{"as_of":"2026-08-14T12:31:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f4eac16748f161024999c58debded0133af5ea0a625433e448abce72b04c1931","coverage":[{"denominator":35,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":35,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T21:58:43.087788Z","state":"measured"},{"denominator":35,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":35,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-14T06:32:32.682623+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2412.03949/citation-record","integrity":"/paper/2412.03949/integrity","json":"/paper/2412.03949/citation-record.json","paper":"/paper/2412.03949"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T21:58:44.212769Z","title":"Mobility and aging: new directions for public health action,","venue":null,"work_id":"af2f5a2f-9252-42cc-b151-7bed9a806c8c","year":2012},"citing_paper":{"arxiv_id":"2412.03949","last_updated":"2024-12-05T07:55:58Z","snapshot_observed_at":"2026-08-12T13:14:03.152327Z","submitted_at":"2024-12-05T07:55:58Z","title":"Learning Speed-Adaptive Walking Agent Using Imitation Learning with Physics-Informed Simulation","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-11T21:58:42.761197Z"},"links":{"citing_paper":"/paper/2412.03949"},"observation_digest":"sha256:f6fb011d714ffb6151879de2317ec339f7030433b2ccad03e41030a0f377a513","observation_id":"5be22698-b7c1-44f9-a128-803abd740529","resolution":{"observed_at":"2026-08-11T21:58:44.314974Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-11T21:58:43.987676Z","title":"Mobility in older adults: a comprehensive framework,","venue":null,"work_id":"96c6cd97-9361-4eb2-be56-529ae7c4533b","year":2010},"citing_paper":{"arxiv_id":"2412.03949","last_updated":"2024-12-05T07:55:58Z","snapshot_observed_at":"2026-08-12T13:14:03.152327Z","submitted_at":"2024-12-05T07:55:58Z","title":"Learning Speed-Adaptive Walking Agent Using Imitation Learning with Physics-Informed Simulation","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-11T21:58:42.764667Z"},"links":{"citing_paper":"/paper/2412.03949"},"observation_digest":"sha256:a869471ffa1a15d3563d25aa712d4eb5bc2a0d833a234b1a75cbe4b9364712ce","observation_id":"c4e3b015-bb8c-41a5-9bb0-89ecb2f2c40e","resolution":{"observed_at":"2026-08-11T21:58:44.094407Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-11T21:58:43.926658Z","title":"Disability and health data system (dhds),","venue":null,"work_id":"388918de-6dd0-4134-9c70-b3b1622e56fe","year":2024},"citing_paper":{"arxiv_id":"2412.03949","last_updated":"2024-12-05T07:55:58Z","snapshot_observed_at":"2026-08-12T13:14:03.152327Z","submitted_at":"2024-12-05T07:55:58Z","title":"Learning Speed-Adaptive Walking Agent Using Imitation Learning with Physics-Informed Simulation","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-11T21:58:42.767544Z"},"links":{"citing_paper":"/paper/2412.03949"},"observation_digest":"sha256:8160e93c2305a0358c263373f2d2e2b019cc06f3a201f5d19a7a360a8fb02d9c","observation_id":"fb6aa39a-4992-4f7c-8b29-ca866b9e68de","resolution":{"observed_at":"2026-08-11T21:58:43.929773Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-11T21:58:43.919131Z","title":"Mobility difficulties are not only a problem of old age,","venue":null,"work_id":"803e9dbb-8c1a-46ba-a003-ba0b13828791","year":2001},"citing_paper":{"arxiv_id":"2412.03949","last_updated":"2024-12-05T07:55:58Z","snapshot_observed_at":"2026-08-12T13:14:03.152327Z","submitted_at":"2024-12-05T07:55:58Z","title":"Learning Speed-Adaptive Walking Agent Using Imitation Learning with Physics-Informed Simulation","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-11T21:58:42.770536Z"},"links":{"citing_paper":"/paper/2412.03949"},"observation_digest":"sha256:d7b43517c52153490fc3288af93b1debe9dfe7ba17c1d81edd81afad9c6e29b0","observation_id":"a1be4222-a0c6-4597-88f0-752b7ca97ea9","resolution":{"observed_at":"2026-08-11T21:58:43.921808Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-11T21:58:43.911893Z","title":"Gait analysis methods in