{"as_of":"2026-08-22T00:40:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:8e5b513f9adf4159934cdb4cd7a2401c7582f245bd06f5ef260a3fcce354063a","coverage":[{"denominator":82,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":82,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-05T12:19:11.863120Z","state":"measured"},{"denominator":86,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":86,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-21T06:32:19.484+00:00","state":"measured"},{"denominator":4,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":4,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-14T18:52:37.718635Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-02T03:56:34.460834Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"cited_work":{"arxiv_id":"2509.01746","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2509.01746","snapshot_observed_at":"2026-07-02T03:56:34.460834Z","title":"Fail2progress: Learning from real-world robot failures with stein variational in- ference","venue":null,"work_id":"62903431-7cd9-4d7f-8640-8adae670f326","year":2025},"citing_paper":{"arxiv_id":"2510.19268","last_updated":"2026-04-15T17:36:28Z","snapshot_observed_at":"2026-08-16T18:37:43.230429Z","submitted_at":"2025-10-22T05:57:23Z","title":"Hierarchical DLO Routing with Reinforcement Learning and In-Context Vision-language Models","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-05-18T05:21:09.184463Z"},"links":{"cited_paper":"/paper/2509.01746","citing_paper":"/paper/2510.19268"},"observation_digest":"sha256:325de9136515dea4f2e2fa1e9bceb95b3b1330143bafc946905aa06631ed038e","observation_id":"227cbdff-8c95-4690-84d1-7352c5035f17","resolution":{"observed_at":"2026-05-18T05:22:24.028990Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"cited_work":{"arxiv_id":"2509.01746","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2509.01746","snapshot_observed_at":"2026-07-02T03:56:34.460834Z","title":"Fail2progress: Learning from real-world robot failures with stein variational in- ference","venue":null,"work_id":"62903431-7cd9-4d7f-8640-8adae670f326","year":2025},"citing_paper":{"arxiv_id":"2605.19029","last_updated":"2026-07-13T06:03:13Z","snapshot_observed_at":"2026-08-20T06:57:05.575868Z","submitted_at":"2026-05-18T18:54:29Z","title":"Distributionally Robust Control via Stein Variational Inference for Contact-Rich Manipulation","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-20T09:23:20.788617Z"},"links":{"cited_paper":"/paper/2509.01746","citing_paper":"/paper/2605.19029"},"observation_digest":"sha256:da8c82deecfbe4f135e7cf29dbabb4c3bb7d5cd83c86e8d426ff053e9b2434f3","observation_id":"1e1e3ad7-0ba2-4ab2-9b59-fe3e21eeb78f","resolution":{"observed_at":"2026-05-20T09:23:24.977267Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2509.01746","snapshot_observed_at":"2026-07-14T18:52:37.718635Z","title":"Fail2progress: Learning from real-world robot failures with stein variational in- ference, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2605.19029","last_updated":"2026-07-13T06:03:13Z","snapshot_observed_at":"2026-08-20T06:57:05.575868Z","submitted_at":"2026-05-18T18:54:29Z","title":"Distributionally Robust Control via Stein Variational Inference for Contact-Rich Manipulation","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-07-14T18:52:37.718635Z"},"links":{"cited_paper":"/paper/2509.01746","citing_paper":"/paper/2605.19029"},"observation_digest":"sha256:f37bd6a0e9f043225374327fe803a572b68dd3e4086e5056b62d9571f7cf10ce","observation_id":"030493f0-58e6-4fa9-b2eb-41e47b87c96e","resolution":{"observed_at":"2026-07-14T18:52:37.718635Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"cited_work":{"arxiv_id":"2509.01746","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2509.01746","snapshot_observed_at":"2026-07-02T03:56:34.460834Z","title":"Fail2progress: Learning from real-world robot failures with stein variational in- ference","venue":null,"work_id":"62903431-7cd9-4d7f-8640-8adae670f326","year":2025},"citing_paper":{"arxiv_id":"2606.03385","last_updated":"2026-06-02T09:29:03Z","snapshot_observed_at":"2026-08-14T02:59:37.231666Z","submitted_at":"2026-06-02T09:29:03Z","title":"Grasp-Then-Plan with Failure Attribution: A Closed Two-Stage Framework for Precise and Generalizable Robotic Manipulation","version":1},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-06-28T09:37:58.434897Z"},"links":{"cited_paper":"/paper/2509.01746","citing_paper":"/paper/2606.03385"},"observation_digest":"sha256:fcbee67fe4b22bf2f520617e9f2d86cef58c7bd03c398dea2740147857679a48","observation_id":"65bbf61c-ee6e-425f-abf2-b62fc2bccf1c","resolution":{"observed_at":"2026-07-02T03:56:34.462349Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2509.01746/citation-record","integrity":"/paper/2509.01746/integrity","json":"/paper/2509.01746/citation-record.json","paper":"/paper/2509.01746"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2109.08771","last_updated":"2022-04-14T01:07:35Z","snapshot_observed_at":"2026-08-16T17:55:47.077258Z","submitted_at":"2021-09-17T22:06:58Z","title":"Search-Based Task Planning with Learned Skill Effect Models for Lifelong Robotic Manipulation","version":2},"cited_work":{"arxiv_id":"2109.08771","doi":null,"metadata_source":"pith","pith_arxiv_id":"2109.08771","snapshot_observed_at":"2026-08-05T12:19:12.397070Z","title":"Search-Based Task Planning with Learned Skill Effect Models for Lifelong Robotic Manipulation","venue":"cs.RO","work_id":"42568ae9-9495-4fb4-9bb6-2e12e579aa29","year":2021},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.664542Z"},"links":{"cited_paper":"/paper/2109.08771","citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:143ecfa1e78801809923c9d1be95b8cda7b388e36859cffe100099cd7c92ab05","observation_id":"d5eec362-b730-49c8-93b4-16db51f19117","resolution":{"observed_at":"2026-08-05T12:19:12.399699Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.14769","last_updated":"2025-03-04T02:53:51Z","snapshot_observed_at":"2026-08-20T17:31:37.822662Z","submitted_at":"2024-08-27T04:10:22Z","title":"Points2Plans: From Point Clouds to Long-Horizon Plans with Composable Relational