{"as_of":"2026-08-09T19:11:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:56526b926bddfcd5a5cd79ebb0ab39c8cb5d5daa5b67a2712def48e4cf74b570","coverage":[{"denominator":52,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":52,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T12:25:48.862295Z","state":"measured"},{"denominator":52,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":52,"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/2507.21796/citation-record","integrity":"/paper/2507.21796/integrity","json":"/paper/2507.21796/citation-record.json","paper":"/paper/2507.21796"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T12:25:49.588723Z","title":"M 2 diffuser: Diffusion-based trajectory optimization for mobile manipulation in 3d scenes,","venue":null,"work_id":"2fee9246-c444-4a07-a695-7eb77ee66dbd","year":2025},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.709982Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:4987c8b7cc604031939864850d37c92f1a9b43caf1ee9ac5693bbdf07653896e","observation_id":"67be6799-148e-4d52-aa3e-2bcffa98d5e2","resolution":{"observed_at":"2026-08-06T12:25:49.591924Z","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":"2409.04882","last_updated":"2024-09-07T18:27:46Z","snapshot_observed_at":"2026-08-09T09:29:16.733973Z","submitted_at":"2024-09-07T18:27:46Z","title":"Learning to Open and Traverse Doors with a Legged Manipulator","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.04882","snapshot_observed_at":"2026-08-06T12:25:48.713450Z","title":"Learning to open and traverse doors with a legged manipulator,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.713450Z"},"links":{"cited_paper":"/paper/2409.04882","citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:b8e3720f90b600581b36336b3597d49a1392a884039bf9485489fb8f572f1dd1","observation_id":"cf768149-b8be-4bbe-a7b5-5ef8640e8fcc","resolution":{"observed_at":"2026-08-06T12:25:48.713450Z","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":"2026-08-06T12:25:49.580263Z","title":"Cherry-picking with reinforcement learning","venue":null,"work_id":"246895f4-ea5c-432a-b0ce-df0896e4febd","year":null},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.717491Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:b0666022d7a880053d45c360e7b0b694f1fe6533401044c5b263ad7e9144ffb5","observation_id":"59ce123a-02bc-4677-8794-211ba1315426","resolution":{"observed_at":"2026-08-06T12:25:49.583403Z","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":"2026-08-06T12:25:49.571463Z","title":"Real-time dynamic ges- ture recognition for human-robot collaboration in rescue operations,","venue":null,"work_id":"e0411546-669e-4732-ac5d-f22319004091","year":2024},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.720786Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:80c8198f0f327d5e59396f6bd874f3c31efdcc43597d32306d8173fd1613f5b2","observation_id":"4209fc86-2e75-4e62-92f9-e1f8c4a1f261","resolution":{"observed_at":"2026-08-06T12:25:49.574836Z","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":"2026-08-06T12:25:49.563080Z","title":"Motion planning for mobile manipulators—a systematic review,","venue":null,"work_id":"f2bb91d1-daa1-4234-baef-47317c6a0129","year":2022},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.723786Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:e9621cc6b8882edb0aa83abeac45c40114f85245941a787354659e2b3eb554e3","observation_id":"a03eea0d-d45a-40c1-b853-2e490874875f","resolution":{"observed_at":"2026-08-06T12:25:49.566164Z","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":"2026-08-06T12:25:49.554741Z","title":"Callister and D","venue":null,"work_id":"60f1fddf-56cb-4bdd-b78f-6af3c421cdfe","year":2008},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.726850Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:6c53c9e5189b6505274cb7114b6c6b05d605ec2b0e3d74b6e6116d193126382b","observation_id":"80cf00bb-202d-4313-ae25-267fb6daac3a","resolution":{"observed_at":"2026-08-06T12:25:49.557798Z","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":"document/9578091","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T12:25:49.222209Z","title":"ManipulaTHOR: A framework for visual object