{"as_of":"2026-08-15T04:20:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:c4409c87989b39a97d54c34b074514e5664100cc826232566a0e81d3ea44f0b9","coverage":[{"denominator":41,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":41,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T14:35:17.349932Z","state":"measured"},{"denominator":41,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":41,"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/2505.18412/citation-record","integrity":"/paper/2505.18412/integrity","json":"/paper/2505.18412/citation-record.json","paper":"/paper/2505.18412"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:35:20.058495Z","title":"Rehabilitation,","venue":null,"work_id":"8f231ee5-bdd8-4a51-98bf-4a25982c7f76","year":2023},"citing_paper":{"arxiv_id":"2505.18412","last_updated":"2025-05-23T22:39:10Z","snapshot_observed_at":"2026-08-11T16:39:24.237050Z","submitted_at":"2025-05-23T22:39:10Z","title":"Rehabilitation Exercise Quality Assessment and Feedback Generation Using Large Language Models with Prompt Engineering","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T14:35:13.067244Z"},"links":{"citing_paper":"/paper/2505.18412"},"observation_digest":"sha256:e939d596b3d3026bc3ecdb61f94724c1ed0803f1158e9ddf36a4943ba0dfac07","observation_id":"7938ebb4-4fb2-4ad0-91d3-7414935f9bdb","resolution":{"observed_at":"2026-08-07T14:35:20.061668Z","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":"2026-08-07T14:35:20.048353Z","title":"Exercise-based cardiac rehabilitation for coronary heart disease: a meta-analysis,","venue":null,"work_id":"faffc29d-c3af-4286-862b-3d9c63d77929","year":2023},"citing_paper":{"arxiv_id":"2505.18412","last_updated":"2025-05-23T22:39:10Z","snapshot_observed_at":"2026-08-11T16:39:24.237050Z","submitted_at":"2025-05-23T22:39:10Z","title":"Rehabilitation Exercise Quality Assessment and Feedback Generation Using Large Language Models with Prompt Engineering","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T14:35:13.144000Z"},"links":{"citing_paper":"/paper/2505.18412"},"observation_digest":"sha256:eabefb19223e461a6cf0a7d9af1cca4f339084ec3d9a1b6015980a096b9efd84","observation_id":"0716820c-3db7-442d-9fcd-65d295fcf1f2","resolution":{"observed_at":"2026-08-07T14:35:20.051866Z","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":"2026-08-07T14:35:20.037931Z","title":"Barriers and facilitators of rehabilitation nursing care for patients with disability in the rehabilitation hospital: A qualitative study,","venue":null,"work_id":"a03b7f6d-d093-46aa-b17a-7a8d3c29e242","year":2022},"citing_paper":{"arxiv_id":"2505.18412","last_updated":"2025-05-23T22:39:10Z","snapshot_observed_at":"2026-08-11T16:39:24.237050Z","submitted_at":"2025-05-23T22:39:10Z","title":"Rehabilitation Exercise Quality Assessment and Feedback Generation Using Large Language Models with Prompt Engineering","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T14:35:13.184973Z"},"links":{"citing_paper":"/paper/2505.18412"},"observation_digest":"sha256:cca3019260dcab496b2aa0b92b8eb33769f14a8dcc7432a90e9f897745b92e12","observation_id":"f24d2247-4e38-4c41-adf5-5488b5e99fb6","resolution":{"observed_at":"2026-08-07T14:35:20.041082Z","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":"2026-08-07T14:35:20.028108Z","title":"Usage of auxiliary systems and artificial intelligence in home-based rehabilitation: A review,","venue":null,"work_id":"d26e25af-dcd6-4a57-bc8b-2b7c31f45e5f","year":2023},"citing_paper":{"arxiv_id":"2505.18412","last_updated":"2025-05-23T22:39:10Z","snapshot_observed_at":"2026-08-11T16:39:24.237050Z","submitted_at":"2025-05-23T22:39:10Z","title":"Rehabilitation Exercise Quality