Dynamics","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.14769","snapshot_observed_at":"2026-08-05T12:19:11.668364Z","title":"Huang, C","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.668364Z"},"links":{"cited_paper":"/paper/2408.14769","citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:db78b04c9a406ad096c9709bb0fc4913992d02089e67151b7e9b7bfdb8a44470","observation_id":"117bfd4c-0943-4828-adc8-c0849d1f741f","resolution":{"observed_at":"2026-08-05T12:19:11.668364Z","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":"2026-08-05T12:19:11.671140Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.671140Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:bee568f6ae609cb988b98b8c89c2e046906c85789825248ca8147ad60ddc94e0","observation_id":"43ddcbed-bd38-4aec-94f8-9093cbf54733","resolution":{"observed_at":"2026-08-05T12:19:11.671140Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2108.12062","last_updated":"2021-08-26T23:05:05Z","snapshot_observed_at":"2026-08-18T07:25:08.734312Z","submitted_at":"2021-08-26T23:05:05Z","title":"Predicting Stable Configurations for Semantic Placement of Novel Objects","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2108.12062","snapshot_observed_at":"2026-08-05T12:19:11.674367Z","title":"Paxton, C","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.674367Z"},"links":{"cited_paper":"/paper/2108.12062","citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:d117cd8bff462552bb3a4cc078fbee3c8fa957e6769b6b345d503233444ee515","observation_id":"2a2a9f12-25ba-4fbe-a890-a60d6d3d3f8d","resolution":{"observed_at":"2026-08-05T12:19:11.674367Z","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":"2026-08-05T12:19:11.677281Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.677281Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:94425afbee72c8d39ecef91293299b80d502a1791d55aabb82842e95f4bacaf9","observation_id":"4762f187-3e8d-413b-9c3f-f3902c2d8d10","resolution":{"observed_at":"2026-08-05T12:19:11.677281Z","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":"2026-08-05T12:19:12.804984Z","title":"Tremblay, A","venue":null,"work_id":"e6457591-7388-4ae0-957c-13d502a8a957","year":2018},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.680147Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:b6e2cca098be8c2f043ef70ff4cdbee3b8d16edf33c44d9905caf4aa8b9a97f4","observation_id":"2f15fbdf-f811-4bc4-940d-744d9cb66a66","resolution":{"observed_at":"2026-08-05T12:19:12.808772Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T12:19:11.683244Z","title":"Tobin, R","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.683244Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:5f6724cd49ab861f3bab05c972e52a42ce7d121973a41779b7a3227cdd633e1c","observation_id":"50503f2a-6d67-4ccd-82f1-4ad3458bac60","resolution":{"observed_at":"2026-08-05T12:19:11.683244Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1906.01728","last_updated":"2019-06-04T21:12:41Z","snapshot_observed_at":"2026-08-15T15:35:01.516908Z","submitted_at":"2019-06-04T21:12:41Z","title":"BayesSim: adaptive domain randomization via probabilistic inference for robotics simulators","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1906.01728","snapshot_observed_at":"2026-08-05T12:19:11.685674Z","title":"Ramos, R","venue":null,"work_id":null,"year":1906},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.685674Z"},"links":{"cited_paper":"/paper/1906.01728","citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:819447b5a64f895ad6b55961a59f85df12ff60d0779af5fc50c65266fa7c0346","observation_id":"fa93c64a-4bd2-4178-9cf4-b283d0846d00","resolution":{"observed_at":"2026-08-05T12:19:11.685674Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.08864","last_updated":"2025-05-14T15:22:36Z","snapshot_observed_at":"2026-08-13T13:59:48.091257Z","submitted_at":"2023-10-13T05:20:40Z","title":"Open X-Embodiment: Robotic Learning Datasets and RT-X Models","version":9},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.08864","snapshot_observed_at":"2026-08-05T12:19:11.688569Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.688569Z"},"links":{"cited_paper":"/paper/2310.08864","citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:7bafa62b158d2f1e61f5aebd8322a8bbd962a958af02b7a9c09fba85ccfe8fe3","observation_id":"c2bc2316-319c-4d3a-88a1-1bdd2d06c03d","resolution":{"observed_at":"2026-08-05T12:19:11.688569Z","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":"2026-08-05T12:19:11.691538Z","title":"Khazatsky, K","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.691538Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:5861159828e05b5db21ad6dfa7167b2f684fc82c82db54fadf3b739298f5972e","observation_id":"8cf45535-fa24-4aae-bfd3-ac8c77569094","resolution":{"observed_at":"2026-08-05T12:19:11.691538Z","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":"2026-08-05T12:19:12.786327Z","title":null,"venue":null,"work_id":"0820502f-2886-4bac-8253-86b99538c457","year":2014},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.693864Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:c9f8713d7cd030491cfc1a71fde442a262bda09317f7599a7ec872805bee7618","observation_id":"c600d26e-1287-48ce-8e91-da8a53749fb1","resolution":{"observed_at":"2026-08-05T12:19:12.789658Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T12:19:12.775806Z","title":"Kumar, T","venue":null,"work_id":"298f6ad2-9070-4a19-bd11-94ac74a96c5e","year":2024},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.696878Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:6c52130c87e82dd12109368f360a31a8f67d8def037fa44294ccbb0ff8e51c11","observation_id":"84efeb14-fa5f-4c16-b055-80ca266bb933","resolution":{"observed_at":"2026-08-05T12:19:12.779250Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T12:19:12.766449Z","title":"Smith, Y","venue":null,"work_id":"fb1af233-82fe-4f65-95fc-10517c5673be","year":2024},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.698885Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:a2f30de5dc543838fcb59bb46504e550f7ea054285307ce31fe8c0809ed8ecbd","observation_id":"30db338f-6d1f-4caf-b732-6159fc988cf2","resolution":{"observed_at":"2026-08-05T12:19:12.769613Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.08474","last_updated":"2024-06-13T17:38:12Z","snapshot_observed_at":"2026-08-16T19:24:28.824837Z","submitted_at":"2024-06-12T17:57:06Z","title":"Real2Code: Reconstruct Articulated Objects via Code Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.08474","snapshot_observed_at":"2026-08-05T12:19:11.701504Z","title":"Mandi, Y","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.701504Z"},"links":{"cited_paper":"/paper/2406.08474","citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:e008e301a464240ade4fd9b8a5ef423ca635cfa8c7022f35ca4387aeee719c5a","observation_id":"a5bf8812-9a38-449a-b956-737ad488b057","resolution":{"observed_at":"2026-08-05T12:19:11.701504Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.11656","last_updated":"2024-05-31T16:44:06Z","snapshot_observed_at":"2026-08-16T13:51:30.172431Z","submitted_at":"2024-05-19T20:01:29Z","title":"URDFormer: