{"as_of":"2026-08-07T05:38:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:3174ff6e475db16b22117975be087e3cefb8a7fa2b67577cfe6fcf2381fce051","coverage":[{"denominator":73,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":73,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-03T22:03:32.666762Z","state":"measured"},{"denominator":73,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":73,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-06T06:34:29.942622+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/2511.12795/citation-record","integrity":"/paper/2511.12795/integrity","json":"/paper/2511.12795/citation-record.json","paper":"/paper/2511.12795"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T22:03:23.778684Z","title":"Ac- tive vision for dexterous grasping of novel objects","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:23.778684Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:d1822490f59db669b6eb527c61e8f6f64c6a3bf050de894a13da856239f6a235","observation_id":"63632838-be94-4b5d-b2e2-e513764b37a8","resolution":{"observed_at":"2026-08-03T22:03:23.778684Z","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":"2026-08-03T22:03:23.835820Z","title":"Active perception.Proceedings of the IEEE, 76(8):966–1005, 1988","venue":null,"work_id":null,"year":1988},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:23.835820Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:29a53513f8fd40ed0274331f7d24549322e1c621f592ab2f4a4ec4d0b13b51c5","observation_id":"e7edb75e-3a7d-42ce-8fc6-9aa794c623e3","resolution":{"observed_at":"2026-08-03T22:03:23.835820Z","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":"2026-08-03T22:03:23.905298Z","title":"Re- visiting active perception.Autonomous Robots, 42:177–196,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:23.905298Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:b4d15c0907bca06c52411508df700f914d39511b7b661045592df8721cfc3955","observation_id":"a3686ee1-7b4c-4dc6-bbdd-4ba9ab6798b1","resolution":{"observed_at":"2026-08-03T22:03:23.905298Z","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":"2026-08-03T22:03:24.010467Z","title":"V olumetric grasping network: Real-time 6 dof grasp detection in clutter","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:24.010467Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:a4ae2429829788e02865b674bfbe4aec79c78a81c6ac87b34c13bb3d4a058e38","observation_id":"6c13ceef-7907-43bc-a44d-19a4df57f734","resolution":{"observed_at":"2026-08-03T22:03:24.010467Z","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":"2026-08-03T22:03:24.072341Z","title":"Closed-loop next-best-view planning for target- driven grasping","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:24.072341Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:937db74c369d745eef95b03c364ed8a00a35289e3a7b9d691201e651fa0562b5","observation_id":"01e8e89d-3aee-4429-92f5-e924d1628bea","resolution":{"observed_at":"2026-08-03T22:03:24.072341Z","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":"2026-08-03T22:03:24.284055Z","title":"Real-time collision-free grasp pose detection with geometry-aware refinement using high-resolution volume","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:24.284055Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:a641ba00e3a2bb1d2edd8b115331a35c5357eb0d4cc0802f485f6f587be148f6","observation_id":"d10a2885-c56a-43f0-a58e-1b2062b411e7","resolution":{"observed_at":"2026-08-03T22:03:24.284055Z","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":"2026-08-03T22:03:24.367510Z","title":null,"venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:24.367510Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:14b4a0669c86481fa185414ac3a3f6733ebd4e91d09ce354a6c93d1393789be6","observation_id":"d36fe10b-e657-400f-8a2a-928749e35cdc","resolution":{"observed_at":"2026-08-03T22:03:24.367510Z","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":"2026-08-03T22:03:24.508843Z","title":"Learning to ex- plore using active neural slam","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:24.508843Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:f0f0ccbd8d1a758c9ebd68336208da23302396f55780a2082137ef72dd117ebc","observation_id":"f023a000-9c47-463c-9381-8d1ff2330ade","resolution":{"observed_at":"2026-08-03T22:03:24.508843Z","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":"2026-08-03T22:03:24.631526Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:24.631526Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:79b0cb1c9651489237f113c35620d38805164a42e972a677388e520bbe0d9d9b","observation_id":"63d052bc-6e85-4917-9412-61ca8bb528ba","resolution":{"observed_at":"2026-08-03T22:03:24.631526Z","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":"2026-08-03T22:03:24.805537Z","title":"Transferable