rehabilitation,","venue":null,"work_id":"23976342-849d-44c2-81be-e48f7f8a1604","year":2006},"citing_paper":{"arxiv_id":"2412.03949","last_updated":"2024-12-05T07:55:58Z","snapshot_observed_at":"2026-08-12T13:14:03.152327Z","submitted_at":"2024-12-05T07:55:58Z","title":"Learning Speed-Adaptive Walking Agent Using Imitation Learning with Physics-Informed Simulation","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-11T21:58:42.774644Z"},"links":{"citing_paper":"/paper/2412.03949"},"observation_digest":"sha256:eb21c84dae84f1a4125c01f7168476cf4e1b5337b9b9b161e97f56b61dea9125","observation_id":"0b4a283d-4308-4caf-b3d1-0059f2ac1229","resolution":{"observed_at":"2026-08-11T21:58:43.914678Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-11T21:58:43.904523Z","title":"Opensim: open-source soft- ware to create and analyze dynamic simulations of movement,","venue":null,"work_id":"b3898561-be75-4b2c-b7c5-9f3a12db495d","year":1940},"citing_paper":{"arxiv_id":"2412.03949","last_updated":"2024-12-05T07:55:58Z","snapshot_observed_at":"2026-08-12T13:14:03.152327Z","submitted_at":"2024-12-05T07:55:58Z","title":"Learning Speed-Adaptive Walking Agent Using Imitation Learning with Physics-Informed Simulation","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-11T21:58:42.777644Z"},"links":{"citing_paper":"/paper/2412.03949"},"observation_digest":"sha256:8509a95eaac6cc66f21ebc7099977eba5cf60675c86fe35d8959b19ff78813d6","observation_id":"829a3945-2c69-44df-9c2d-8d321c0b291e","resolution":{"observed_at":"2026-08-11T21:58:43.907661Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-11T21:58:43.896065Z","title":"A survey on digital twin: Definitions, characteristics, applications, and design implications,","venue":null,"work_id":"f38d0748-c72c-48db-bfd6-a00b5cbb11b4","year":2019},"citing_paper":{"arxiv_id":"2412.03949","last_updated":"2024-12-05T07:55:58Z","snapshot_observed_at":"2026-08-12T13:14:03.152327Z","submitted_at":"2024-12-05T07:55:58Z","title":"Learning Speed-Adaptive Walking Agent Using Imitation Learning with Physics-Informed Simulation","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-11T21:58:42.780208Z"},"links":{"citing_paper":"/paper/2412.03949"},"observation_digest":"sha256:efd299bbb062bde18e20c3a0d05970c900145252e8fc7376505243e1d6d4eb98","observation_id":"a882ca11-36e9-4b59-a70c-8afee1f6536e","resolution":{"observed_at":"2026-08-11T21:58:43.898960Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-11T21:58:43.888863Z","title":"An interactive graphics-based model of the lower extremity to study orthopaedic surgical procedures,","venue":null,"work_id":"5d5c2ba6-eac9-4b9b-a788-385be9fc9fc1","year":1990},"citing_paper":{"arxiv_id":"2412.03949","last_updated":"2024-12-05T07:55:58Z","snapshot_observed_at":"2026-08-12T13:14:03.152327Z","submitted_at":"2024-12-05T07:55:58Z","title":"Learning Speed-Adaptive Walking Agent Using Imitation Learning with Physics-Informed Simulation","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-11T21:58:42.782818Z"},"links":{"citing_paper":"/paper/2412.03949"},"observation_digest":"sha256:aa314f38a95769bfebac2713c409b5c75511fb999ad18e04acc75e90c5740056","observation_id":"56ea7f4b-5887-464d-8692-b9ac07b6799a","resolution":{"observed_at":"2026-08-11T21:58:43.891906Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-11T21:58:43.880028Z","title":"Predicting gait adaptations due to ankle plantarflexor muscle weakness and contracture using physics-based musculoskeletal simulations,","venue":null,"work_id":"a4a98d18-924a-4391-9660-a2d04c821e7e","year":2019},"citing_paper":{"arxiv_id":"2412.03949","last_updated":"2024-12-05T07:55:58Z","snapshot_observed_at":"2026-08-12T13:14:03.152327Z","submitted_at":"2024-12-05T07:55:58Z","title":"Learning Speed-Adaptive Walking Agent Using Imitation Learning with Physics-Informed Simulation","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-11T21:58:42.799977Z"},"links":{"citing_paper":"/paper/2412.03949"},"observation_digest":"sha256:a2670d0d2c4fdcf2bd3b55e48e786325173872eaf52129a24bf5738cb6c64741","observation_id":"c8aca824-8656-4ba8-b071-7851807840ab","resolution":{"observed_at":"2026-08-11T21:58:43.883649Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-11T21:58:43.871788Z","title":"Optimal