manipulation,","venue":null,"work_id":"0f4708b4-6d9b-4dbf-85ae-9bc6889c7103","year":2021},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.729808Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:95dab6c95a37cd4c150905ada18c714cc11b2005028a458711c10ec5d05210f9","observation_id":"5c8c7025-92d8-40ed-a5d1-fb1b9ef4f47a","resolution":{"observed_at":"2026-08-06T12:25:49.226746Z","resolver_source":"raw_fallback","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":"2009.12293","last_updated":"2025-01-18T02:57:38Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2020-09-25T15:32:31Z","title":"robosuite: A Modular Simulation Framework and Benchmark for Robot Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.12293","snapshot_observed_at":"2026-08-06T12:25:48.732863Z","title":"robosuite: A modular simulation framework and benchmark for robot learning","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.732863Z"},"links":{"cited_paper":"/paper/2009.12293","citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:2ca7804ac92421334084e632779ddcd318d396c59cdb86ad4eb2855c45d2ede5","observation_id":"f3b75114-d6d0-4761-9ffd-3c95fd2de764","resolution":{"observed_at":"2026-08-06T12:25:48.732863Z","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":"2026-08-06T12:25:49.546197Z","title":"SoftGym: Benchmarking deep reinforcement learning for deformable object manipulation","venue":null,"work_id":"7a251a00-536e-4f6d-ba69-dac4f5521c7f","year":null},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.736208Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:f21a0a47fc310782803d2798f84f2ed0253e5ead4f10d8757179ba5180d52cf6","observation_id":"7b054904-3442-4966-8ef7-89626bdf7859","resolution":{"observed_at":"2026-08-06T12:25:49.549359Z","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":"2026-08-06T12:25:49.537289Z","title":"Reform: A robot learning sandbox for deformable linear object manipulation,","venue":null,"work_id":"9f0550a2-d272-4b83-a8c3-f47bf6cea3c3","year":2021},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.739059Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:55adbc178c195b717cc12b9ca38e1e8bb5fd7826248722f56e44f967db961eec","observation_id":"1ecd8621-5d37-4d6a-98de-932ce7b518b5","resolution":{"observed_at":"2026-08-06T12:25:49.540646Z","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":"2026-08-06T12:25:49.528887Z","title":"Behavior-1k: A benchmark for embodied ai with 1,000 everyday activities and realistic simulation,","venue":null,"work_id":"af17484c-85b7-4d72-9b2f-8fd612025203","year":2023},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.741922Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:941fdfe6438d750180365b718e21b69a6c60c0bd98452975d32e9041757b84f4","observation_id":"24e98e91-65e6-41d5-a472-5f85da050651","resolution":{"observed_at":"2026-08-06T12:25:49.532151Z","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":"1712.05474","last_updated":"2022-08-26T17:12:17Z","snapshot_observed_at":"2026-07-06T06:14:28.435222Z","submitted_at":"2017-12-14T23:17:24Z","title":"AI2-THOR: An Interactive 3D Environment for Visual AI","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1712.05474","snapshot_observed_at":"2026-08-06T12:25:48.744855Z","title":"Ai2-thor: An interactive 3d environment for visual ai,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.744855Z"},"links":{"cited_paper":"/paper/1712.05474","citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:2e41d137bf0dca58133da9d48fd61b9ae6bdea6bf535bd39d90411c69a3536ca","observation_id":"2ba95108-0d47-42a1-81ff-89d81045138a","resolution":{"observed_at":"2026-08-06T12:25:48.744855Z","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":"2026-08-06T12:25:49.520208Z","title":"The threedworld transport challenge: A visually guided task-and-motion planning benchmark towards physically real- istic embodied ai,","venue":null,"work_id":"3035f629-1e0f-4270-8b5e-b96d6f80a7b0","year":2022},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.748036Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:14df0ca889d37518941be21cea76591c119393d705497395b776d4e2e5320a56","observation_id":"68a5de0d-cc71-416d-a1aa-a132ba574efa","resolution":{"observed_at":"2026-08-06T12:25:49.523464Z","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":"2026-08-06T12:25:49.511730Z","title":"Habitat 3.0: A co-habitat for humans, avatars and robots,","venue":null,"work_id":"c9ada9da-78b5-480d-96f5-ac21ab72b903","year":2023},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.750978Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:5e230412c3347c09ec6a55d2eea01f3c74d50bb1dce04fdb851cb997fda362f9","observation_id":"47fdcca5-af4a-40b4-9111-f9056b995493","resolution":{"observed_at":"2026-08-06T12:25:49.514810Z","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":"2026-08-06T12:25:49.503032Z","title":"Maniskill3: Gpu parallelized robotics simulation and rendering for generalizable embodied ai,","venue":null,"work_id":"6043afca-2987-4e4c-a048-9fcdabaa5667","year":2025},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.753781Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:dc97460db2372a7816f3d682ffb848ac032f46dcb614065f2565f3779312b890","observation_id":"3e0bacaa-de55-42f5-9e03-0095fce5c1b6","resolution":{"observed_at":"2026-08-06T12:25:49.506394Z","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":"2301.04195","last_updated":"2024-02-16T13:45:11Z","snapshot_observed_at":"2026-07-06T14:40:08.765591Z","submitted_at":"2023-01-10T20:19:17Z","title":"Orbit: A Unified Simulation Framework for Interactive Robot Learning Environments","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2301.04195","snapshot_observed_at":"2026-08-06T12:25:48.756635Z","title":"ORBIT: A unified simulation framework for interactive robot learning environments","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.756635Z"},"links":{"cited_paper":"/paper/2301.04195","citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:fef3f3e0edcd865b1c24090ac3cf02d5ead8c787ed53747cbbfab210a9d04a75","observation_id":"663b1465-c31a-4369-8ffe-52a5caa26822","resolution":{"observed_at":"2026-08-06T12:25:48.756635Z","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":"2026-08-06T12:25:49.494506Z","title":"Learning to Rearrange Deformable Cables, Fabrics, and Bags with Goal-Conditioned Transporter Networks,","venue":null,"work_id":"c2424931-2b56-4d29-9326-fdf954dc9dce","year":2021},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.759934Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:a2fcdfdc1ce1d36e1e6a159a822db7998f93d13ece604419dc24f4039701d061","observation_id":"1d8ff1e4-0889-4e9d-a48e-5e56f4e8416b","resolution":{"observed_at":"2026-08-06T12:25:49.497860Z","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":"2026-08-06T12:25:49.486446Z","title":"Dynamic environments with deformable objects,","venue":null,"work_id":"6899be51-bea5-440e-855d-69c494d484c3","year":2021},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.762692Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:f8086bdc8dad6df10e345b0eb9b54053c35ef8c3fc69e7efd03b47a76a15a90b","observation_id":"eaac96da-2c3c-4b8b-93f9-23477cd92f80","resolution":{"observed_at":"2026-08-06T12:25:49.489523Z","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":"2026-08-06T12:25:49.477308Z","title":"Daxbench: Benchmarking deformable object ma- nipulation with differentiable physics,","venue":null,"work_id":"ecb37490-2c47-45c7-b5ff-43f588d531d9","year":null},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.765406Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:c465395b6dc1b736f4a330d2cab55154d6742fbaf529c17142e5d711d7788521","observation_id":"a682cffb-3c78-4e77-8b2e-3231c9ab244d","resolution":{"observed_at":"2026-08-06T12:25:49.480700Z","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":"2026-08-06T12:25:49.469026Z","title":"Plasticinelab: A soft-body manipulation benchmark with differentiable physics,","venue":null,"work_id":"f967b2bc-5b93-4e8b-bc61-1a65a14b9499","year":2021},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.768529Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:3515c3bb41d6b13be58f5a5195c37aacc36ddb121c56319ed4928b8fd956216b","observation_id":"d74d17c8-24a9-4f4d-9f64-4a711a440d6b","resolution":{"observed_at":"2026-08-06T12:25:49.472038Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T12:25:48.771452Z","title":"Dexgarmentlab: Dexterous garment manip- ulation environment with generalizable policy,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.771452Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:ebdd4e08838d8227af2a93bd532b25c3a2029424128dcc5f043ce932ba23b331","observation_id":"07953fe8-bf54-42c8-a9fa-ea6f76da08f2","resolution":{"observed_at":"2026-08-06T12:25:48.771452Z","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":"2026-08-06T12:25:49.460822Z","title":"Nvidia isaac