Assessment and Feedback Generation Using Large Language Models with Prompt Engineering","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T14:35:13.302137Z"},"links":{"citing_paper":"/paper/2505.18412"},"observation_digest":"sha256:f44088bad3e473b6b9b45d4c84c9f8a4a26d5fb4ba2ec12e55dffeb4f907b46b","observation_id":"514156ad-5290-479c-bc71-c1ef275f8d31","resolution":{"observed_at":"2026-08-07T14:35:20.031239Z","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":"2026-08-07T14:35:20.018115Z","title":"Effective- ness of telerehabilitation in physical therapy: a rapid overview,","venue":null,"work_id":"6fecf1f4-fcfe-4d9c-8c74-b3de93da9f3e","year":2021},"citing_paper":{"arxiv_id":"2505.18412","last_updated":"2025-05-23T22:39:10Z","snapshot_observed_at":"2026-08-11T16:39:24.237050Z","submitted_at":"2025-05-23T22:39:10Z","title":"Rehabilitation Exercise Quality Assessment and Feedback Generation Using Large Language Models with Prompt Engineering","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T14:35:13.406283Z"},"links":{"citing_paper":"/paper/2505.18412"},"observation_digest":"sha256:1235f84a73b04388189181030a51b2f961eb3e69aac1d7be3e0a8e36d28d4396","observation_id":"d1fca74c-f15d-4776-adf0-6cf0cf4ce98a","resolution":{"observed_at":"2026-08-07T14:35:20.021547Z","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":"2026-08-07T14:35:20.007017Z","title":"Wear- able sensors and machine learning in post-stroke rehabilitation assessment: A sys- tematic review,","venue":null,"work_id":"ffd9b85d-beb6-4bbf-af93-6e7cbb41e6cd","year":2022},"citing_paper":{"arxiv_id":"2505.18412","last_updated":"2025-05-23T22:39:10Z","snapshot_observed_at":"2026-08-11T16:39:24.237050Z","submitted_at":"2025-05-23T22:39:10Z","title":"Rehabilitation Exercise Quality Assessment and Feedback Generation Using Large Language Models with Prompt Engineering","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T14:35:13.475098Z"},"links":{"citing_paper":"/paper/2505.18412"},"observation_digest":"sha256:2bfa2d35a9157cceefceeb940fd98e337ca79a039d7b69b99dd9607c2d07cddb","observation_id":"2be84dfd-91d5-4747-8f03-c05fb70a4760","resolution":{"observed_at":"2026-08-07T14:35:20.011095Z","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":"2026-08-07T14:35:13.555497Z","title":"Artificial intelligence-driven virtual rehabilitation for people living in the community: A scoping review,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.18412","last_updated":"2025-05-23T22:39:10Z","snapshot_observed_at":"2026-08-11T16:39:24.237050Z","submitted_at":"2025-05-23T22:39:10Z","title":"Rehabilitation Exercise Quality Assessment and Feedback Generation Using Large Language Models with Prompt Engineering","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T14:35:13.555497Z"},"links":{"citing_paper":"/paper/2505.18412"},"observation_digest":"sha256:98f1e743922dcc7157971fce385f4434d5269af150264bdeaeec3cf9db19b444","observation_id":"17d5b1f2-6f08-4740-b436-7e37515fa08c","resolution":{"observed_at":"2026-08-07T14:35:13.555497Z","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":"2026-08-07T14:35:19.991508Z","title":"Artificial intelligence for skeleton-based physical rehabilitation action evaluation: A systematic review,","venue":null,"work_id":"d399b0ed-014f-4f64-beb2-16ad4ffecaf4","year":2023},"citing_paper":{"arxiv_id":"2505.18412","last_updated":"2025-05-23T22:39:10Z","snapshot_observed_at":"2026-08-11T16:39:24.237050Z","submitted_at":"2025-05-23T22:39:10Z","title":"Rehabilitation Exercise Quality Assessment and Feedback Generation Using Large Language Models with Prompt