control based stiffness identification of an ankle-foot orthosis using a predictive walking model,","venue":null,"work_id":"dce49b61-b153-41c9-bc38-ea545ddfe1c9","year":2017},"citing_paper":{"arxiv_id":"2412.03949","last_updated":"2024-12-05T07:55:58Z","snapshot_observed_at":"2026-08-12T13:14:03.152327Z","submitted_at":"2024-12-05T07:55:58Z","title":"Learning Speed-Adaptive Walking Agent Using Imitation Learning with Physics-Informed Simulation","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-11T21:58:42.831398Z"},"links":{"citing_paper":"/paper/2412.03949"},"observation_digest":"sha256:06deb0d18a16649a78aaafca7e6d9a8a7032d3ca8c0ed2fdddd6a429cc80fd90","observation_id":"d50a7059-a77f-4a65-b731-9da430e9b253","resolution":{"observed_at":"2026-08-11T21:58:43.874440Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-11T21:58:43.863768Z","title":"Learning a control policy for fall prevention on an assistive walking device,","venue":null,"work_id":"3c3dfcb4-7fa6-4db9-94a9-823f35c0c0aa","year":2020},"citing_paper":{"arxiv_id":"2412.03949","last_updated":"2024-12-05T07:55:58Z","snapshot_observed_at":"2026-08-12T13:14:03.152327Z","submitted_at":"2024-12-05T07:55:58Z","title":"Learning Speed-Adaptive Walking Agent Using Imitation Learning with Physics-Informed Simulation","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-11T21:58:42.873395Z"},"links":{"citing_paper":"/paper/2412.03949"},"observation_digest":"sha256:6ecc57e13006170602a3b2ee35b5641942700e6ce6d5101fc4df70095561b1ce","observation_id":"b323f139-b825-4e32-bc20-9f651d888ec3","resolution":{"observed_at":"2026-08-11T21:58:43.866838Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-11T21:58:43.723747Z","title":"A lightweight robotic leg prosthesis replicating the biomechanics of the knee, ankle, and toe joint,","venue":null,"work_id":"5248c8e6-73a8-413d-ba6c-ee9f577cb05d","year":2022},"citing_paper":{"arxiv_id":"2412.03949","last_updated":"2024-12-05T07:55:58Z","snapshot_observed_at":"2026-08-12T13:14:03.152327Z","submitted_at":"2024-12-05T07:55:58Z","title":"Learning Speed-Adaptive Walking Agent Using Imitation Learning with Physics-Informed Simulation","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-11T21:58:42.904507Z"},"links":{"citing_paper":"/paper/2412.03949"},"observation_digest":"sha256:69355033836b9a85853408da782f7c0bdf02495cc0e66a68f7893693b66a40aa","observation_id":"a008236f-b510-4492-b977-52d711c6ba92","resolution":{"observed_at":"2026-08-11T21:58:43.819684Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-11T21:58:43.526742Z","title":"The effect of hip assistance levels on human energetic cost using robotic hip exoskeletons,","venue":null,"work_id":"5045b833-d5ad-4a3d-818e-e4e22f515f6f","year":2019},"citing_paper":{"arxiv_id":"2412.03949","last_updated":"2024-12-05T07:55:58Z","snapshot_observed_at":"2026-08-12T13:14:03.152327Z","submitted_at":"2024-12-05T07:55:58Z","title":"Learning Speed-Adaptive Walking Agent Using Imitation Learning with Physics-Informed Simulation","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-11T21:58:42.924202Z"},"links":{"citing_paper":"/paper/2412.03949"},"observation_digest":"sha256:ff98a08aa2c61e537207c5df9f6f328806c6fd32e57ddfb3a4e31e1ffe16b0c6","observation_id":"bd1692d4-7dad-44db-a4d7-9933b3607c7b","resolution":{"observed_at":"2026-08-11T21:58:43.637385Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-11T21:58:43.496917Z","title":"Crossing the reality gap: A survey on sim-to-real transferability of robot controllers in reinforcement learning,","venue":null,"work_id":"1448ef81-f4db-44f6-b857-d5070c170b10","year":2021},"citing_paper":{"arxiv_id":"2412.03949","last_updated":"2024-12-05T07:55:58Z","snapshot_observed_at":"2026-08-12T13:14:03.152327Z","submitted_at":"2024-12-05T07:55:58Z","title":"Learning Speed-Adaptive Walking Agent Using Imitation Learning