sim,","venue":null,"work_id":"480766d7-56fc-4bc2-b31f-cb6d78ec431e","year":2022},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.775105Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:b23ce93afbc4982c4ea000ad5650ecb5956968a76053472cf315cf1f222e7b9b","observation_id":"1b4ee416-5b34-4c46-8d3f-b3b35b1880da","resolution":{"observed_at":"2026-08-06T12:25:49.463782Z","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":"2026-08-06T12:25:49.452085Z","title":"Collaborative object manipulation through indirect control of a deformable sheet by a mobile robotic team,","venue":null,"work_id":"90fefbfe-f248-4348-8629-a9cc62b500ee","year":2019},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.777985Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:20e17faf0c5f52ea1f0a37696f6430fd8b52d8d746d55f318023edef7cdf3293","observation_id":"aab1a2a5-a278-4219-a20e-e5ec5dd405dc","resolution":{"observed_at":"2026-08-06T12:25:49.455361Z","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":"2503.04007","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T12:25:49.066898Z","title":"Planning and control for deformable linear object manipulation,","venue":null,"work_id":"5b30c3cd-26ee-4929-89c0-1a73ddda8316","year":2025},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.780877Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:c886eaacade06502f3c7268d5a9be7eb8841cf7bfaf088638420634b27dc865f","observation_id":"9d52c4c0-40cf-4399-a6fe-e924662f83bb","resolution":{"observed_at":"2026-08-06T12:25:49.072503Z","resolver_source":"raw_fallback","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":"2026-08-06T12:25:49.443406Z","title":"Combining learning-based locomotion policy with model-based manipulation for legged mobile manipulators,","venue":null,"work_id":"d5a10333-8640-4d48-8ade-7c434a6c8bef","year":null},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.783627Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:1dfccaf45d1bb1d110072a2ac39115c5d744350178c374457a8d585f1eb54d55","observation_id":"ad301040-e836-48fa-9f7b-87cba6fea007","resolution":{"observed_at":"2026-08-06T12:25:49.446690Z","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":"2026-08-06T12:25:49.434612Z","title":"Learning kinematic feasibility for mobile manipulation through deep reinforcement learn- ing,","venue":null,"work_id":"ae7a008a-fa3a-4150-870b-2fadd0aee16f","year":null},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.786725Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:0b2a12242782c742d5839b899d9d00c792e078f4c2794ab89f978633567b0f08","observation_id":"89e8f44c-e580-4bcb-a89d-b86b48167b2e","resolution":{"observed_at":"2026-08-06T12:25:49.437985Z","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":"2026-08-06T12:25:49.426185Z","title":"Learning shape control of elastoplas- tic deformable linear objects,","venue":null,"work_id":"c5e83852-f3e6-4a5a-bbe3-1c431cf9c6f9","year":2021},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.789851Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:259ab086b8d32f9c877786c53da156998d7b5abb9c6003076c12972ffff089a4","observation_id":"19c1dab4-4927-4ea9-a4bd-12fe02c0784c","resolution":{"observed_at":"2026-08-06T12:25:49.429312Z","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":"2026-08-06T12:25:49.417305Z","title":"Cloth manipulation using random-forest-based imitation learning,","venue":null,"work_id":"240c8faf-5512-41ef-be0f-705a91d4849a","year":2019},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.792902Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:f275e599b81b102544eff323444c70aa2fa5accaf0b1084bdd05b494f047ec13","observation_id":"3ca79b12-00c6-427b-8daa-6f2ced268d44","resolution":{"observed_at":"2026-08-06T12:25:49.420548Z","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":"2026-08-06T12:25:49.408675Z","title":"Learning deformable object manipulation from expert demonstra- tions,","venue":null,"work_id":"4c5166ff-66e2-4546-b184-3d8aa40f28e9","year":2022},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.795742Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:943ef8e66076fefbf87da7ad394b092bb64a6ab24690d4428c9b3cc39cd4a648","observation_id":"e6c40684-ca14-4c6c-87b5-441f6f131388","resolution":{"observed_at":"2026-08-06T12:25:49.411804Z","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":"2026-08-06T12:25:49.400106Z","title":"Demobot: Deformable mobile manipulation with vision-based sub-goal