active grasp- ing and real embodied dataset","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:24.805537Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:ef9b7a778bf4e81bb51867bc255fa0e7857c9c6547b84ed44b1502730dc51098","observation_id":"fdf60c22-92ad-4944-b551-a149aa289b8d","resolution":{"observed_at":"2026-08-03T22:03:24.805537Z","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":"2026-08-03T22:03:24.974634Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:24.974634Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:fc921159836c6cb62c7f84c4051337fa3625882cc9f1251a6fb39d27179c1a73","observation_id":"4eec2f73-5663-4dfd-bc28-c441fa6ee9ae","resolution":{"observed_at":"2026-08-03T22:03:24.974634Z","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":"2026-08-03T22:03:25.155889Z","title":"Pybullet, a python mod- ule for physics simulation for games, robotics and machine learning.http://pybullet.org, 2016–2021","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:25.155889Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:142b7afdb86609767e1acfbbee2da5b51f8c1e80a1aa6a199afc1a8480a18846","observation_id":"88f09a44-a526-40a5-8590-8340f7bd80c0","resolution":{"observed_at":"2026-08-03T22:03:25.155889Z","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":"2026-08-03T22:03:25.282918Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:25.282918Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:7500a642488d39b81d849156055c48956f10117c5f9462dcdbd89dd3a993377c","observation_id":"fd136e8a-1717-4025-96b6-2c87a0e33ec2","resolution":{"observed_at":"2026-08-03T22:03:25.282918Z","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":"2026-08-03T22:03:25.432023Z","title":"Pred-nbv: Prediction-guided next-best-view planning for 3d object reconstruction","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:25.432023Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:a6a32dd34281defb5dfc09848b202e4c7065858f5b7b065ad60a3c8b05d0f2c4","observation_id":"db6d566e-0004-4806-bafe-8e35e6a52a5a","resolution":{"observed_at":"2026-08-03T22:03:25.432023Z","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":"2026-08-03T22:03:25.539962Z","title":"ACRONYM: A large-scale grasp dataset based on simula- tion","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:25.539962Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:05ea441fc56d70a2c378dd2d0906b5701f356b78873ab540ec09ab7666d8c90c","observation_id":"46c56d52-66b7-46b5-8654-24c3f8e97e2f","resolution":{"observed_at":"2026-08-03T22:03:25.539962Z","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":"2026-08-03T22:03:25.715509Z","title":"A density-based algorithm for discovering clusters in large spatial databases with noise","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:25.715509Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:2471f5e6a14bdfbc390753eca29fb6f0508e964406fcaa89c48552c5118ff18f","observation_id":"fdf8beea-7f92-4baf-8c4d-0fa59931f277","resolution":{"observed_at":"2026-08-03T22:03:25.715509Z","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":"2026-08-03T22:03:25.869487Z","title":"Anygrasp: Robust and efficient grasp perception in spa- tial and temporal domains.IEEE Trans","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:25.869487Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:2fc9e70aab3dcca75753b48ff103e3856751660ede88f39077c5ed4c662a780d","observation_id":"2bf599ff-0df6-40a3-b355-62fa0521383c","resolution":{"observed_at":"2026-08-03T22:03:25.869487Z","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":"2026-08-03T22:03:26.033787Z","title":"Kruspe, Rudolph Triebel, Peter Jung, Ribana Roscher, Muhammad Shahzad, Wen Yang, Richard Bamler, and Xiaoxiang Zhu","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:26.033787Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:9400074da5d776f8028feec410b8b08ee923dc43f777d9dc56f37a90ba2afe7e","observation_id":"05ef473f-c252-498b-a5af-ce155e58e55a","resolution":{"observed_at":"2026-08-03T22:03:26.033787Z","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":"2026-08-03T22:03:26.194836Z","title":"Uncertainty-driven planner for exploration and