with Physics-Informed Simulation","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-11T21:58:42.966636Z"},"links":{"citing_paper":"/paper/2412.03949"},"observation_digest":"sha256:7cd9d156e9e67cbd8e569f602ffb0bf25f162c4f2bce08b3c219931ae8e122f8","observation_id":"518bd505-e358-43dd-b2f3-a25d8d7cd62e","resolution":{"observed_at":"2026-08-11T21:58:43.500254Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-11T21:58:43.488737Z","title":"Exploring the sim2real gap using digital twins,","venue":null,"work_id":"4f89002d-27be-40cf-b8a6-5d975d9b3867","year":2023},"citing_paper":{"arxiv_id":"2412.03949","last_updated":"2024-12-05T07:55:58Z","snapshot_observed_at":"2026-08-12T13:14:03.152327Z","submitted_at":"2024-12-05T07:55:58Z","title":"Learning Speed-Adaptive Walking Agent Using Imitation Learning with Physics-Informed Simulation","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-11T21:58:42.998425Z"},"links":{"citing_paper":"/paper/2412.03949"},"observation_digest":"sha256:53b7a4e70feac6421a612bc0a5de96f68aa822cd2ed1148612fa228d11ea1de4","observation_id":"f76e6698-78ef-4603-b149-8b2bdbe4bddf","resolution":{"observed_at":"2026-08-11T21:58:43.491784Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-11T21:58:43.480356Z","title":"Analysis of musculoskeletal systems in the anybody modeling system,","venue":null,"work_id":"61bb0946-b689-4646-bc47-bbb11603b50f","year":2006},"citing_paper":{"arxiv_id":"2412.03949","last_updated":"2024-12-05T07:55:58Z","snapshot_observed_at":"2026-08-12T13:14:03.152327Z","submitted_at":"2024-12-05T07:55:58Z","title":"Learning Speed-Adaptive Walking Agent Using Imitation Learning with Physics-Informed Simulation","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-11T21:58:43.036407Z"},"links":{"citing_paper":"/paper/2412.03949"},"observation_digest":"sha256:c9c9f6561e17930d9f958a005038bfd6200ba9ab7fb7b1827205aa9a0f25a4fb","observation_id":"d79df9fd-6b02-4d6e-b709-6540b22720ac","resolution":{"observed_at":"2026-08-11T21:58:43.483637Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2205.13600","last_updated":"2022-05-26T20:11:23Z","snapshot_observed_at":"2026-08-13T15:35:45.688247Z","submitted_at":"2022-05-26T20:11:23Z","title":"MyoSuite -- A contact-rich simulation suite for musculoskeletal motor control","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2205.13600","snapshot_observed_at":"2026-08-11T21:58:43.039061Z","title":"Myosuite–a contact-rich simulation suite for musculoskeletal motor control,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.03949","last_updated":"2024-12-05T07:55:58Z","snapshot_observed_at":"2026-08-12T13:14:03.152327Z","submitted_at":"2024-12-05T07:55:58Z","title":"Learning Speed-Adaptive Walking Agent Using Imitation Learning with Physics-Informed Simulation","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-11T21:58:43.039061Z"},"links":{"cited_paper":"/paper/2205.13600","citing_paper":"/paper/2412.03949"},"observation_digest":"sha256:08d1daea59e04a4aaaec581f1b1049e38676d6f762b2058d14123a542d1a2a70","observation_id":"c584b9cf-7f42-447f-a56a-091d1314c86e","resolution":{"observed_at":"2026-08-11T21:58:43.039061Z","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":"2026-08-11T21:58:43.042535Z","title":"Mujoco: A physics engine for model-based control,","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2412.03949","last_updated":"2024-12-05T07:55:58Z","snapshot_observed_at":"2026-08-12T13:14:03.152327Z","submitted_at":"2024-12-05T07:55:58Z","title":"Learning Speed-Adaptive Walking Agent Using Imitation Learning with Physics-Informed Simulation","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-11T21:58:43.042535Z"},"links":{"citing_paper":"/paper/2412.03949"},"observation_digest":"sha256:55470ac0d3c56d9a14c707d32c392310198e770269cedc9eeebda155402c9068","observation_id":"ac542cdc-a4af-4bee-8f7a-97b66e9a83bd","resolution":{"observed_at":"2026-08-11T21:58:43.042535Z","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":"2026-08-11T21:58:43.464639Z","title":"Markerless motion capture