retrieval,","venue":null,"work_id":"8607b5e6-ded0-4a7d-973c-f9fdaa6cadb1","year":null},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.798467Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:77d625c16a219e6687e67de9e817af3b745dc06b98b9841cbba39a4b6228cfb6","observation_id":"b55c65ce-0a78-48c9-aba4-a5cc5ce112eb","resolution":{"observed_at":"2026-08-06T12:25:49.403140Z","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":"2026-08-06T12:25:49.390749Z","title":"Exploring 3-d reconstruction techniques: A bench- marking tool for underwater robotics,","venue":null,"work_id":"d524198c-e66b-4eb4-8b24-6601593c6708","year":null},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.804115Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:c87edfcdfe8ad21ef6b4dd1be8baebfd3c650a9801a89452e3dd424a982ff42c","observation_id":"7fe7b5b4-18d8-4fc1-80d3-d593d4e0bba1","resolution":{"observed_at":"2026-08-06T12:25:49.394104Z","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":"2026-08-06T12:25:49.381105Z","title":"Benchmarks for aerial manipulation,","venue":null,"work_id":"9bbaa21b-f812-4742-9f65-ef3dcc2b5f92","year":null},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.807008Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:77d1847e04defa0fd9186ea7b52f173d2e48f6c1a3fb2e999f1385bd8e19026f","observation_id":"5ac8fa43-500f-4da6-be57-8c002b54113a","resolution":{"observed_at":"2026-08-06T12:25:49.384158Z","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":"2026-08-06T12:25:49.372447Z","title":"Aerial gym simulator: A framework for highly parallelized simulation of aerial robots,","venue":null,"work_id":"5c85a8b3-c932-44f2-9a71-7509265a7da1","year":2025},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.809776Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:249b7898d24981c5041aa93902bffd47b05c24b965e21fcf8eb9491edb7bf772","observation_id":"a8039467-aa88-436c-9c60-798ffb17bb26","resolution":{"observed_at":"2026-08-06T12:25:49.375590Z","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":"2026-08-06T12:25:49.362428Z","title":"Omnidrones: An efficient and flexible platform for reinforcement learning in drone control,","venue":null,"work_id":"81ea2051-7f8d-4a95-81d1-e9fb3e60ae1b","year":2024},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.812505Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:3222a4a7dd1fc705d8a6694c43bf50fe180eb871c9865d8a0e8b433bf2c6ce51","observation_id":"2cb2cf87-4953-4a67-8624-865fb0bbcb47","resolution":{"observed_at":"2026-08-06T12:25:49.366639Z","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":"2026-08-06T12:25:49.352793Z","title":"Assistive gym: A physics simulation framework for assistive robotics,","venue":null,"work_id":"e23e7f1f-b922-4ce5-9339-5c3447321b41","year":2020},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.815623Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:3f1f7f09dcc1934fe08701018c5d9033bdc7e875a1ccef5f8738c6c462e3e990","observation_id":"45b40e46-558d-4e66-b4fb-d136450c3f60","resolution":{"observed_at":"2026-08-06T12:25:49.355927Z","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":"2026-08-06T12:25:49.343858Z","title":"Rlroverlab: An advanced reinforce- ment learning suite for planetary rover simulation and training,","venue":null,"work_id":"8f809ff1-d341-4862-9209-bb469bbc91d3","year":2024},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.818459Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:8a4239b1074f58d4f4c818cf6dd5c2a47970a17068639f8ca5e24ab4825f1f95","observation_id":"92b15138-2f95-43f2-87f7-e45c808b519b","resolution":{"observed_at":"2026-08-06T12:25:49.347158Z","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":"2503.05652","last_updated":"2025-08-24T20:43:32Z","snapshot_observed_at":"2026-08-09T09:28:00.655508Z","submitted_at":"2025-03-07T18:15:21Z","title":"BEHAVIOR Robot Suite: Streamlining Real-World Whole-Body Manipulation for Everyday Household Activities","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.05652","snapshot_observed_at":"2026-08-06T12:25:48.821372Z","title":"Behavior robot suite: Streamlining real-world whole- body manipulation for everyday household activities,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.821372Z"},"links":{"cited_paper":"/paper/2503.05652","citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:ec5ec966068f019c682b8986305e11a14a2d59cd52e6ab6a33265e799404d2ac","observation_id":"a0b27531-8555-4544-bfcf-401199b3d8ef","resolution":{"observed_at":"2026-08-06T12:25:48.821372Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.18860","last_updated":"2024-06-06T05:53:19Z","snapshot_observed_at":"2026-07-06T18:21:48.356478Z","submitted_at":"2024-05-29T08:15:56Z","title":"Empowering