Engineering","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T14:35:13.633531Z"},"links":{"citing_paper":"/paper/2505.18412"},"observation_digest":"sha256:f67e0faa3d34233e40b96a304785db20f1d5424617e838d2fe121201872fb90b","observation_id":"89d689f9-ab4d-4741-bda1-67eae2ff2178","resolution":{"observed_at":"2026-08-07T14:35:19.994780Z","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":"2026-08-07T14:35:19.982319Z","title":"Technological advances in lower-limb tele- rehabilitation:Areviewofliterature,","venue":null,"work_id":"c1933bc0-60bf-4381-8310-ea0c71891eca","year":2024},"citing_paper":{"arxiv_id":"2505.18412","last_updated":"2025-05-23T22:39:10Z","snapshot_observed_at":"2026-08-11T16:39:24.237050Z","submitted_at":"2025-05-23T22:39:10Z","title":"Rehabilitation Exercise Quality Assessment and Feedback Generation Using Large Language Models with Prompt Engineering","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T14:35:13.724217Z"},"links":{"citing_paper":"/paper/2505.18412"},"observation_digest":"sha256:b51083c0c857ec893809935ba7b9e169edf9dff28468267d6936c2b196704c66","observation_id":"82626625-c63b-4f62-bf49-2d907df9d446","resolution":{"observed_at":"2026-08-07T14:35:19.985843Z","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":"2026-08-07T14:35:19.973301Z","title":"Feedback design in targeted exercise digital biofeedback systems for home rehabilitation: A scoping review,","venue":null,"work_id":"d7fe95f9-00b6-453a-8ddd-458a584c99ef","year":2019},"citing_paper":{"arxiv_id":"2505.18412","last_updated":"2025-05-23T22:39:10Z","snapshot_observed_at":"2026-08-11T16:39:24.237050Z","submitted_at":"2025-05-23T22:39:10Z","title":"Rehabilitation Exercise Quality Assessment and Feedback Generation Using Large Language Models with Prompt Engineering","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T14:35:13.819907Z"},"links":{"citing_paper":"/paper/2505.18412"},"observation_digest":"sha256:6251b696630233fca1d8d5f0a7fe8c6e0dc57945317f423f33984d8d97f06fb2","observation_id":"a1d84672-dc9a-46a0-9bf8-17b68fb57ab0","resolution":{"observed_at":"2026-08-07T14:35:19.976356Z","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":"2026-08-07T14:35:19.963108Z","title":"3d human pose estimation in video with temporal convolutions and semi-supervised training,","venue":null,"work_id":"ec2e5fa1-1e73-4354-ae06-37748e26c834","year":2019},"citing_paper":{"arxiv_id":"2505.18412","last_updated":"2025-05-23T22:39:10Z","snapshot_observed_at":"2026-08-11T16:39:24.237050Z","submitted_at":"2025-05-23T22:39:10Z","title":"Rehabilitation Exercise Quality Assessment and Feedback Generation Using Large Language Models with Prompt Engineering","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T14:35:13.923459Z"},"links":{"citing_paper":"/paper/2505.18412"},"observation_digest":"sha256:986c8267c4b1d79d52fa12f6e7b2035a1710ba80e93f3b4a3534a5f034cea6c6","observation_id":"b1896bdf-ae16-42c1-a4f2-d5517c27d43c","resolution":{"observed_at":"2026-08-07T14:35:19.966610Z","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":"1906.08172","last_updated":"2019-06-14T05:49:22Z","snapshot_observed_at":"2026-08-05T19:15:35.517082Z","submitted_at":"2019-06-14T05:49:22Z","title":"MediaPipe: A Framework for Building Perception Pipelines","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1906.08172","snapshot_observed_at":"2026-08-07T14:35:14.015550Z","title":"Mediapipe: A framework for building perception pipelines,","venue":null,"work_id":null,"year":1906},"citing_paper":{"arxiv_id":"2505.18412","last_updated":"2025-05-23T22:39:10Z","snapshot_observed_at":"2026-08-11T16:39:24.237050Z","submitted_at":"2025-05-23T22:39:10Z","title":"Rehabilitation Exercise Quality Assessment and Feedback Generation Using Large Language Models with Prompt