through visual hull, articu- lated icp and subject specific model generation,","venue":null,"work_id":"451400a5-2961-489f-bf05-49954d4697ca","year":2010},"citing_paper":{"arxiv_id":"2412.03949","last_updated":"2024-12-05T07:55:58Z","snapshot_observed_at":"2026-08-12T13:14:03.152327Z","submitted_at":"2024-12-05T07:55:58Z","title":"Learning Speed-Adaptive Walking Agent Using Imitation Learning with Physics-Informed Simulation","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-11T21:58:43.045134Z"},"links":{"citing_paper":"/paper/2412.03949"},"observation_digest":"sha256:01d3b116c336d27b2baa55bf1af8a2b01d8020c09d2783ae7416838bdce5b4a3","observation_id":"b2dd36d9-ac47-47b9-9755-9343e9bf32dc","resolution":{"observed_at":"2026-08-11T21:58:43.468243Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-11T21:58:43.047940Z","title":"Soft actor-critic: Off- policy maximum entropy deep reinforcement learning with a stochastic actor,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.03949","last_updated":"2024-12-05T07:55:58Z","snapshot_observed_at":"2026-08-12T13:14:03.152327Z","submitted_at":"2024-12-05T07:55:58Z","title":"Learning Speed-Adaptive Walking Agent Using Imitation Learning with Physics-Informed Simulation","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-11T21:58:43.047940Z"},"links":{"citing_paper":"/paper/2412.03949"},"observation_digest":"sha256:02a3d5302b9f17e1ffe9327f397873504924de77f0a5980d6eec378624971c6f","observation_id":"5b0321c7-cd19-4002-9302-ded57a4e777a","resolution":{"observed_at":"2026-08-11T21:58:43.047940Z","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":"2026-08-11T21:58:43.050358Z","title":"Deepmimic: Example-guided deep reinforcement learning of physics-based char- acter skills,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.03949","last_updated":"2024-12-05T07:55:58Z","snapshot_observed_at":"2026-08-12T13:14:03.152327Z","submitted_at":"2024-12-05T07:55:58Z","title":"Learning Speed-Adaptive Walking Agent Using Imitation Learning with Physics-Informed Simulation","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-11T21:58:43.050358Z"},"links":{"citing_paper":"/paper/2412.03949"},"observation_digest":"sha256:73cc668063e985dff5d5f8f00008abc52f948f110b693ea2c71d727ff3c9c646","observation_id":"90de4644-f46a-4160-a92d-af50c6070a8f","resolution":{"observed_at":"2026-08-11T21:58:43.050358Z","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":"2026-08-11T21:58:43.444184Z","title":"Opensim moco: Musculoskeletal optimal control,","venue":null,"work_id":"e9e9da72-741e-4ede-8b8b-caaf86c25a6d","year":2020},"citing_paper":{"arxiv_id":"2412.03949","last_updated":"2024-12-05T07:55:58Z","snapshot_observed_at":"2026-08-12T13:14:03.152327Z","submitted_at":"2024-12-05T07:55:58Z","title":"Learning Speed-Adaptive Walking Agent Using Imitation Learning with Physics-Informed Simulation","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-11T21:58:43.052413Z"},"links":{"citing_paper":"/paper/2412.03949"},"observation_digest":"sha256:e57ed6bcb254e51616ad15530fc038f0d25130685e5a3fbbce939762fb98877e","observation_id":"1cd23365-72ae-41f5-8aa2-7e057a2a2b99","resolution":{"observed_at":"2026-08-11T21:58:43.447549Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-11T21:58:43.434117Z","title":"Reinforcement learning for control of human locomotion in simulation,","venue":null,"work_id":"ed83ef41-8a86-45f2-b2f8-27d207f3b466","year":2024},"citing_paper":{"arxiv_id":"2412.03949","last_updated":"2024-12-05T07:55:58Z","snapshot_observed_at":"2026-08-12T13:14:03.152327Z","submitted_at":"2024-12-05T07:55:58Z","title":"Learning Speed-Adaptive Walking Agent Using Imitation Learning with Physics-Informed Simulation","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-11T21:58:43.055158Z"},"links":{"citing_paper":"/paper/2412.03949"},"observation_digest":"sha256:691f49521c55ec9af06c5eaf46bf2db8d569c31dbd015992a6343f17a994ea37","observation_id":"8031af6a-06b8-47bd-8583-56901a542403","resolution":{"observed_at":"2026-08-11T21:58:43.437671Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1810.00821","last_updated":"2020-08-25T02:41:11Z","snapshot_observed_at":"2026-08-04T12:42:55.627023Z","submitted_at":"2018-10-01T17:02:24Z","title":"Variational