Embodied Manipulation: A Bimanual-Mobile Robot Manipulation Dataset for Household Tasks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.18860","snapshot_observed_at":"2026-08-06T12:25:48.824953Z","title":"Empowering embodied manipulation: A bimanual- mobile robot manipulation dataset for household tasks,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.824953Z"},"links":{"cited_paper":"/paper/2405.18860","citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:69f6bb219cb7c0b24c540c511ca8ae6b686a4f9b8fde84bbb6ed84daeb056b22","observation_id":"3bcef111-933c-45fc-90d3-7132618c00f4","resolution":{"observed_at":"2026-08-06T12:25:48.824953Z","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":"2026-08-06T12:25:49.334063Z","title":"Habitat 2.0: Training home assistants to rearrange their habitat,","venue":null,"work_id":"9d2c312b-fa98-4e32-9c89-4910e86d3ec5","year":2021},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.828079Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:e4a52c3d99fec3383e4c59907eb488d467ac98b97df04b1c7d2f2ea119fe88a4","observation_id":"501a7cff-156e-41fe-a2df-e069b3a40bba","resolution":{"observed_at":"2026-08-06T12:25:49.337834Z","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":"2026-08-06T12:25:49.324602Z","title":"Benchmarking and simulating bimanual robot shoe lacing,","venue":null,"work_id":"64a18109-1177-44d8-bdef-359a375e2b33","year":2024},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.830909Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:2ec85e86c115cee4f413b4d947e402174175bd3c7063c40b46bf0c7a59687750","observation_id":"35b47c4e-dd73-4d65-8e4a-445388c76ed5","resolution":{"observed_at":"2026-08-06T12:25:49.328333Z","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":"2026-08-06T12:25:49.315335Z","title":"Orbit-surgical: An open-simulation framework for learning surgical augmented dexterity,","venue":null,"work_id":"0ea2ae26-c7c4-47e7-aad9-6eca54d0ce5a","year":2024},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.833699Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:ea893dfde2bfb7a692aef14f755ceb4d9cd1ff17356653ae4976345d24604d0c","observation_id":"5ff5b707-6846-47e2-aa0f-c599b48b1ade","resolution":{"observed_at":"2026-08-06T12:25:49.318579Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T12:25:48.836529Z","title":"Modeling, learning, perception, and control methods for deformable object manipulation,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.836529Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:f68aa12c0e1803d7c443b831ca496249a9e19a099f0940c595a001707475d313","observation_id":"88a7ad8f-bb23-4db1-880f-2e4f8e628114","resolution":{"observed_at":"2026-08-06T12:25:48.836529Z","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":"2026-08-06T12:25:49.300409Z","title":"Available: \\url{https://www.franka.de/}","venue":null,"work_id":"18ff624b-4ffc-43d4-ab9b-4d39b319b6bf","year":null},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.839628Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:25dddc3de58f666e4bc96b2a0727689d48b8107b2862fdc60c391afdc42ca94a","observation_id":"7f54ff2c-afd0-4394-9aff-6d78095c4391","resolution":{"observed_at":"2026-08-06T12:25:49.303397Z","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":"2026-08-06T12:25:49.290758Z","title":"Ridgeback,","venue":null,"work_id":"5844e0d0-cb49-4bae-af8d-84f434b40878","year":null},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.842516Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:72c5d70df29f88781d0a3a286a67f3c5cba0277466be6a154b67979ab9dcd6e4","observation_id":"71e92d5f-544d-4609-aa8f-e8093b46aecd","resolution":{"observed_at":"2026-08-06T12:25:49.294441Z","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":"2026-08-06T12:25:49.282605Z","title":null,"venue":null,"work_id":"bfbb7c48-7eb9-4b59-8b12-f5113ae3deb8","year":null},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.845236Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:c9b7db14c0979ca7c97fed7e26d99addcc0eb9e0ad2d87c1fa7cca073a5f4097","observation_id":"aeaa1851-6478-4038-a069-0b42866dfd99","resolution":{"observed_at":"2026-08-06T12:25:49.285440Z","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":"2026-08-06T12:25:49.274217Z","title":"Spot