Engineering","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T14:35:14.015550Z"},"links":{"cited_paper":"/paper/1906.08172","citing_paper":"/paper/2505.18412"},"observation_digest":"sha256:7469e557c4e9800e904177b8aea9903c442af16e91617eccc0c613480608fe5a","observation_id":"d72954e5-7564-482e-aa61-04a029274724","resolution":{"observed_at":"2026-08-07T14:35:14.015550Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.09546","last_updated":"2023-06-15T23:23:35Z","snapshot_observed_at":"2026-08-15T02:56:04.590792Z","submitted_at":"2023-06-15T23:23:35Z","title":"Cross-Modal Video to Body-joints Augmentation for Rehabilitation Exercise Quality Assessment","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.09546","snapshot_observed_at":"2026-08-07T14:35:14.100554Z","title":"Cross-modal video to body-joints augmentation for rehabilitation exercise quality assessment,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.18412","last_updated":"2025-05-23T22:39:10Z","snapshot_observed_at":"2026-08-11T16:39:24.237050Z","submitted_at":"2025-05-23T22:39:10Z","title":"Rehabilitation Exercise Quality Assessment and Feedback Generation Using Large Language Models with Prompt Engineering","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T14:35:14.100554Z"},"links":{"cited_paper":"/paper/2306.09546","citing_paper":"/paper/2505.18412"},"observation_digest":"sha256:6b53c4e2a8cb84a30bd0e3fc863e76bec7b800cdbbccfec6ebe60c9c90a3ee75","observation_id":"9860901a-c9d2-4807-a621-2592d5fee54f","resolution":{"observed_at":"2026-08-07T14:35:14.100554Z","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":"2026-08-07T14:35:19.954369Z","title":"Spatial temporal graph convolutional networks for skeleton-based action recognition,","venue":null,"work_id":"ef638766-64b8-4376-ba80-79fdd2baf005","year":2018},"citing_paper":{"arxiv_id":"2505.18412","last_updated":"2025-05-23T22:39:10Z","snapshot_observed_at":"2026-08-11T16:39:24.237050Z","submitted_at":"2025-05-23T22:39:10Z","title":"Rehabilitation Exercise Quality Assessment and Feedback Generation Using Large Language Models with Prompt Engineering","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T14:35:14.208119Z"},"links":{"citing_paper":"/paper/2505.18412"},"observation_digest":"sha256:06d1692c2bb28212480334e763dba2fa0a53b8ec3f6dabae121d88bb025ccdf9","observation_id":"57deeed6-1593-4440-a619-75f24075e894","resolution":{"observed_at":"2026-08-07T14:35:19.957546Z","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":"2026-08-07T14:35:19.943735Z","title":"The kimore dataset: Kinematic assessment of movement and clinical scores for remote monitoring of physical rehabilitation,","venue":null,"work_id":"e1c30e10-9a0e-40fb-96f8-f5298ef614dc","year":2019},"citing_paper":{"arxiv_id":"2505.18412","last_updated":"2025-05-23T22:39:10Z","snapshot_observed_at":"2026-08-11T16:39:24.237050Z","submitted_at":"2025-05-23T22:39:10Z","title":"Rehabilitation Exercise Quality Assessment and Feedback Generation Using Large Language Models with Prompt Engineering","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T14:35:14.299783Z"},"links":{"citing_paper":"/paper/2505.18412"},"observation_digest":"sha256:3fb226dd37f144f32fb9acdadbd45b0e8355ff615c3ed74e22a36a22b9ad3327","observation_id":"a0504ce1-12c5-4b2c-8778-c360f49b4d3b","resolution":{"observed_at":"2026-08-07T14:35:19.947148Z","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":"2026-08-07T14:35:19.932321Z","title":"Relevance of therapist feedback in the context of group-based exercise programs in medical rehabilitation–results from a qualitative study with patients and exercise