navigation","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:26.194836Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:ac064210831ea4bcaa99e0c6e4d6d2a4d1553f90ff2a0440a1d712192b4311fc","observation_id":"8c62a7df-a99f-47b2-ac93-becbf07a763e","resolution":{"observed_at":"2026-08-03T22:03:26.194836Z","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":"2026-08-03T22:03:26.268110Z","title":"Bayes’ Rays: Uncertainty quantifica- tion in neural radiance fields.arXiv, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:26.268110Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:97af82e4dd7d37899394431fcdec5aed572a6d1c64736a0ec9f2831607478b9b","observation_id":"00cb1924-d9b1-4186-9dd3-71be953b354b","resolution":{"observed_at":"2026-08-03T22:03:26.268110Z","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":"2026-08-03T22:03:26.364618Z","title":"Your classifier is secretly an energy based model and you should treat it like one","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:26.364618Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:37c3348ea01e74ad62d8faa30d4e8cb9aa17a7adb3d21aadd5abce0177c8ff10","observation_id":"3c6d7ad9-5544-40e2-b3e5-cc74ef12f918","resolution":{"observed_at":"2026-08-03T22:03:26.364618Z","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":"2026-08-03T22:03:26.472054Z","title":"Viewpoint selection for grasp detection","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:26.472054Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:ae674fa0fe6e4b43a9a75795b5c61ff75e51be35e107fd45d9e4a76191a1822c","observation_id":"0203904a-0bbc-4fbf-8b17-8637ebeac14b","resolution":{"observed_at":"2026-08-03T22:03:26.472054Z","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":"2026-08-03T22:03:26.576525Z","title":"High precision grasp pose detection in dense clutter","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:26.576525Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:05a355211ea83606a25e5c9c95e22e7470b23f719689465b741d32ecda291087","observation_id":"e218ea3a-cfba-4dda-aac2-5ec5ccea54ea","resolution":{"observed_at":"2026-08-03T22:03:26.576525Z","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":"2026-08-03T22:03:26.714103Z","title":"Scone: Surface coverage optimization in unknown environ- ments by volumetric integration.Advances in Neural Infor- mation Processing Systems, 35:20731–20743, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:26.714103Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:a42be139aec8c23f856b8e824eac2f4a264e893a5500a489fe9929608d188beb","observation_id":"73473a77-0618-4eb1-936f-1667e2d95df6","resolution":{"observed_at":"2026-08-03T22:03:26.714103Z","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":"2026-08-03T22:03:26.845664Z","title":"Macarons: Mapping and coverage anticipa- tion with rgb online self-supervision","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:26.845664Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:75758a894f4d723a4581b5a13b79a99d53ab69c284136ff6e36c88a7fdcf9120","observation_id":"d85852f5-b162-47a1-88ed-1ff33f90d386","resolution":{"observed_at":"2026-08-03T22:03:26.845664Z","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":"2026-08-03T22:03:26.970183Z","title":"Weinberger","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:26.970183Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:fb012201e90acef459c2beb909f63de54af3511e8c7660b84aa1be7bd45e5a0d","observation_id":"64a87da9-af2b-4eff-ae2c-79a39d717c01","resolution":{"observed_at":"2026-08-03T22:03:26.970183Z","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":"2026-08-03T22:03:27.083945Z","title":"Orbitgrasp: Se(3)-equivariant grasp learning","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:27.083945Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:c897355b8aab5481e02e4b6650642f925f2852dbed74a011e23bb22d4943cba1","observation_id":"6378b48e-e164-4685-914b-21b7cb1f6c4e","resolution":{"observed_at":"2026-08-03T22:03:27.083945Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.16054","last_updated":"2025-04-22T17:31:29Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-04-22T17:31:29Z","title":"$\\pi_{0.5}$: a Vision-Language-Action Model with Open-World Generalization","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.16054","snapshot_observed_at":"2026-08-03T22:03:27.184247Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:27.184247Z"},"links":{"cited_paper":"/paper/2504.16054","citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:5cb341f24a818ae090768b68a92524c6b91456a5cb1524a2100f2ae2979203a3","observation_id":"1e5343eb-1f60-4702-a82a-269dbe94dcd3","resolution":{"observed_at":"2026-08-03T22:03:27.184247Z","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":"2026-08-03T22:03:27.292593Z","title":"Maddox, Polina