Discriminator Bottleneck: Improving Imitation Learning, Inverse RL, and GANs by Constraining Information Flow","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1810.00821","snapshot_observed_at":"2026-08-11T21:58:43.057428Z","title":"Variational discriminator bottleneck: Improving imitation learning, inverse rl, and gans by constraining information flow,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.03949","last_updated":"2024-12-05T07:55:58Z","snapshot_observed_at":"2026-08-12T13:14:03.152327Z","submitted_at":"2024-12-05T07:55:58Z","title":"Learning Speed-Adaptive Walking Agent Using Imitation Learning with Physics-Informed Simulation","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-11T21:58:43.057428Z"},"links":{"cited_paper":"/paper/1810.00821","citing_paper":"/paper/2412.03949"},"observation_digest":"sha256:ec296ac115f7e0d87210004cea3fe0e0069946389907e4f3124c5f9b1766a43e","observation_id":"93fd818b-4b1c-4791-b214-e705a97f09f1","resolution":{"observed_at":"2026-08-11T21:58:43.057428Z","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":"2026-08-11T21:58:43.425085Z","title":"A compre- hensive, open-source dataset of lower limb biomechanics in multiple conditions of stairs, ramps, and level-ground ambulation and transi- tions,","venue":null,"work_id":"e356d10d-3e6f-4ad8-8ce8-c3fcea0c4207","year":2021},"citing_paper":{"arxiv_id":"2412.03949","last_updated":"2024-12-05T07:55:58Z","snapshot_observed_at":"2026-08-12T13:14:03.152327Z","submitted_at":"2024-12-05T07:55:58Z","title":"Learning Speed-Adaptive Walking Agent Using Imitation Learning with Physics-Informed Simulation","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-11T21:58:43.060255Z"},"links":{"citing_paper":"/paper/2412.03949"},"observation_digest":"sha256:65ff145c380ad528b1db0bae4be25a4a2a1c49a34ed2b0a956a20d16bd420973","observation_id":"7f76724d-65ea-46ee-95e0-79b9fb66fa61","resolution":{"observed_at":"2026-08-11T21:58:43.427992Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.02496","last_updated":"2023-11-30T17:47:04Z","snapshot_observed_at":"2026-08-13T05:32:51.891832Z","submitted_at":"2023-11-04T19:41:50Z","title":"LocoMuJoCo: A Comprehensive Imitation Learning Benchmark for Locomotion","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.02496","snapshot_observed_at":"2026-08-11T21:58:43.062782Z","title":"Locomujoco: A comprehensive imitation learning benchmark for locomotion,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.03949","last_updated":"2024-12-05T07:55:58Z","snapshot_observed_at":"2026-08-12T13:14:03.152327Z","submitted_at":"2024-12-05T07:55:58Z","title":"Learning Speed-Adaptive Walking Agent Using Imitation Learning with Physics-Informed Simulation","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-11T21:58:43.062782Z"},"links":{"cited_paper":"/paper/2311.02496","citing_paper":"/paper/2412.03949"},"observation_digest":"sha256:2439fc734afb555094bb1534f371c722babb4de1552e69d6ba5f99e49ab6837f","observation_id":"2a5f23c3-ea14-4764-8f53-4b8a7e97183e","resolution":{"observed_at":"2026-08-11T21:58:43.062782Z","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":"2026-08-11T21:58:43.416028Z","title":"Muscle contributions to propulsion and support during running,","venue":null,"work_id":"de23a46f-175c-447b-919f-a3f104a69a79","year":2010},"citing_paper":{"arxiv_id":"2412.03949","last_updated":"2024-12-05T07:55:58Z","snapshot_observed_at":"2026-08-12T13:14:03.152327Z","submitted_at":"2024-12-05T07:55:58Z","title":"Learning Speed-Adaptive Walking Agent Using Imitation Learning with Physics-Informed Simulation","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-11T21:58:43.065642Z"},"links":{"citing_paper":"/paper/2412.03949"},"observation_digest":"sha256:f19581ae0d11fa519d21a5d468976e72385c5b8ca88656f64559d0ed1249f6b5","observation_id":"4ee64a9b-c70e-4bba-a0c3-4f91a1a54c72","resolution":{"observed_at":"2026-08-11T21:58:43.419370Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-11T21:58:43.407638Z","title":"Benchmark