancy and Learning-Based Predictive Control","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T15:08:03.618530Z"},"links":{"cited_paper":"/paper/2409.17124","citing_paper":"/paper/2505.16249"},"observation_digest":"sha256:2eef0a859fe06246c66cb68875bf2c45d6e7a10446eff2d145f72ab1b0c15db1","observation_id":"6b02de6b-6582-4f53-8e15-14943373fbce","resolution":{"observed_at":"2026-08-07T15:08:04.220641Z","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":{"arxiv_id":"2410.21758","last_updated":"2024-10-29T05:46:16Z","snapshot_observed_at":"2026-07-06T19:41:19.700669Z","submitted_at":"2024-10-29T05:46:16Z","title":"DOFS: A Real-world 3D Deformable Object Dataset with Full Spatial Information for Dynamics Model Learning","version":1},"cited_work":{"arxiv_id":"2410.21758","doi":null,"metadata_source":"pith","pith_arxiv_id":"2410.21758","snapshot_observed_at":"2026-08-07T15:08:04.092174Z","title":"DOFS: A Real-world 3D Deformable Object Dataset with Full Spatial Information for Dynamics Model Learning","venue":"cs.CV","work_id":"fc5d3d43-de3e-467e-94c2-16d2c5456fc5","year":2024},"citing_paper":{"arxiv_id":"2505.16249","last_updated":"2025-05-23T03:16:57Z","snapshot_observed_at":"2026-08-09T05:27:59.436937Z","submitted_at":"2025-05-22T05:36:00Z","title":"Manipulating Elasto-Plastic Objects With 3D Occupancy and Learning-Based Predictive Control","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T15:08:03.761184Z"},"links":{"cited_paper":"/paper/2410.21758","citing_paper":"/paper/2505.16249"},"observation_digest":"sha256:e3d07a9c8588fcfe96448b2c65b1f60f4924792d2595279a4209442ead8574b0","observation_id":"2579838d-5e24-4018-b9e0-3e17b4cf65e8","resolution":{"observed_at":"2026-08-07T15:08:04.131832Z","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":"2026-08-07T15:08:04.465623Z","title":"A density-based algorithm for discovering clusters in large spatial databases with noise,","venue":null,"work_id":"4514f0f9-d24d-4ea9-bce0-9a3298e0ebd0","year":1996},"citing_paper":{"arxiv_id":"2505.16249","last_updated":"2025-05-23T03:16:57Z","snapshot_observed_at":"2026-08-09T05:27:59.436937Z","submitted_at":"2025-05-22T05:36:00Z","title":"Manipulating Elasto-Plastic Objects With 3D Occupancy and Learning-Based Predictive Control","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T15:08:03.821504Z"},"links":{"citing_paper":"/paper/2505.16249"},"observation_digest":"sha256:7a1c24ba55f5d64bb3d48301e671314ad479bb083b9f00c874f8527aa2280378","observation_id":"6e05fa4c-b4d1-45fe-8edf-1a6856c80481","resolution":{"observed_at":"2026-08-07T15:08:04.512117Z","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":"2026-08-07T15:08:04.353654Z","title":"Poisson surface reconstruction,","venue":null,"work_id":"f95199bc-5f5e-4c96-9d12-95f0e0fb51c9","year":2006},"citing_paper":{"arxiv_id":"2505.16249","last_updated":"2025-05-23T03:16:57Z","snapshot_observed_at":"2026-08-09T05:27:59.436937Z","submitted_at":"2025-05-22T05:36:00Z","title":"Manipulating Elasto-Plastic Objects With 3D Occupancy and Learning-Based Predictive Control","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T15:08:03.876917Z"},"links":{"citing_paper":"/paper/2505.16249"},"observation_digest":"sha256:c790c63f8280ed7e16d13c808e2dbda10ef8b12202c08bf24ea70e0f67f3d9a3","observation_id":"d55d50b4-dc70-4ced-948b-2a28244b04b6","resolution":{"observed_at":"2026-08-07T15:08:04.411843Z","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":"2104.03311","last_updated":"2021-04-07T17:59:23Z","snapshot_observed_at":"2026-08-05T09:53:30.515362Z","submitted_at":"2021-04-07T17:59:23Z","title":"PlasticineLab: A Soft-Body Manipulation Benchmark with Differentiable Physics","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2104.03311","snapshot_observed_at":"2026-08-07T15:08:03.922293Z","title":"PlasticineLab: A soft-body manipulation benchmark with differentiable physics,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.16249","last_updated":"2025-05-23T03:16:57Z","snapshot_observed_at":"2026-08-09T05:27:59.436937Z","submitted_at":"2025-05-22T05:36:00Z","title":"Manipulating Elasto-Plastic Objects With 3D Occupancy and Learning-Based Predictive Control","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T15:08:03.922293Z"},"links":{"cited_paper":"/paper/2104.03311","citing_paper":"/paper/2505.16249"},"observation_digest":"sha256:c89508b9741991bd13c53abf38a0a706076091d8c900b59df874d1135b3a4614","observation_id":"ac38e47c-a8f6-48b7-b176-71e6d51b9756","resolution":{"observed_at":"2026-08-07T15:08:03.922293Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.10329","last_updated":"2024-03-06T00:11:34Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-02-15T21:11:50Z","title":"Universal Manipulation Interface: In-The-Wild Robot Teaching Without In-The-Wild Robots","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.10329","snapshot_observed_at":"2026-08-07T15:08:03.997114Z","title":"Universal Manipulation Interface: In-the-wild robot teaching without in-the-wild robots,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.16249","last_updated":"2025-05-23T03:16:57Z","snapshot_observed_at":"2026-08-09T05:27:59.436937Z","submitted_at":"2025-05-22T05:36:00Z","title":"Manipulating Elasto-Plastic Objects With 3D Occupancy and Learning-Based Predictive Control","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T15:08:03.997114Z"},"links":{"cited_paper":"/paper/2402.10329","citing_paper":"/paper/2505.16249"},"observation_digest":"sha256:7835a636ff791da06147c5e1a3ad9bf4ef92f14679bad774554bf9bc477f6548","observation_id":"4ac7fb6c-2a90-4379-a0ed-85cbb994626f","resolution":{"observed_at":"2026-08-07T15:08:03.997114Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2505.16249","last_updated":"2025-05-23T03:16:57Z","latest_version":2,"primary_category":"cs.RO","snapshot_observed_at":"2026-08-09T05:27:59.436937Z","submitted_at":"2025-05-22T05:36:00Z","title":"Manipulating Elasto-Plastic Objects With 3D Occupancy and Learning-Based Predictive Control"},"reference_resolution":{"displayed":35,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":9,"verified_exact":2,"verified_fuzzy":24},"total_outbound_references":35},"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 9 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2505.16249."}