therapists,","venue":null,"work_id":"07557d47-032a-473f-be88-9d9488ff5901","year":2024},"citing_paper":{"arxiv_id":"2505.18412","last_updated":"2025-05-23T22:39:10Z","snapshot_observed_at":"2026-08-11T16:39:24.237050Z","submitted_at":"2025-05-23T22:39:10Z","title":"Rehabilitation Exercise Quality Assessment and Feedback Generation Using Large Language Models with Prompt Engineering","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T14:35:14.384275Z"},"links":{"citing_paper":"/paper/2505.18412"},"observation_digest":"sha256:3e6fd35b2a7c522420517be8a195cd0c0cb91fe8aed8ef21694a73e1c2683cb9","observation_id":"8cc75b2d-2e0f-47e5-bb2f-59ebfb7c0f26","resolution":{"observed_at":"2026-08-07T14:35:19.935905Z","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":"2026-08-07T14:35:19.921739Z","title":"Feedback- mediated upper extremities exercise: Increasing patient motivation in poststroke rehabilitation,","venue":null,"work_id":"9ade648b-c04e-48b1-92eb-8902a3e7bd3e","year":2014},"citing_paper":{"arxiv_id":"2505.18412","last_updated":"2025-05-23T22:39:10Z","snapshot_observed_at":"2026-08-11T16:39:24.237050Z","submitted_at":"2025-05-23T22:39:10Z","title":"Rehabilitation Exercise Quality Assessment and Feedback Generation Using Large Language Models with Prompt Engineering","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T14:35:14.494698Z"},"links":{"citing_paper":"/paper/2505.18412"},"observation_digest":"sha256:68b69748c56bd045d09ba2d3a6525ebbe4a3c7199aebe935af5e0b21085a4c37","observation_id":"5f8f3db1-71d8-43e1-962b-c1583ad73b54","resolution":{"observed_at":"2026-08-07T14:35:19.925293Z","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":"2026-08-07T14:35:19.911614Z","title":"Ubiphysio: Support daily functioning, fitness, and rehabilitation with action understanding and feedback in natural language,","venue":null,"work_id":"4dc415a4-34f0-4511-8348-7e48e6fa9260","year":2024},"citing_paper":{"arxiv_id":"2505.18412","last_updated":"2025-05-23T22:39:10Z","snapshot_observed_at":"2026-08-11T16:39:24.237050Z","submitted_at":"2025-05-23T22:39:10Z","title":"Rehabilitation Exercise Quality Assessment and Feedback Generation Using Large Language Models with Prompt Engineering","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T14:35:14.652483Z"},"links":{"citing_paper":"/paper/2505.18412"},"observation_digest":"sha256:1c21ea060e76d3693ea2096b3a754fbbcc9ef25ec013dfa706dc21a955719a5c","observation_id":"330325e7-a378-45fe-959e-29476e9b29a9","resolution":{"observed_at":"2026-08-07T14:35:19.914895Z","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":"2026-08-07T14:35:19.903210Z","title":"A data set of human body movements for physical rehabilitation exercises,","venue":null,"work_id":"b03371e1-f56c-42b8-b63d-8f4e736a6861","year":2018},"citing_paper":{"arxiv_id":"2505.18412","last_updated":"2025-05-23T22:39:10Z","snapshot_observed_at":"2026-08-11T16:39:24.237050Z","submitted_at":"2025-05-23T22:39:10Z","title":"Rehabilitation Exercise Quality Assessment and Feedback Generation Using Large Language Models with Prompt Engineering","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T14:35:14.809334Z"},"links":{"citing_paper":"/paper/2505.18412"},"observation_digest":"sha256:3929eb4c73a62237bb89a9dc7a0edd7ba4ccdfd6fb2152dadc0ff4c903436275","observation_id":"a105aea0-c051-4529-9d95-61e26c6306e9","resolution":{"observed_at":"2026-08-07T14:35:19.905971Z","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":"2026-08-07T14:35:19.894057Z","title":"Rehab24-6: Physical therapy dataset for analyzing pose estimation methods,","venue":null,"work_id":"7f179e62-12c3-4099-b31a-e20fdf8d25b3","year":2024},"citing_paper":{"arxiv_id":"2505.18412","last_updated":"2025-05-23T22:39:10Z","snapshot_observed_at":"2026-08-11T16:39:24.237050Z","submitted_at":"2025-05-23T22:39:10Z","title":"Rehabilitation