Kirichenko, Timur Garipov, Dmitry P","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:27.292593Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:2e6fd693e0a2f85d3df3a02a52b00438fa32d5c45792469aeb78dffaa2a5b459","observation_id":"f34453e1-2909-4c4b-9776-6e2088df6041","resolution":{"observed_at":"2026-08-03T22:03:27.292593Z","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":"2026-08-03T22:03:27.440974Z","title":"Fisherrf: Ac- tive view selection and mapping with radiance fields using fisher information","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:27.440974Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:314cf77b07ad8ae3e1da4113c03b169961b91b99725fd7a7b18836d15b737aae","observation_id":"cfc008b8-2d9a-4970-96ba-bd588d14c15f","resolution":{"observed_at":"2026-08-03T22:03:27.440974Z","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":"2026-08-03T22:03:27.518745Z","title":"Multimodal llm guided exploration and active map- ping using fisher information","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:27.518745Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:4e568447d1d40d6cc06ea44676f2b85627e03dd79a7ccc6161cc1ead4f31b58c","observation_id":"86700415-f02d-489d-a8fe-628ddc5bca7f","resolution":{"observed_at":"2026-08-03T22:03:27.518745Z","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":"2026-08-03T22:03:27.584618Z","title":"Neu-nbv: Next best view planning using uncer- tainty estimation in image-based neural rendering","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:27.584618Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:7797c9d5a01988be564bbd024c5cf1b7350937dc607772bf4a40ba001f67f836","observation_id":"32e8bb5d-3fed-47b8-a0f3-afdc9e124447","resolution":{"observed_at":"2026-08-03T22:03:27.584618Z","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":"2026-08-03T22:03:27.685678Z","title":null,"venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:27.685678Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:cf933c96044df127d0f5246e8077f08b5406726647d8134b9f47e7fe5203d056","observation_id":"56294fba-5290-4654-b5a3-712240fc2f4d","resolution":{"observed_at":"2026-08-03T22:03:27.685678Z","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":"2026-08-03T22:03:27.886389Z","title":"Bopar- dikar, Julian Ryde, Kenneth Y","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:27.886389Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:95907d86b571eb00e43ae74961d79d4e6926089852c82c78408082903e45f32a","observation_id":"68a65fc9-76f9-4895-a986-11dd35801888","resolution":{"observed_at":"2026-08-03T22:03:27.886389Z","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":"2026-08-03T22:03:27.984255Z","title":"Spherical fibonacci mapping.ACM Trans","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:27.984255Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:e338e7ad6bdb3221b1781adf3c657b077bd0ffc0c4b7309a674b15859fe26292","observation_id":"0bfbf8c1-26b2-4927-82dd-bca06103a027","resolution":{"observed_at":"2026-08-03T22:03:27.984255Z","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":"2026-08-03T22:03:28.126766Z","title":"3d gaussian splatting for real-time radiance field rendering.ACM Transactions on Graphics, 42 (4), 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:28.126766Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:fcb41e7c8c4438e81d378ddb0ee0ee24f2b104462a12c231c2902bdb3355e655","observation_id":"dbe27169-bef2-4ed3-9ba3-87c82fed82c3","resolution":{"observed_at":"2026-08-03T22:03:28.126766Z","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":"2026-08-03T22:03:28.259093Z","title":"Unifying approaches in ac- tive learning and active sampling via fisher information and information-theoretic quantities.Transactions on Machine Learning Research, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:28.259093Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:2aaaa8fccf4597dbf0242ef5860ba4179ac7c1243a4d70cc2f7d97e5942aeb48","observation_id":"0d4fb2de-b8c0-471a-bed9-d3a3534fe9a3","resolution":{"observed_at":"2026-08-03T22:03:28.259093Z","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":"2026-08-03T22:03:28.389304Z","title":"A survey on learning-based robotic grasp- ing.Current Robotics Reports, 1:239–249, 2020","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:28.389304Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:153b4dc760e77ed282a877f5939243b17300642ecdc4457be4507f28cbbbc6cd","observation_id":"0899a37b-03b2-40e1-8dcc-61fed46698d4","resolution":{"observed_at":"2026-08-03T22:03:28.389304Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.12656","last_updated":"2019-10-28T13:23:09Z","snapshot_observed_at":"2026-07-06T08:32:45.995913Z","submitted_at":"2019-10-28T13:23:09Z","title":"Beyond