datasets for bi- lateral lower-limb neuromechanical signals from wearable sensors during unassisted locomotion in able-bodied individuals,","venue":null,"work_id":"4bf802ea-4341-4e68-8dd8-1f1a9b52af7f","year":2018},"citing_paper":{"arxiv_id":"2412.03949","last_updated":"2024-12-05T07:55:58Z","snapshot_observed_at":"2026-08-12T13:14:03.152327Z","submitted_at":"2024-12-05T07:55:58Z","title":"Learning Speed-Adaptive Walking Agent Using Imitation Learning with Physics-Informed Simulation","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-11T21:58:43.068575Z"},"links":{"citing_paper":"/paper/2412.03949"},"observation_digest":"sha256:c9f4410e0b913cbba6a02f12c9b191c0388f1ef78d1d8130e3f2edc9bc313c0c","observation_id":"94079650-e386-4990-b4d6-fd0069c3de68","resolution":{"observed_at":"2026-08-11T21:58:43.410832Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-11T21:58:43.071290Z","title":"Human kinematic, kinetic and emg data during level walking, toe/heel-walking, stairs ascending/descending,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.03949","last_updated":"2024-12-05T07:55:58Z","snapshot_observed_at":"2026-08-12T13:14:03.152327Z","submitted_at":"2024-12-05T07:55:58Z","title":"Learning Speed-Adaptive Walking Agent Using Imitation Learning with Physics-Informed Simulation","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-11T21:58:43.071290Z"},"links":{"citing_paper":"/paper/2412.03949"},"observation_digest":"sha256:849f8627b5bdd913fe76c3a4f02e6a17bbfb35f91c4a132a1665513ab159cb23","observation_id":"cefd6b46-7647-4487-89bb-b2b9733091b2","resolution":{"observed_at":"2026-08-11T21:58:43.071290Z","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":"2026-08-11T21:58:43.313470Z","title":"Lower limb kinematic, kinetic, and emg data from young healthy humans during walking at controlled speeds,","venue":null,"work_id":"38e1210b-ccbf-42b3-b6eb-baad705b86ad","year":2021},"citing_paper":{"arxiv_id":"2412.03949","last_updated":"2024-12-05T07:55:58Z","snapshot_observed_at":"2026-08-12T13:14:03.152327Z","submitted_at":"2024-12-05T07:55:58Z","title":"Learning Speed-Adaptive Walking Agent Using Imitation Learning with Physics-Informed Simulation","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-11T21:58:43.073968Z"},"links":{"citing_paper":"/paper/2412.03949"},"observation_digest":"sha256:5652906e2b3ae83955ec8abbd6f2799390f2773e09052976ee93e109f3aace56","observation_id":"b2362eb8-16e8-4c12-897e-4823c593fcb1","resolution":{"observed_at":"2026-08-11T21:58:43.401613Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-11T21:58:43.077245Z","title":"Generative adversarial net- works,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.03949","last_updated":"2024-12-05T07:55:58Z","snapshot_observed_at":"2026-08-12T13:14:03.152327Z","submitted_at":"2024-12-05T07:55:58Z","title":"Learning Speed-Adaptive Walking Agent Using Imitation Learning with Physics-Informed Simulation","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-11T21:58:43.077245Z"},"links":{"citing_paper":"/paper/2412.03949"},"observation_digest":"sha256:fdbe0051d29a96fd85c406b8b5896aded38bea33a0cf9043996efc85f3c7bc35","observation_id":"d6fa5f8c-2827-46e7-85b0-169a09af8e85","resolution":{"observed_at":"2026-08-11T21:58:43.077245Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1502.05477","last_updated":"2017-04-20T18:04:12Z","snapshot_observed_at":"2026-07-06T04:09:39.172428Z","submitted_at":"2015-02-19T06:44:25Z","title":"Trust Region Policy Optimization","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1502.05477","snapshot_observed_at":"2026-08-11T21:58:43.079755Z","title":"Trust region policy optimization,","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2412.03949","last_updated":"2024-12-05T07:55:58Z","snapshot_observed_at":"2026-08-12T13:14:03.152327Z","submitted_at":"2024-12-05T07:55:58Z","title":"Learning Speed-Adaptive Walking