A Pipeline for Constructing Articulated Simulation Environments from Real-World Images","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.11656","snapshot_observed_at":"2026-08-05T12:19:11.703898Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.703898Z"},"links":{"cited_paper":"/paper/2405.11656","citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:06d9eb86399df58c4e2d3e2cbc1ad5b28452d9fb45638efea454cf507b82cd59","observation_id":"925b2132-05d4-4a14-b06f-103cd16c2b10","resolution":{"observed_at":"2026-08-05T12:19:11.703898Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.03949","last_updated":"2024-11-24T02:02:33Z","snapshot_observed_at":"2026-08-17T23:29:31.642440Z","submitted_at":"2024-03-06T18:55:36Z","title":"Reconciling Reality through Simulation: A Real-to-Sim-to-Real Approach for Robust Manipulation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.03949","snapshot_observed_at":"2026-08-05T12:19:11.705942Z","title":"Torne, A","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.705942Z"},"links":{"cited_paper":"/paper/2403.03949","citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:3cb443ed515450cdaee5ad43f3c28f5d7e42c13d09fceca72b19cebb3e5f19ce","observation_id":"429acebe-362e-4c3f-8fb8-4f77b6524ab6","resolution":{"observed_at":"2026-08-05T12:19:11.705942Z","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":"2026-08-05T12:19:12.755619Z","title":"Makoviychuk, L","venue":null,"work_id":"07c7daf1-fc7d-46fe-9a16-29d0197c4ac0","year":2021},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.707939Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:51e29db6b603e6497c5475250af903263fbd857f9bf128a03ac284d932cd43ce","observation_id":"3e864931-4753-4cf1-a021-95786d173852","resolution":{"observed_at":"2026-08-05T12:19:12.759569Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T12:19:11.709887Z","title":"Mittal, C","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.709887Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:a5db4135d8fb5d7b831f29d1fa4cf57425f4afbac03f14ed8ed8d3934836bcb8","observation_id":"6f96efc4-280a-4666-b60b-01e4a48cb561","resolution":{"observed_at":"2026-08-05T12:19:11.709887Z","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":"2026-08-05T12:19:12.744698Z","title":"Pavlasek, S","venue":null,"work_id":"ee9230fc-d910-43af-a858-ad4d0b3fdfea","year":null},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.711633Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:b50382eaccc3fda05b3335ded0e99800a8a664a826a097bf015f6d5685233052","observation_id":"9955d17d-85db-4858-97ca-b6a626e10e68","resolution":{"observed_at":"2026-08-05T12:19:12.748679Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T12:19:12.723840Z","title":null,"venue":null,"work_id":"836a6368-8c01-4bfc-89f7-db26248ca082","year":2023},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.715419Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:e2ea88411412acce8980c847ae73170ff5e5c11f90582a533e65a2057fc6a03e","observation_id":"94062fc2-260e-448f-b5a5-b1798fb0f060","resolution":{"observed_at":"2026-08-05T12:19:12.728180Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2202.05894","last_updated":"2022-05-06T00:50:56Z","snapshot_observed_at":"2026-08-16T17:21:53.304135Z","submitted_at":"2022-02-11T20:24:27Z","title":"Failure Prediction with Statistical Guarantees for Vision-Based Robot Control","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2202.05894","snapshot_observed_at":"2026-08-05T12:19:11.717680Z","title":"Farid, D","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.717680Z"},"links":{"cited_paper":"/paper/2202.05894","citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:a1953f7c3cc91c8c48a212e063f3b56a2cd673f71a47b126dfb74d99804972aa","observation_id":"501c236f-accf-43da-b291-a2fa34487b43","resolution":{"observed_at":"2026-08-05T12:19:11.717680Z","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":"2026-08-05T12:19:12.713123Z","title":"Inceoglu, E","venue":null,"work_id":"413297f7-97e9-49cf-8905-aea9a0096742","year":2021},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.720317Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:e4a4e6f275148a5440729b70cc98691b176f7980e42745a7c6de3310692ed44b","observation_id":"54ccc447-f7e6-4aeb-b4e8-5697c9f70352","resolution":{"observed_at":"2026-08-05T12:19:12.717645Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T12:19:12.704005Z","title":null,"venue":null,"work_id":"9d52cdee-df91-4910-8103-99837a93203b","year":2024},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.723016Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:752d02e360d42c799e828c591fc9edfc29754ff305f4020205010e45ad839844","observation_id":"d57488bb-156f-4c60-aa98-e525eb95cc8b","resolution":{"observed_at":"2026-08-05T12:19:12.707759Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T12:19:12.693037Z","title":"Sharma, N","venue":null,"work_id":"31b59379-25ef-4c56-9a0d-d43a6a396f3d","year":1958},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.725067Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:31acdf957071294a37f97e550a2eb89621e3e3dfafefe3fd4777dee7b2c68105","observation_id":"c05abadf-9982-48f0-a875-eca3ff398cee","resolution":{"observed_at":"2026-08-05T12:19:12.697932Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T12:19:12.682593Z","title":"Antonante, D","venue":null,"work_id":"ff915c9e-e86b-4997-bc3b-ac9c4167c936","year":2021},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.727865Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:07ba8319bfe5aa9e783349f3ff4dd93be0dd84ea597c852f63e18f8cda90e675","observation_id":"afab84fa-17ee-421e-8285-63e782486d38","resolution":{"observed_at":"2026-08-05T12:19:12.685678Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T12:19:12.670977Z","title":null,"venue":null,"work_id":"e0284dcc-a7bd-445b-9ca8-354962c58e63","year":2023},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.730183Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:a496fb28db4d8c79315d100d7a6a36840713f58d2789f7c8c3c117420420f188","observation_id":"bddc3ed3-6b46-40d0-acd1-84838fba8a6c","resolution":{"observed_at":"2026-08-05T12:19:12.675512Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T12:19:12.657721Z","title":"Namasivayam, A","venue":null,"work_id":"78cd2a08-b395-462a-bca7-dd91865ced57","year":2024},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.732786Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:ab5e9226d3bf66db8534447bd2a8ded7b377189287f0c834a6159d6531a5b8fd","observation_id":"3a6ab5e8-6811-4cc6-957e-e6510e9f9bf8","resolution":{"observed_at":"2026-08-05T12:19:12.662012Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.13979","last_updated":"2025-03-07T05:39:48Z","snapshot_observed_at":"2026-08-19T06:46:21.416366Z","submitted_at":"2024-10-17T19:14:43Z","title":"RecoveryChaining: Learning Local Recovery Policies for Robust Manipulation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.13979","snapshot_observed_at":"2026-08-05T12:19:11.735259Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.735259Z"},"links":{"cited_paper":"/paper/2410.13979","citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:3304f23399c85efb7b54c20c12fdc8f1397c0481cea143fc8178f20a710537ab","observation_id":"d58504be-3516-41c7-882c-a6fb4967c5fa","resolution":{"observed_at":"2026-08-05T12:19:11.735259Z","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":"2026-08-05T12:19:12.647260Z","title":"Thomason and H","venue":null,"work_id":"6aa066c0-6d22-4ddb-a516-7ba2bf0b6bb9","year":2023},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.738111Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:48a7879719567efeb203bdaacda02a5c67656aa9fe9561f51316de2739f83cbd","observation_id":"c8480e7c-e4ed-45e5-83bf-97a513e6f8df","resolution":{"observed_at":"2026-08-05T12:19:12.650987Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T12:19:11.740751Z","title":"Torne, A","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.740751Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:f6ec45b67b4dfa7bb5984ea2baa99c8c3c4f65633f62af0f7d33f80a5e0ac42d","observation_id":"9ae51457-c113-4a87-8f8f-7f9a44b59114","resolution":{"observed_at":"2026-08-05T12:19:11.740751Z","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":"2026-08-05T12:19:12.636735Z","title":null,"venue":null,"work_id":"9d9dd3a6-a049-423d-8d54-27c1dec2a9e7","year":2023},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.742571Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:f7dbf5336509c298c91dcdf8835e821ee725026f23607b80105fb25907060d97","observation_id":"71fae108-7390-49ab-8c3c-c5a8edee2ef0","resolution":{"observed_at":"2026-08-05T12:19:12.640668Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2111.04814","last_updated":"2022-06-25T18:50:54Z","snapshot_observed_at":"2026-08-16T17:43:09.156728Z","submitted_at":"2021-11-08T20:37:30Z","title":"Planar Robot Casting with Real2Sim2Real Self-Supervised Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2111.04814","snapshot_observed_at":"2026-08-05T12:19:11.744331Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.744331Z"},"links":{"cited_paper":"/paper/2111.04814","citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:dc9102051415931bd371a493583b1f593e0e6fa585acd984a0d8c7a6800153b8","observation_id":"5560af1f-93f3-4081-bacf-48f992a54fd8","resolution":{"observed_at":"2026-08-05T12:19:11.744331Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.12308","last_updated":"2024-06-27T01:22:30Z","snapshot_observed_at":"2026-08-20T05:25:23.161579Z","submitted_at":"2024-04-18T16:35:38Z","title":"ASID: Active Exploration for System Identification in Robotic Manipulation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.12308","snapshot_observed_at":"2026-08-05T12:19:11.747959Z","title":"Memmel, A","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.747959Z"},"links":{"cited_paper":"/paper/2404.12308","citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:fcd3685a28515c6c5475b9519b44a6020fb31d83eacd12788afc04cd35f543e8","observation_id":"458888ac-12ba-4ca1-bf58-32cd17e01656","resolution":{"observed_at":"2026-08-05T12:19:11.747959Z","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":"2026-08-05T12:19:11.751661Z","title":"Chebotar, A","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.751661Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:8cb728ab7a6f1b2ba3beeee495332117fc5c9737baeea4c3ac8e9aabf1d479b9","observation_id":"61e24642-368e-4682-a0f8-2d74a69a13b7","resolution":{"observed_at":"2026-08-05T12:19:11.751661Z","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":"2026-08-05T12:19:12.621085Z","title":null,"venue":null,"work_id":"07c25210-6a9f-47fd-92cf-5593cc16f12b","year":2023},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.753573Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:4485fb24241843a7f3567609429c351d80ff9b0af2549f03c9fb9fadfd18aab8","observation_id":"6151ade0-5575-4c69-8111-a290b8a533a2","resolution":{"observed_at":"2026-08-05T12:19:12.624805Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T12:19:12.611353Z","title":"Antonova, J","venue":null,"work_id":"6623f82e-12a9-46ed-ae2f-d7b06f7f449b","year":2022},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.756072Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:3e78571c29708762e6878f1adcd3dedafa353323b16bc85d5fe6109c02b2fc69","observation_id":"0f92d6db-4473-4c6c-b303-d3fbec5a5ec7","resolution":{"observed_at":"2026-08-05T12:19:12.615105Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T12:19:12.601675Z","title":null,"venue":null,"work_id":"5335344a-8577-479e-a0db-a4868122fa1f","year":2022},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.758074Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:e45acfe0618df70043d3d6d61031cd4519b8711bacf8bffb84054b10d5c8b43f","observation_id":"0aa00823-752f-4f94-988e-945de6bc6f0c","resolution":{"observed_at":"2026-08-05T12:19:12.605659Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T12:19:12.590768Z","title":"Jiang, C.-C","venue":null,"work_id":"db80bce6-470e-41bc-8d3d-b10aa2fa3396","year":2022},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.760664Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:77ab5bd2a776b2c1e9730e115ee2f453c35224415031b4e08210e72126cb543f","observation_id":"a0d261a1-1e73-400f-8d5c-2a140cbd32fd","resolution":{"observed_at":"2026-08-05T12:19:12.594635Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T12:19:12.580383Z","title":"Heiden, Z","venue":null,"work_id":"f935d625-39e2-4bfe-b93e-294dfd099496","year":2022},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.762838Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:d3897ecdcbf8d16a56226cb86a558a5e2c95fdda34abf2b378f930c7e769ba44","observation_id":"a6af9302-0c45-4f53-a3c0-bbd23de94efe","resolution":{"observed_at":"2026-08-05T12:19:12.583291Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T12:19:12.568099Z","title":null,"venue":null,"work_id":"b8c471f2-4b8f-48ba-be48-a47192960159","year":2022},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.765395Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:7fa78a7e617b76340fb8519aa7001f1c48c5096fe3cf2bc091a46ebf30d2ed34","observation_id":"294c88f3-4408-4a46-89ab-9c72e10b8f1c","resolution":{"observed_at":"2026-08-05T12:19:12.572831Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.15607/rss.2021.xvii.068","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Barcelos, A","venue":null,"work_id":"33ffa5a0-89e3-4b8b-95ce-40a635cab362","year":2021},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.767593Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:3c513feddb1fa492ef67bbfd987e0da99a29adea10343afab360a7c9173f04d4","observation_id":"e83f244d-a3f5-4774-b06b-5aca187d24b6","resolution":{"observed_at":"2026-08-05T12:19:11.889651Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.01775","last_updated":"2024-09-29T04:43:45Z","snapshot_observed_at":"2026-08-16T14:55:37.183752Z","submitted_at":"2023-10-03T03:53:51Z","title":"STAMP: Differentiable Task and Motion Planning via Stein Variational Gradient Descent","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.01775","snapshot_observed_at":"2026-08-05T12:19:11.769643Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.769643Z"},"links":{"cited_paper":"/paper/2310.01775","citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:73d34077c1a17a54efab18c195212e865d9a41e8b5b4516136293d3765c173e2","observation_id":"7bfc7fd4-9495-4b9b-9760-9f25314f25dd","resolution":{"observed_at":"2026-08-05T12:19:11.769643Z","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":"2026-08-05T12:19:12.556669Z","title":"Power and D","venue":null,"work_id":"b2a5b733-55d6-4f97-b348-19869b0e7eff","year":2024},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.772019Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:9eb9f7ab6f94e78da83f71c2da01183bbf01715f22f94782f82f3e231d79e8b3","observation_id":"f3681efd-1aa4-452e-841c-e152a922a9fa","resolution":{"observed_at":"2026-08-05T12:19:12.560847Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2107.05146","last_updated":"2021-07-11T23:39:24Z","snapshot_observed_at":"2026-08-16T18:10:47.632843Z","submitted_at":"2021-07-11T23:39:24Z","title":"Entropy Regularized Motion Planning via Stein Variational Inference","version":1},"cited_work":{"arxiv_id":"2107.05146","doi":null,"metadata_source":"pith","pith_arxiv_id":"2107.05146","snapshot_observed_at":"2026-08-05T12:19:12.172928Z","title":"Entropy Regularized Motion Planning via Stein Variational Inference","venue":"cs.RO","work_id":"84f97a0c-6d48-4c27-9afd-74644b457f01","year":2021},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.773953Z"},"links":{"cited_paper":"/paper/2107.05146","citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:307296e599a390d79a796ea637c52678cf70579d0c6dffe55956a72cb3ba2e59","observation_id":"5b6f7a7c-83e7-48a6-8058-468189e93b08","resolution":{"observed_at":"2026-08-05T12:19:12.176038Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T12:19:12.546543Z","title":"Lambert, B","venue":null,"work_id":"e491e417-1f3a-4e32-b1ae-bdfe5b93667c","year":2022},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.776224Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:a92a5b1bc4a34a5bdd36ba82f3b3ac6d7813fd7dab89b6e9321e72449ebb35fe","observation_id":"e9c3a6f6-5733-4ae9-8034-47b26977bf41","resolution":{"observed_at":"2026-08-05T12:19:12.549691Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T12:19:12.535339Z","title":"Honda, N","venue":null,"work_id":"5d10a0b0-a6c1-4b2b-b102-dc9bcca94ccb","year":2024},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.778747Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:b7477df3195c5a7ffd07c846ad88f9bbfca3de5f2204d09b4f2841014e08d138","observation_id":"63bae2b5-09fa-4d4a-a56e-9043992eb08c","resolution":{"observed_at":"2026-08-05T12:19:12.539296Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T12:19:11.781119Z","title":"Kirillov, E","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.781119Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:d3d72a5f94eff27ba0f9d35ff911a6da4472515c0e83d2a7ee468003abc764a4","observation_id":"4cb4d082-dda4-4165-bb61-0f9188abd6d2","resolution":{"observed_at":"2026-08-05T12:19:11.781119Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.05499","last_updated":"2024-07-19T06:00:41Z","snapshot_observed_at":"2026-08-19T16:02:58.628969Z","submitted_at":"2023-03-09T18:52:16Z","title":"Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.05499","snapshot_observed_at":"2026-08-05T12:19:11.783210Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.783210Z"},"links":{"cited_paper":"/paper/2303.05499","citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:8ef5125e6c50a745ce04a926bc312ad5d61f5de06930409d1cf8720d652985c7","observation_id":"4eb1f346-9f4e-40df-8998-e60ff08961d9","resolution":{"observed_at":"2026-08-05T12:19:11.783210Z","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":"2026-08-05T12:19:12.518093Z","title":null,"venue":null,"work_id":"8a122cfb-5430-4d95-b3bd-d5b4374a55d7","year":2023},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.786736Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:e6210ca9aa0050a2721405de98c4ebaff4a8a2046ac70e83d793dd139b69aca7","observation_id":"ab8a7ce4-4df0-47ba-b555-1b6de1bad7f2","resolution":{"observed_at":"2026-08-05T12:19:12.520877Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.10857","last_updated":"2024-01-28T05:39:29Z","snapshot_observed_at":"2026-08-18T20:57:00.151672Z","submitted_at":"2023-05-18T10:19:57Z","title":"Latent Space Planning for Multi-Object Manipulation with Environment-Aware Relational Classifiers","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.10857","snapshot_observed_at":"2026-08-05T12:19:11.788904Z","title":"Huang, N","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.788904Z"},"links":{"cited_paper":"/paper/2305.10857","citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:09c0f7c4c9423d4c12055a0b5bcfa3eb7145887db6a09b9060b63cb72b0890ba","observation_id":"a44e92d8-ef49-493b-ab83-d7ee127b5a02","resolution":{"observed_at":"2026-08-05T12:19:11.788904Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2010.01083","last_updated":"2020-10-02T16:23:08Z","snapshot_observed_at":"2026-08-19T19:21:38.391205Z","submitted_at":"2020-10-02T16:23:08Z","title":"Integrated Task and Motion Planning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.01083","snapshot_observed_at":"2026-08-05T12:19:11.791500Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.791500Z"},"links":{"cited_paper":"/paper/2010.01083","citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:1dbf50c96d1aade6ca36b9d4196e14e708a9b8ceff3bcd15ae790468343a8311","observation_id":"966931a4-60f3-4366-9989-4d373a81aef8","resolution":{"observed_at":"2026-08-05T12:19:11.791500Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2209.11943","last_updated":"2023-03-16T21:37:23Z","snapshot_observed_at":"2026-08-16T16:30:12.300018Z","submitted_at":"2022-09-24T07:14:32Z","title":"Planning