temperature scaling: Obtaining well-calibrated multiclass probabilities with Dirichlet calibration","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.12656","snapshot_observed_at":"2026-08-03T22:03:28.503902Z","title":null,"venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:28.503902Z"},"links":{"cited_paper":"/paper/1910.12656","citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:02642ee612951c3be72030157cd202e51e1ec44da5bf4ab0c8e1de088889a08d","observation_id":"bdf74e70-b0ec-4790-8cca-58c3d8bdc7ea","resolution":{"observed_at":"2026-08-03T22:03:28.503902Z","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":"2026-08-03T22:03:28.599833Z","title":"A tutorial on energy-based learning.Predicting structured data, 1(0), 2006","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:28.599833Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:52078e7915e5f513c2ba1c6375b7b0a8de8184122662d0224ccd78ec2027019c","observation_id":"e6617e5e-7221-4bb4-b2b3-964d6e795245","resolution":{"observed_at":"2026-08-03T22:03:28.599833Z","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":"2026-08-03T22:03:28.713377Z","title":"Deep learning for detecting robotic grasps.Int","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:28.713377Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:1b901123eeff4f304d5441b166a164846d8578801191bd5d473e9ea052585839","observation_id":"72878812-bcbb-43d3-889f-bf5c2d280f31","resolution":{"observed_at":"2026-08-03T22:03:28.713377Z","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":"2026-08-03T22:03:28.805813Z","title":"Eval- uating and calibrating uncertainty prediction in regression tasks.Sensors, 22(15):5540, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:28.805813Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:c877697a280c70864a0bb4649609dd6121e9d0cade015cb3bf43e769b645528a","observation_id":"0f6149f1-d9c9-4ff4-ac0a-b1cc00a29528","resolution":{"observed_at":"2026-08-03T22:03:28.805813Z","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":"2026-08-03T22:03:28.906100Z","title":"Learning hand-eye coordination for robotic grasping with deep learning and large-scale data col- lection.Int","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:28.906100Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:09ac689274eee43f8f2f380264663cbab09a9f4be7be5c7f2f504b952e050f4a","observation_id":"581a7620-f6e7-451f-b5bd-6fe06af57deb","resolution":{"observed_at":"2026-08-03T22:03:28.906100Z","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":"2026-08-03T22:03:29.016204Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:29.016204Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:e1d916491e0b0541cf96ead8f96055d517848e8a845ab5471fb4557d353814c6","observation_id":"b0536790-ab74-4d82-bd2e-cc65c63a7b2a","resolution":{"observed_at":"2026-08-03T22:03:29.016204Z","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":"2026-08-03T22:03:29.143864Z","title":"Active perception for grasp detection via neural graspness field","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:29.143864Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:0b1cbf5a4d65016ed41fce6066df443453cf686eeefc489ecd17d680f87fa522","observation_id":"f3c3d792-dce3-4b60-bbfe-f5ff71dccf16","resolution":{"observed_at":"2026-08-03T22:03:29.143864Z","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":"2026-08-03T22:03:29.345065Z","title":"Dex-net 2.0: Deep learning to plan robust grasps with synthetic point clouds and analytic grasp metrics","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:29.345065Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:e8badb8fe7aebd5bf6357019ca84f2f699eb075355554be82cc6c951e8b490f6","observation_id":"62372bd0-aa44-49b5-9bfc-83e3adbf0faf","resolution":{"observed_at":"2026-08-03T22:03:29.345065Z","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":"2026-08-03T22:03:29.497805Z","title":"Wells III, Clare M","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:29.497805Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:2199efc3589633d47a0754801ce80766ff3a00326c1e4083ba03c840120d2dde","observation_id":"de0690ea-e711-4283-b7f0-8cc11e0d3d0e","resolution":{"observed_at":"2026-08-03T22:03:29.497805Z","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":"2026-08-03T22:03:29.565813Z","title":"Multi- view picking: Next-best-view reaching for improved grasp- ing in clutter","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:29.565813Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:0abf8d49bdb0ff9e1427a07e20c32d1e3ae416fc00700790316b1e61cff9e602","observation_id":"091f61bd-62c8-444e-9ea8-5c3755541ec8","resolution":{"observed_at":"2026-08-03T22:03:29.565813Z","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":"2026-08-03T22:03:29.668762Z","title":"Ac- tivenerf: Learning where to see with uncertainty estimation","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:29.668762Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:388b6f780dd724496ee0897e77ae76b15a70755ee1f1901f45b93cdadae1d83a","observation_id":"90068abd-f26c-4c61-aeaf-8d0d700541ad","resolution":{"observed_at":"2026-08-03T22:03:29.668762Z","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":"2026-08-03T22:03:29.844309Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:29.844309Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:d78fc5a4636ba246f8dba9f67474998ef22152401fd347fe1cc13c02eecaeccf","observation_id":"f1572716-855f-40a3-88b1-77aed0e61fc7","resolution":{"observed_at":"2026-08-03T22:03:29.844309Z","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":"2026-08-03T22:03:29.961461Z","title":"Supersizing self- supervision: Learning to grasp from 50k tries and 700 robot hours","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:29.961461Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:c6c2c7a4a4d8d3e9eabd2ff9e2f165922c9ef9d6f2883bbd6ccd33b37352f4ad","observation_id":"7e936ef2-1ad5-4743-8e88-63594c2eef6d","resolution":{"observed_at":"2026-08-03T22:03:29.961461Z","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":"2026-08-03T22:03:30.130915Z","title":"Grasp learning: Models, methods, and per- formance.Annual Review of Control, Robotics, and Au- tonomous Systems, 6(1):363–389, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:30.130915Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:9dddba4ed58fca8420798e4bebde056a999e6270113854cbe9c6faa37025c092","observation_id":"bbf724e3-399d-4379-8025-76d792ea96c5","resolution":{"observed_at":"2026-08-03T22:03:30.130915Z","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":"2026-08-03T22:03:30.264791Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:30.264791Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:d1d4a28d412e6712716a29ac62f4de9a809955772a0305e01c97186abba45542","observation_id":"f1b5c2d9-9aa5-4eca-84af-1dcd5468dbf1","resolution":{"observed_at":"2026-08-03T22:03:30.264791Z","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":"2026-08-03T22:03:30.381284Z","title":"Occupancy anticipation for efficient exploration and navigation","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:30.381284Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:e3e98cabf9d0f1796f1c475478a8c962f5b023118de09279d98c5dace908a8a0","observation_id":"4973cdaa-193e-4231-82ca-71d665e01a6f","resolution":{"observed_at":"2026-08-03T22:03:30.381284Z","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":"2026-08-03T22:03:30.505623Z","title":"Neurar: Neural uncertainty for autonomous 3d reconstruction with implicit neural representations.IEEE Robotics and Automation Let- ters, 8(2):1125–1132, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:30.505623Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:3af14a81dcfd976fb91a6a34855f564b57321d44e08ddc29c1416a7608c696f3","observation_id":"420b8e90-05c7-49bd-bacc-8efc5ae81e66","resolution":{"observed_at":"2026-08-03T22:03:30.505623Z","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":"2026-08-03T22:03:30.692217Z","title":"SAM 2: Segment anything in images and videos","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:30.692217Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:5508a13cbb91f3d6b0a7e11c6cb6504652fc9a632d9eaada791a611b2b5dea0c","observation_id":"62f3e41d-9949-47b1-af6a-2922f55660f6","resolution":{"observed_at":"2026-08-03T22:03:30.692217Z","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":"2026-08-03T22:03:30.855134Z","title":"Real-time grasp de- tection using convolutional neural networks","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:30.855134Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:544f70d41e1cd674af462a9b1c4420ea5001141632d30117c4389e37a4c322d7","observation_id":"8bb1f5e2-6da9-4474-8aeb-1a1340b60f6a","resolution":{"observed_at":"2026-08-03T22:03:30.855134Z","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":"2026-08-03T22:03:31.009643Z","title":"Rezende, and C´esar