Exercise Quality Assessment and Feedback Generation Using Large Language Models with Prompt Engineering","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T14:35:14.978174Z"},"links":{"citing_paper":"/paper/2505.18412"},"observation_digest":"sha256:31e3502ea8525d31b4c5609b4e339ea29cb21e818f2cb613800a9c9a22679029","observation_id":"8b896ae9-2da8-4503-9ead-ad5c25fb152e","resolution":{"observed_at":"2026-08-07T14:35:19.897428Z","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":"2026-08-07T14:35:19.884424Z","title":"A deep learning framework for assessing physical rehabilitation exercises,","venue":null,"work_id":"2d76d52e-fa86-4ad3-96dc-143bcefdbcaf","year":2020},"citing_paper":{"arxiv_id":"2505.18412","last_updated":"2025-05-23T22:39:10Z","snapshot_observed_at":"2026-08-11T16:39:24.237050Z","submitted_at":"2025-05-23T22:39:10Z","title":"Rehabilitation Exercise Quality Assessment and Feedback Generation Using Large Language Models with Prompt Engineering","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T14:35:15.150732Z"},"links":{"citing_paper":"/paper/2505.18412"},"observation_digest":"sha256:490bf9dd1086dd5558ccbea4b687b182651d057e386341b28da7da6b4e134a69","observation_id":"55965bbd-ab1f-4f19-8e25-4ff878571655","resolution":{"observed_at":"2026-08-07T14:35:19.887669Z","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":"2026-08-07T14:35:19.875631Z","title":"Exercise-specific feature extraction approach for assessing physical rehabilitation,","venue":null,"work_id":"cedc7aa7-c88b-45d8-856e-87fc8b9c9ba8","year":2021},"citing_paper":{"arxiv_id":"2505.18412","last_updated":"2025-05-23T22:39:10Z","snapshot_observed_at":"2026-08-11T16:39:24.237050Z","submitted_at":"2025-05-23T22:39:10Z","title":"Rehabilitation Exercise Quality Assessment and Feedback Generation Using Large Language Models with Prompt Engineering","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T14:35:15.266213Z"},"links":{"citing_paper":"/paper/2505.18412"},"observation_digest":"sha256:859bfa25b3290642fdf1899bb47897f65e1b5d3727560cfe16715df2b181fbdc","observation_id":"09177de6-e0c6-4d0f-8ecc-2d869d6946d5","resolution":{"observed_at":"2026-08-07T14:35:19.878649Z","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":"2026-08-07T14:35:19.866531Z","title":"Supervised sequential contrastive regression: Improving performance on imbalanced rehabilitation exercises datasets,","venue":null,"work_id":"62710228-4bc8-463b-a251-699ed72e6edd","year":2023},"citing_paper":{"arxiv_id":"2505.18412","last_updated":"2025-05-23T22:39:10Z","snapshot_observed_at":"2026-08-11T16:39:24.237050Z","submitted_at":"2025-05-23T22:39:10Z","title":"Rehabilitation Exercise Quality Assessment and Feedback Generation Using Large Language Models with Prompt Engineering","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T14:35:15.450537Z"},"links":{"citing_paper":"/paper/2505.18412"},"observation_digest":"sha256:2805badf7d7c7f47eefaa3132e8ed970c3c53a77b7f8f23d7e4c2d31e939bfd9","observation_id":"4f206bed-de9f-4c8f-a148-7623821305f9","resolution":{"observed_at":"2026-08-07T14:35:19.869896Z","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":"2026-08-07T14:35:19.856616Z","title":"Graph convolutional networks for assessment of physical rehabilitation exercises,","venue":null,"work_id":"95b8bd7f-94ed-43c9-b7ab-00b7671be27f","year":2022},"citing_paper":{"arxiv_id":"2505.18412","last_updated":"2025-05-23T22:39:10Z","snapshot_observed_at":"2026-08-11T16:39:24.237050Z","submitted_at":"2025-05-23T22:39:10Z","title":"Rehabilitation Exercise Quality Assessment and Feedback Generation Using