for Multi-Object Manipulation with Graph Neural Network Relational Classifiers","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2209.11943","snapshot_observed_at":"2026-08-05T12:19:11.794374Z","title":"Huang, A","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.794374Z"},"links":{"cited_paper":"/paper/2209.11943","citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:9c5a4f55042ea45bfa72c846b56f8ed77b1b2e266ee25f2f5a7dcaad46bb5c8a","observation_id":"43ca583c-36f2-4d4f-ba6b-55a4931ce66e","resolution":{"observed_at":"2026-08-05T12:19:11.794374Z","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":"2026-08-05T12:19:12.510811Z","title":"Huang, J","venue":null,"work_id":"2dbf1b4d-bf94-491e-98a7-9473639e8361","year":2024},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.796800Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:7967e50bc3214d677713aac14508cfb6c2f7b29ff4e3299ae18869c527084b47","observation_id":"c77dcc31-9ee5-499e-ae6e-e3f3cee6902d","resolution":{"observed_at":"2026-08-05T12:19:12.513115Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T12:19:12.504015Z","title":null,"venue":null,"work_id":"206d4732-9768-4194-b32e-f71b8dac5ede","year":2012},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.798841Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:87bd68ca863003b282cc149c32a9c34c16eaf12cb134fd3fbe758f5a4d16ce15","observation_id":"941260e7-d8e8-4421-b2fb-7abc5b22d820","resolution":{"observed_at":"2026-08-05T12:19:12.506402Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1907.00277","last_updated":"2022-05-04T17:30:23Z","snapshot_observed_at":"2026-08-15T13:56:13.006382Z","submitted_at":"2019-06-29T21:01:57Z","title":"Active Learning of Probabilistic Movement Primitives","version":2},"cited_work":{"arxiv_id":"1907.00277","doi":null,"metadata_source":"pith","pith_arxiv_id":"1907.00277","snapshot_observed_at":"2026-08-05T12:19:12.130005Z","title":"Active Learning of Probabilistic Movement Primitives","venue":"cs.RO","work_id":"626086f4-71e8-4896-8601-24a8f6aa66b5","year":2019},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.800784Z"},"links":{"cited_paper":"/paper/1907.00277","citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:d252ecc8ba364121408792bbfd8995d48f864feb5ac85b7ef7cf896fe45f130c","observation_id":"7dfe5c21-3f87-4090-a282-68c3b5e82b29","resolution":{"observed_at":"2026-08-05T12:19:12.132822Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2006.05264","last_updated":"2020-08-01T20:11:27Z","snapshot_observed_at":"2026-07-06T09:27:21.949573Z","submitted_at":"2020-06-06T05:56:45Z","title":"Multi-Fingered Active Grasp Learning","version":2},"cited_work":{"arxiv_id":"2006.05264","doi":null,"metadata_source":"pith","pith_arxiv_id":"2006.05264","snapshot_observed_at":"2026-08-05T12:19:12.119602Z","title":"Multi-Fingered Active Grasp Learning","venue":"cs.RO","work_id":"04860bd1-abcf-420d-b25f-5a24e6fa73a0","year":2020},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.803471Z"},"links":{"cited_paper":"/paper/2006.05264","citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:cedb4e883a69674284b65d82badc24ea621d270243157785c3382efa17deece2","observation_id":"d5518a19-3b1a-416f-a4a3-bf86a46b3623","resolution":{"observed_at":"2026-08-05T12:19:12.122500Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T12:19:12.497745Z","title":"H¨ullermeier and W","venue":null,"work_id":"bdd591df-1501-4a8b-9a2a-84e32b364c7b","year":2021},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.805894Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:68315e51fd1759f3d319bbbcdc2cbd57b0b81bd14ecb6c1e75ea8f67d96a20f7","observation_id":"a59428fa-aae6-48e4-8d07-4153f896ad80","resolution":{"observed_at":"2026-08-05T12:19:12.500011Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T12:19:12.490685Z","title":"Kendall and Y","venue":null,"work_id":"2a91650a-a530-4489-9375-8fe95e40078f","year":2017},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.807876Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:0be7f56b70dfd6ce5a8539b7bb9127ce3cafa6c1b729238091d7770007265903","observation_id":"54b225dc-7986-4855-b1c6-374394c83469","resolution":{"observed_at":"2026-08-05T12:19:12.492978Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T12:19:12.482509Z","title":"Matsubara, J","venue":null,"work_id":"01906fd9-4287-4214-aaaa-9eceb0447577","year":2022},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.809762Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:53729583feb96393f26e72c6ecfe26defccbbb87ed0224865fa4eb4a5c25c7bd","observation_id":"5864d55c-3573-4e90-88f4-4ef51e2f440d","resolution":{"observed_at":"2026-08-05T12:19:12.485573Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T12:19:11.811722Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.811722Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:e186a57447e721c5739c1f80cc4eee29b114e700d92d94d635a034dcb259b84f","observation_id":"a86ab84b-6de1-4485-a60d-0ded5500443d","resolution":{"observed_at":"2026-08-05T12:19:11.811722Z","resolver_source":null,"status":"malformed_identifier"},"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":"2026-08-05T12:19:12.473125Z","title":"Liu and D","venue":null,"work_id":"e950bb14-05d5-49ef-99ca-2d9f5b7fc0db","year":2016},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.813871Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:8fcc045f397d229bf0eae8aef2606a6d3a7a324a77e680a2820c3c3575c02c51","observation_id":"10aaa173-8a8f-4f52-9a3c-3e6baafa682b","resolution":{"observed_at":"2026-08-05T12:19:12.476526Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1707.07269","last_updated":"2018-10-30T09:48:51Z","snapshot_observed_at":"2026-08-17T07:21:17.547491Z","submitted_at":"2017-07-23T09:32:55Z","title":"Large sample analysis of the median heuristic","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1707.07269","snapshot_observed_at":"2026-08-05T12:19:11.815972Z","title":"Garreau, W","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.815972Z"},"links":{"cited_paper":"/paper/1707.07269","citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:bab1df115da2c104fca4dff40dfc8d9b58778f34f69e9e44c5ad28f72e0046e5","observation_id":"51b8a049-6b25-4a55-89ff-89fa6e31e142","resolution":{"observed_at":"2026-08-05T12:19:11.815972Z","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":"2026-08-05T12:19:12.464655Z","title":null,"venue":null,"work_id":"700f41bd-5bc5-40d0-b70b-853fbc187e13","year":1992},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.818146Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:39f777a9d7517c27dcdcdf6d187aaab11d7dbabac97f404ed2af39fd0090d0be","observation_id":"f8bef437-2c74-4d6e-b4a1-95742c6ebf1c","resolution":{"observed_at":"2026-08-05T12:19:12.467904Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2306.15724","last_updated":"2023-10-16T21:04:57Z","snapshot_observed_at":"2026-08-21T18:34:11.182539Z","submitted_at":"2023-06-27T18:03:15Z","title":"REFLECT: Summarizing Robot Experiences for Failure Explanation and Correction","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.15724","snapshot_observed_at":"2026-08-05T12:19:11.821016Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.821016Z"},"links":{"cited_paper":"/paper/2306.15724","citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:89093b385fb5d8159e6cf5905d2efd7b62a2777a09e3b1498c70ff957327a81f","observation_id":"fc1f939e-4f0b-45df-8303-9dd2b79d6cf5","resolution":{"observed_at":"2026-08-05T12:19:11.821016Z","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":"2026-08-05T12:19:11.823819Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.823819Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:de31ad57c323c20282d616b4068b6f3d77a0958a18e7d6fd37c8e05b481b5d1f","observation_id":"6fbae597-14c9-4acb-8d8e-857fece49feb","resolution":{"observed_at":"2026-08-05T12:19:11.823819Z","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":"2026-08-05T12:19:12.456167Z","title":"Ahmetoglu, B","venue":null,"work_id":"f115ab66-4568-450e-94fd-1d2200d724f8","year":2024},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.826358Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:d95b18994d8093971a2b59e3ba7e9c728bf2733dbe0b0d24589d0a1537dd52a1","observation_id":"04b42af3-2c2d-4f44-aeb0-167d38231c1d","resolution":{"observed_at":"2026-08-05T12:19:12.459346Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.06237","last_updated":"2024-10-08T17:52:29Z","snapshot_observed_at":"2026-08-18T09:19:45.451184Z","submitted_at":"2024-10-08T17:52:29Z","title":"BUMBLE: Unifying Reasoning and Acting with Vision-Language Models for Building-wide Mobile Manipulation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.06237","snapshot_observed_at":"2026-08-05T12:19:11.828565Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.828565Z"},"links":{"cited_paper":"/paper/2410.06237","citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:b69e3ebb2f271755a823d2b78a0b31645ce76a6e94aa0ac3d470a8a8f5936cdb","observation_id":"a019563c-784b-42e2-a768-e1fddf7d1995","resolution":{"observed_at":"2026-08-05T12:19:11.828565Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.04999","last_updated":"2025-05-29T13:57:04Z","snapshot_observed_at":"2026-08-20T21:31:47.153163Z","submitted_at":"2024-11-07T18:59:27Z","title":"DynaMem: Online Dynamic Spatio-Semantic Memory for Open World Mobile Manipulation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.04999","snapshot_observed_at":"2026-08-05T12:19:11.831521Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.831521Z"},"links":{"cited_paper":"/paper/2411.04999","citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:39e343632eaa2292ce3fc6905fda6d115576ffab0e177a52b8b9225a58d1d45c","observation_id":"75f0a5bc-7bf6-47ec-8269-9fbafa2a22e7","resolution":{"observed_at":"2026-08-05T12:19:11.831521Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.04279","last_updated":"2025-01-08T05:01:59Z","snapshot_observed_at":"2026-08-15T07:08:43.316048Z","submitted_at":"2025-01-08T05:01:59Z","title":"OpenIN: Open-Vocabulary Instance-Oriented Navigation in Dynamic Domestic Environments","version":1},"cited_work":{"arxiv_id":"2501.04279","doi":null,"metadata_source":"pith","pith_arxiv_id":"2501.04279","snapshot_observed_at":"2026-08-05T12:19:11.938587Z","title":"OpenIN: Open-Vocabulary Instance-Oriented Navigation in Dynamic Domestic Environments","venue":"cs.RO","work_id":"e4d72ca5-d0e3-4df9-9ecd-3e4729231cba","year":2025},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.833733Z"},"links":{"cited_paper":"/paper/2501.04279","citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:2e650b08027cbb5c8d0669a395c11c3fd4d4a782a5fab16dc2f62b20a93ff4ad","observation_id":"b16c99b5-c0c3-49f7-a080-f34346764f3a","resolution":{"observed_at":"2026-08-05T12:19:11.941522Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T12:19:12.449721Z","title":null,"venue":null,"work_id":"7de65b39-8102-4f52-84ee-94be35f34c14","year":2023},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.835986Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:0cd2456de82b75b2e7d2883d8d33ac5278762adf169deed5e9c9e0cd5a1f9b3f","observation_id":"20f1cdca-19cd-447d-90ee-9c1a2e65ac29","resolution":{"observed_at":"2026-08-05T12:19:12.451916Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T12:19:12.443178Z","title":null,"venue":null,"work_id":"21b2d935-ca81-4d2a-8a53-5a2ad27ec7cd","year":2022},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.839708Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:348bb4f2fd692f21235facbe9c6e61363ab63264adf819f14a77ddda2dd2a383","observation_id":"b3ecb00b-bc42-4fd5-91e7-59f6b74976af","resolution":{"observed_at":"2026-08-05T12:19:12.445444Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1802.08705","last_updated":"2020-03-23T15:14:02Z","snapshot_observed_at":"2026-08-14T19:42:44.709891Z","submitted_at":"2018-02-23T19:26:46Z","title":"PDDLStream: Integrating Symbolic Planners and Blackbox Samplers via Optimistic Adaptive Planning","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1802.08705","snapshot_observed_at":"2026-08-05T12:19:11.841958Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.841958Z"},"links":{"cited_paper":"/paper/1802.08705","citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:3234ba6b811656121b8dc9a701b5e0816061505a95745761840d8d0c68b0ec55","observation_id":"33af0277-f2e7-4c12-b47d-23b787ab02e7","resolution":{"observed_at":"2026-08-05T12:19:11.841958Z","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":"2026-08-05T12:19:12.434036Z","title":null,"venue":null,"work_id":"04a73fb0-eb69-4da2-a0f4-2481de5f5f7d","year":2017},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.844237Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:9142e7f1d6d9f4dfaecd69ae46793a2be2645765feebeb4eb3ab89b01c3b085c","observation_id":"d19a02ad-771f-4860-a1d4-fba3adb112c1","resolution":{"observed_at":"2026-08-05T12:19:12.436497Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1807.09962","last_updated":"2018-07-26T05:35:18Z","snapshot_observed_at":"2026-08-14T18:47:37.172267Z","submitted_at":"2018-07-26T05:35:18Z","title":"Learning