Roberto de Souza","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:31.009643Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:b4726ac31d89e66f06ffc64e15c80d3923868a9cdb12736a44dc227f2d22cea3","observation_id":"21a4e87a-2001-49a2-8474-d4c502e354eb","resolution":{"observed_at":"2026-08-03T22:03:31.009643Z","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":"2026-08-03T22:03:31.170692Z","title":"Learn- ing for single-shot confidence calibration in deep neural net- works through stochastic inferences","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:31.170692Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:235d0dcc6f544a4f9b90c283f459d5849e0255a4d2702bd3dc31a9e62da25c13","observation_id":"98067900-a3b6-49b3-8a8f-d8e484232b0e","resolution":{"observed_at":"2026-08-03T22:03:31.170692Z","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":"2026-08-03T22:03:31.335260Z","title":"Generative modeling by estimating gradients of the data distribution","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:31.335260Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:1db2a190169c2d0e946d3e3f72728f0c8621d1630dde4f6c37f92c0d6c8bbbb1","observation_id":"5f519958-da82-45dc-b314-a92beaf89a9b","resolution":{"observed_at":"2026-08-03T22:03:31.335260Z","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":"2026-08-03T22:03:31.431505Z","title":"Contact-graspnet: Efficient 6-dof grasp gen- eration in cluttered scenes","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:31.431505Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:2f99506c0b8679e29c9524ab77ab36f4f02016f589e56026f22b973ecf805bb1","observation_id":"5b6d0627-71b8-4621-ac71-af4daf17061f","resolution":{"observed_at":"2026-08-03T22:03:31.431505Z","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":"2026-08-03T22:03:31.563582Z","title":"Rethinking the in- ception architecture for computer vision","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:31.563582Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:e47c4be9f41445c9651e6fd939d445351f04117ef3a897822859a7811e1a9466","observation_id":"cf8d1d1d-82e4-45dd-8d1d-7cbd6fffa599","resolution":{"observed_at":"2026-08-03T22:03:31.563582Z","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":"2026-08-03T22:03:31.792830Z","title":"Grasp pose detection in point clouds.The International Journal of Robotics Research, 36(13-14):1455–1473, 2017","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:31.792830Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:a66fc882e8f4a42a8d7bf5a09f10c2dd1864753567539f1014e4139c5048b513","observation_id":"8d97b11b-efeb-4d66-9749-cae4f672528d","resolution":{"observed_at":"2026-08-03T22:03:31.792830Z","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":"2026-08-03T22:03:31.856841Z","title":"Se(3)-diffusionfields: Learning smooth cost func- tions for joint grasp and motion optimization through diffu- sion","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:31.856841Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:5158de5b6945d91e40b00e21a52c9a839334475938be3960ef33d4b43dc91249","observation_id":"777b758a-aebf-4adf-b72b-2b8825e5a3d3","resolution":{"observed_at":"2026-08-03T22:03:31.856841Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.11142","last_updated":"2024-06-17T02:06:47Z","snapshot_observed_at":"2026-07-06T18:31:53.591578Z","submitted_at":"2024-06-17T02:06:47Z","title":"Graspness Discovery in Clutters for Fast and Accurate Grasp Detection","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.11142","snapshot_observed_at":"2026-08-03T22:03:31.963560Z","title":"Graspness discovery in clutters for fast and accurate grasp detection.CoRR, abs/2406.11142,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:31.963560Z"},"links":{"cited_paper":"/paper/2406.11142","citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:c2b98722e63636411a441ed94de7567c972efcf776665bcff14d3ea5197c4ae8","observation_id":"c6e101ce-51c2-48a4-b726-92fdbd9a5a09","resolution":{"observed_at":"2026-08-03T22:03:31.963560Z","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":"2026-08-03T22:03:32.068787Z","title":"GPR: grasp pose refine- ment network for cluttered scenes","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:32.068787Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:605c0e6e341506f97ae9d10d8ed720fdf91f7b49418a5462fe275beb55bcd6ba","observation_id":"cbbbdb69-5247-42ae-95a1-ad88579c38a3","resolution":{"observed_at":"2026-08-03T22:03:32.068787Z","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":"2026-08-03T22:03:32.173645Z","title":"Capgrasp: An $\\mathbb{R}ˆ{3}\\times\\text{SO(2)- Equivariant}$ continuous approach-constrained generative grasp sampler.IEEE Robotics Autom","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:32.173645Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:76ec11e8b76ef6eddb79270d6a65e5a87ecd74e99f53ecca6b4ab8905bc5ef2c","observation_id":"1ec0daf8-beda-4560-9562-05308b27f4e0","resolution":{"observed_at":"2026-08-03T22:03:32.173645Z","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":"2026-08-03T22:03:32.244590Z","title":"Non-parametric calibration for classification","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:32.244590Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:c39749f8422bfb429131d3e89c6f1bdca612a5a89b4f5bf8f578fafc10909e85","observation_id":"4d8ed1c2-6f68-4fae-816a-ced980c9922b","resolution":{"observed_at":"2026-08-03T22:03:32.244590Z","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":"2026-08-03T22:03:32.339958Z","title":"Active neural mapping","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:32.339958Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:0265c8a8ee18291c094153f90e9e3305b76fa093b7bacff087d006e9ded2a295","observation_id":"c3833e62-f9c3-475a-85fd-6cf5fd8d4bf3","resolution":{"observed_at":"2026-08-03T22:03:32.339958Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2202.03631","last_updated":"2022-02-08T03:59:20Z","snapshot_observed_at":"2026-08-06T08:48:32.037373Z","submitted_at":"2022-02-08T03:59:20Z","title":"Robotic Grasping from Classical to Modern: A Survey","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2202.03631","snapshot_observed_at":"2026-08-03T22:03:32.450754Z","title":"Robotic grasping from classical to modern: A survey.arXiv preprint arXiv:2202.03631, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:32.450754Z"},"links":{"cited_paper":"/paper/2202.03631","citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:838de10a938c03556f4df65fd94ced85c6c28e8322ff0028bb4dacc45bbf150e","observation_id":"ed398476-cc3f-49b5-8a5a-0a8ed891bb9e","resolution":{"observed_at":"2026-08-03T22:03:32.450754Z","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":"2026-08-03T22:03:32.557528Z","title":"Affordance-driven next-best- view planning for robotic grasping","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:32.557528Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:08c41692e2238cc3e3d1b5af8237a75c05584c48a55ee5dff5e69fa933cf357e","observation_id":"024de264-b62e-486a-a10a-9910d975c81e","resolution":{"observed_at":"2026-08-03T22:03:32.557528Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1801.09847","last_updated":"2018-01-30T04:33:20Z","snapshot_observed_at":"2026-07-06T06:20:51.245757Z","submitted_at":"2018-01-30T04:33:20Z","title":"Open3D: A Modern Library for 3D Data Processing","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1801.09847","snapshot_observed_at":"2026-08-03T22:03:32.666762Z","title":"Open3d: A modern library for 3d data processing.CoRR, abs/1801.09847, 2018","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:32.666762Z"},"links":{"cited_paper":"/paper/1801.09847","citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:5b102ceb29fcef1ac6c2775d4c4d2b3ba5f42c9206a8b7d3d7fa246c0de488fd","observation_id":"695fe2f7-b016-4bb8-ba98-eac541f25f61","resolution":{"observed_at":"2026-08-03T22:03:32.666762Z","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":"2026-08-03T22:03:31.703046Z","title":null,"venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model","version":2},"reference_index":2826,"source":"pdf_text","source_observed_at":"2026-08-03T22:03:31.703046Z"},"links":{"citing_paper":"/paper/2511.12795"},"observation_digest":"sha256:dc2a85f58e4899d5ff020f91ce1afe6c2bee8f391013d9082dbc9d57cb28663c","observation_id":"10e815d5-ffcc-471a-a990-ca253d8b0e28","resolution":{"observed_at":"2026-08-03T22:03:31.703046Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2511.12795","last_updated":"2026-06-04T23:11:07Z","latest_version":2,"primary_category":"cs.RO","snapshot_observed_at":"2026-08-06T15:53:49.540569Z","submitted_at":"2025-11-16T21:55:05Z","title":"ActiveGrasp: Information-Guided Active Grasping with Calibrated Energy-based Model"},"reference_resolution":{"displayed":73,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":73,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":73},"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":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 73 of 73 outbound references and 0 inbound Pith citation observations for arXiv:2511.12795."}