Agent Using Imitation Learning with Physics-Informed Simulation","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-11T21:58:43.079755Z"},"links":{"cited_paper":"/paper/1502.05477","citing_paper":"/paper/2412.03949"},"observation_digest":"sha256:357241463d2971ea3bd4b3ba2efef683ff5dffcf82b9dfb5e50187408eec77c3","observation_id":"3b61bf21-a600-400d-b948-f50c2d7fe588","resolution":{"observed_at":"2026-08-11T21:58:43.079755Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.02976","last_updated":"2023-09-07T15:23:29Z","snapshot_observed_at":"2026-08-13T10:19:17.847287Z","submitted_at":"2023-09-06T13:20:31Z","title":"Natural and Robust Walking using Reinforcement Learning without Demonstrations in High-Dimensional Musculoskeletal Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.02976","snapshot_observed_at":"2026-08-11T21:58:43.082667Z","title":"Natural and robust walking using reinforcement learning without demonstrations in high-dimensional musculoskeletal models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.03949","last_updated":"2024-12-05T07:55:58Z","snapshot_observed_at":"2026-08-12T13:14:03.152327Z","submitted_at":"2024-12-05T07:55:58Z","title":"Learning Speed-Adaptive Walking Agent Using Imitation Learning with Physics-Informed Simulation","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-11T21:58:43.082667Z"},"links":{"cited_paper":"/paper/2309.02976","citing_paper":"/paper/2412.03949"},"observation_digest":"sha256:5bbd4be8fad7687264fd3d28a9668a70bad0940b6bc4818c6e572143990ad624","observation_id":"1ba6e6a3-2429-4245-b00e-3eab43ea3af3","resolution":{"observed_at":"2026-08-11T21:58:43.082667Z","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":"2026-08-11T21:58:43.220582Z","title":"Creation and evaluation of human models with varied walking ability from motion capture for assistive device development,","venue":null,"work_id":"795b7ad0-305b-4b9a-9aab-a7abc2b4d243","year":2023},"citing_paper":{"arxiv_id":"2412.03949","last_updated":"2024-12-05T07:55:58Z","snapshot_observed_at":"2026-08-12T13:14:03.152327Z","submitted_at":"2024-12-05T07:55:58Z","title":"Learning Speed-Adaptive Walking Agent Using Imitation Learning with Physics-Informed Simulation","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-11T21:58:43.085303Z"},"links":{"citing_paper":"/paper/2412.03949"},"observation_digest":"sha256:4595f8cd94791d98b880b4daad775d408cc426ca3c044db049e4249e06580b04","observation_id":"3a087875-e7ab-4f95-8b53-449cd3bb49ed","resolution":{"observed_at":"2026-08-11T21:58:43.258000Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-11T21:58:43.143126Z","title":"Deep reinforcement learning for modeling human locomotion control in neuromechanical simulation,","venue":null,"work_id":"e07ea521-22b9-48b2-9641-cae0da27cb1b","year":2021},"citing_paper":{"arxiv_id":"2412.03949","last_updated":"2024-12-05T07:55:58Z","snapshot_observed_at":"2026-08-12T13:14:03.152327Z","submitted_at":"2024-12-05T07:55:58Z","title":"Learning Speed-Adaptive Walking Agent Using Imitation Learning with Physics-Informed Simulation","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-11T21:58:43.087788Z"},"links":{"citing_paper":"/paper/2412.03949"},"observation_digest":"sha256:230861c92f9cb10b5141643b8d69f4ef8bcdf7cdba866b544a899146eb886cb1","observation_id":"3cd5fa95-d268-47b8-87a6-ee37cf8e73d6","resolution":{"observed_at":"2026-08-11T21:58:43.182448Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2412.03949","last_updated":"2024-12-05T07:55:58Z","latest_version":1,"primary_category":"cs.RO","snapshot_observed_at":"2026-08-12T13:14:03.152327Z","submitted_at":"2024-12-05T07:55:58Z","title":"Learning Speed-Adaptive Walking Agent Using Imitation Learning with Physics-Informed Simulation"},"reference_resolution":{"displayed":35,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":9,"verified_exact":0,"verified_fuzzy":25},"total_outbound_references":35},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"thesis":"As of 14 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2412.03949."}