to guide task and motion planning using score-space representation","version":1},"cited_work":{"arxiv_id":"1807.09962","doi":null,"metadata_source":"pith","pith_arxiv_id":"1807.09962","snapshot_observed_at":"2026-08-05T12:19:11.921513Z","title":"Learning to guide task and motion planning using score-space representation","venue":"cs.RO","work_id":"1d9da482-6401-4401-a880-1d9b78831d38","year":2018},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.846440Z"},"links":{"cited_paper":"/paper/1807.09962","citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:2e61d25899d57aa761b2d7169daf18a39ba34e07c6dabe14394f3e6f246013d2","observation_id":"83db4f81-c7e9-44d2-8450-d4afcc4642f8","resolution":{"observed_at":"2026-08-05T12:19:11.924840Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T12:19:12.426589Z","title":"Curtis, X","venue":null,"work_id":"ee539f70-788b-4a93-b099-58cf179a86f1","year":1940},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.848554Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:8c1e0636ecfdf5c2fdecf5aa07ad04c618c402d951de5526dd886fb4cc02da65","observation_id":"83a66142-1b12-457d-a5a4-812d26fb8361","resolution":{"observed_at":"2026-08-05T12:19:12.428878Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2006.05398","last_updated":"2020-06-09T16:52:02Z","snapshot_observed_at":"2026-08-19T07:54:06.600745Z","submitted_at":"2020-06-09T16:52:02Z","title":"Deep Visual Reasoning: Learning to Predict Action Sequences for Task and Motion Planning from an Initial Scene Image","version":1},"cited_work":{"arxiv_id":"2006.05398","doi":null,"metadata_source":"pith","pith_arxiv_id":"2006.05398","snapshot_observed_at":"2026-08-05T12:19:11.909883Z","title":"Deep Visual Reasoning: Learning to Predict Action Sequences for Task and Motion Planning from an Initial Scene Image","venue":"cs.LG","work_id":"a9b8ee16-a259-4a1e-8bea-944ece4969d3","year":2020},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":76,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.850518Z"},"links":{"cited_paper":"/paper/2006.05398","citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:15a605c97adb47cd0471447e982015f6f2bbfd4d052d207fa0461cf21b4d368b","observation_id":"e99418b5-c63c-4aa5-b2db-bd48a9e72bcf","resolution":{"observed_at":"2026-08-05T12:19:11.913915Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T12:19:12.419599Z","title":null,"venue":null,"work_id":"fbc8a1fc-f03d-494a-934d-03a9350c58ce","year":2023},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.853183Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:f84646e2789046ee7b46d412c45d5762ec5ca54acc028f2319d815f0aa14144e","observation_id":"d0cfe149-1fd1-4771-aae9-5edb8bf66c9a","resolution":{"observed_at":"2026-08-05T12:19:12.421814Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-05T12:19:12.411680Z","title":"Cheng and D","venue":null,"work_id":"727fd6f9-9366-40c9-bb77-8611da284310","year":2023},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":78,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.856007Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:8f42c825ea43c8873549e92c8f53ace141e1d1bb132dc0b85f477a1ea7b8ecba","observation_id":"8dee8a68-cef1-4c8b-8cb6-e67c5b09fd8b","resolution":{"observed_at":"2026-08-05T12:19:12.413844Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1811.07246","last_updated":"2020-11-09T21:20:22Z","snapshot_observed_at":"2026-08-21T10:05:34.114940Z","submitted_at":"2018-11-17T23:42:13Z","title":"PointConv: Deep Convolutional Networks on 3D Point Clouds","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1811.07246","snapshot_observed_at":"2026-08-05T12:19:11.858142Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":79,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.858142Z"},"links":{"cited_paper":"/paper/1811.07246","citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:ec3948b0859044b79b93f8d19a5e4dae651a7e3504c735bfef6bde9ae1583613","observation_id":"a81b9cb1-6aa6-445e-bf34-0de55ae360aa","resolution":{"observed_at":"2026-08-05T12:19:11.858142Z","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":"2026-08-05T12:19:12.404166Z","title":"Paszke, S","venue":null,"work_id":"128e3f74-3860-41bc-86be-ddba86137828","year":2019},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":80,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.860507Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:e5431408d8c998f62ef490cb0a064659343bb1b41e5b6c86cc00f8c84474f75f","observation_id":"3e84c25c-cd16-41a9-8419-cefb54328ee4","resolution":{"observed_at":"2026-08-05T12:19:12.407077Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1412.6980","last_updated":"2017-01-30T01:27:54Z","snapshot_observed_at":"2026-08-17T19:26:44.032537Z","submitted_at":"2014-12-22T13:54:29Z","title":"Adam: A Method for Stochastic Optimization","version":9},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.6980","snapshot_observed_at":"2026-08-05T12:19:11.863120Z","title":null,"venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":81,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.863120Z"},"links":{"cited_paper":"/paper/1412.6980","citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:81cb5b854422f45f03a16968b0b4040aa4c7df1b65f2555200182638f79c92ef","observation_id":"8ecf8c9f-dce4-4249-85b2-f09aa71dad84","resolution":{"observed_at":"2026-08-05T12:19:11.863120Z","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":"2026-08-05T12:19:12.734328Z","title":null,"venue":null,"work_id":"d4a779ae-a108-46db-8319-8726f7928a8b","year":null},"citing_paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-05T12:19:11.713525Z"},"links":{"citing_paper":"/paper/2509.01746"},"observation_digest":"sha256:cb0778896e14be11a5ac14ea250709b574f619b2b18d6c9a959b720ce7fddf2a","observation_id":"b6abb1b9-b1bb-4a24-8609-3d2fec9a1b13","resolution":{"observed_at":"2026-08-05T12:19:12.738395Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2509.01746","last_updated":"2025-09-01T20:00:56Z","latest_version":1,"primary_category":"cs.RO","snapshot_observed_at":"2026-08-19T07:24:48.060103Z","submitted_at":"2025-09-01T20:00:56Z","title":"Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference"},"reference_resolution":{"displayed":82,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":48,"verified_exact":8,"verified_fuzzy":25},"total_outbound_references":82},"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":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"thesis":"As of 22 August 2026, this Paper Citation Record lists 82 of 82 outbound references and 4 inbound Pith citation observations for arXiv:2509.01746."}