arm,","venue":null,"work_id":"d57af113-e712-49f0-85cf-18f0cf9a102a","year":null},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.848024Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:a38708c711bea8b94916d8aebbb8ce0ae9314279669e5f5dadb0a4508b5834aa","observation_id":"f7d1afd1-696c-48e2-a2e4-152d2881da98","resolution":{"observed_at":"2026-08-06T12:25:49.277039Z","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":"2026-08-06T12:25:49.264984Z","title":"Dinov2: Learning robust visual features without supervision,","venue":null,"work_id":"6925702c-1518-4058-8667-1e9c9343e78d","year":2023},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.850803Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:92cfce46e0630f6f99431b7cc8786bc75e5323f3badd21af7997e5ce89390798","observation_id":"809718db-9f13-4029-a5a2-063c70035656","resolution":{"observed_at":"2026-08-06T12:25:49.268432Z","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":"1707.06347","last_updated":"2017-08-28T09:20:06Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2017-07-20T02:32:33Z","title":"Proximal Policy Optimization Algorithms","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1707.06347","snapshot_observed_at":"2026-08-06T12:25:48.853534Z","title":"Proximal policy optimization algorithms,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.853534Z"},"links":{"cited_paper":"/paper/1707.06347","citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:f2f7c67d71bb8aafbc115b6f29ab162d3f47ce033a0412936b16cd8b7fcf6b94","observation_id":"884985ce-66c4-4954-9524-0b8e14ea94c6","resolution":{"observed_at":"2026-08-06T12:25:48.853534Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T12:25:48.856598Z","title":"Soft actor-critic: Off- policy maximum entropy deep reinforcement learning with a stochastic actor,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.856598Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:b4ddfaba1c305bd8ce59b25942c42536fd7c1f5328123b2410ae7ca0f9440a6e","observation_id":"353f5567-7efe-452b-bb60-d590d5a8b030","resolution":{"observed_at":"2026-08-06T12:25:48.856598Z","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":"2026-08-06T12:25:49.251216Z","title":"rl-games: A high-performance framework for reinforcement learning,","venue":null,"work_id":"279ee78e-e729-4a2d-b82f-78794bb9e55c","year":2021},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.859464Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:2f62f1c929428f34658564f1a2f440c4b842ec389be95e00066cf7d16e72883f","observation_id":"02df2a98-0354-41bd-8435-bf8b734519f0","resolution":{"observed_at":"2026-08-06T12:25:49.254546Z","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":"2026-08-06T12:25:49.242088Z","title":"A framework for behavioural cloning","venue":null,"work_id":"4c5e9cfb-825d-4ff6-9f40-1d409bceb37b","year":1995},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.862295Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:b8e7bff87c45063d55b0d199344f835c9f5b41caa95277871d3122f4eb22bbec","observation_id":"980ca689-9a17-4392-aabc-6b939687219c","resolution":{"observed_at":"2026-08-06T12:25:49.245020Z","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":"2408.15919","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T12:25:48.980557Z","title":"Available: https://arxiv.org/abs/2408.15919","venue":null,"work_id":"bee66b83-3f77-4318-a6e8-8976cbe271a6","year":null},"citing_paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-06T12:25:48.801335Z"},"links":{"citing_paper":"/paper/2507.21796"},"observation_digest":"sha256:7995b54d8cf68153b66f337338e0a9b96ff467c1150e62a3c44e79b47a711026","observation_id":"477d96ea-1c0c-480e-87b6-7bf0e17dd03b","resolution":{"observed_at":"2026-08-06T12:25:48.986232Z","resolver_source":"raw_fallback","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"}}],"paper":{"arxiv_id":"2507.21796","last_updated":"2025-07-29T13:33:43Z","latest_version":1,"primary_category":"cs.RO","snapshot_observed_at":"2026-08-09T09:28:21.323517Z","submitted_at":"2025-07-29T13:33:43Z","title":"MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects"},"reference_resolution":{"displayed":52,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":11,"verified_exact":3,"verified_fuzzy":38},"total_outbound_references":52},"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 52 of 52 outbound references and 0 inbound Pith citation observations for arXiv:2507.21796."}