Large Language Models with Prompt Engineering","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T14:35:15.635415Z"},"links":{"citing_paper":"/paper/2505.18412"},"observation_digest":"sha256:1d20ff76a3985455c6b21541164975090397ddd182d857c28c7a4dc19e4e5e1f","observation_id":"4d300ebd-4a0f-4300-bb6e-97e022047b1c","resolution":{"observed_at":"2026-08-07T14:35:19.860082Z","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":"2026-08-07T14:35:19.845723Z","title":"A skeleton-based rehabilitation exer- cise assessment system with rotation invariance,","venue":null,"work_id":"cd9f8592-3c45-4264-8d2c-133c2b698549","year":2023},"citing_paper":{"arxiv_id":"2505.18412","last_updated":"2025-05-23T22:39:10Z","snapshot_observed_at":"2026-08-11T16:39:24.237050Z","submitted_at":"2025-05-23T22:39:10Z","title":"Rehabilitation Exercise Quality Assessment and Feedback Generation Using Large Language Models with Prompt Engineering","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T14:35:15.853224Z"},"links":{"citing_paper":"/paper/2505.18412"},"observation_digest":"sha256:5ddcbba31bb5a71f33c9774d710bdeb973a938635e0f23bca069375206133a0a","observation_id":"7074183a-3742-4d07-80ec-32955baead57","resolution":{"observed_at":"2026-08-07T14:35:19.850390Z","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":"2026-08-07T14:35:19.677363Z","title":"Graph transformer for phys- ical rehabilitation evaluation,","venue":null,"work_id":"439c2715-5729-4800-99ba-b4f48a73c7a5","year":2023},"citing_paper":{"arxiv_id":"2505.18412","last_updated":"2025-05-23T22:39:10Z","snapshot_observed_at":"2026-08-11T16:39:24.237050Z","submitted_at":"2025-05-23T22:39:10Z","title":"Rehabilitation Exercise Quality Assessment and Feedback Generation Using Large Language Models with Prompt Engineering","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T14:35:16.076918Z"},"links":{"citing_paper":"/paper/2505.18412"},"observation_digest":"sha256:f4e812710401a8f71446555f5fc765d0b227045def9f55e3db1ebf7d8353da62","observation_id":"620c817e-1ea8-45a7-91db-b25edc941002","resolution":{"observed_at":"2026-08-07T14:35:19.838534Z","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":"2026-08-07T14:35:19.335683Z","title":"Rehabilitation exercise quality assessment through supervised contrastive learning with hard and soft negatives,","venue":null,"work_id":"2225ca66-eae7-427f-abcd-65f4c460bd2e","year":2024},"citing_paper":{"arxiv_id":"2505.18412","last_updated":"2025-05-23T22:39:10Z","snapshot_observed_at":"2026-08-11T16:39:24.237050Z","submitted_at":"2025-05-23T22:39:10Z","title":"Rehabilitation Exercise Quality Assessment and Feedback Generation Using Large Language Models with Prompt Engineering","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T14:35:16.259890Z"},"links":{"citing_paper":"/paper/2505.18412"},"observation_digest":"sha256:fd17ace25ef98527b0e72bdfef1c67ba7706ee48ae32d6ddd8f7ddc53c4cdee0","observation_id":"c57ec8cb-950c-4308-bd67-cd76e0e32268","resolution":{"observed_at":"2026-08-07T14:35:19.499325Z","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":"2026-08-07T14:35:19.123560Z","title":"Egcn++: A new fusion strategy for ensemble learning in skeleton-based rehabilitation exercise assessment,","venue":null,"work_id":"973a3b1e-0a7b-4246-8cbc-48aee7becf26","year":2024},"citing_paper":{"arxiv_id":"2505.18412","last_updated":"2025-05-23T22:39:10Z","snapshot_observed_at":"2026-08-11T16:39:24.237050Z","submitted_at":"2025-05-23T22:39:10Z","title":"Rehabilitation Exercise Quality Assessment and Feedback Generation Using Large Language Models with Prompt Engineering","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T14:35:16.314303Z"},"links":{"citing_paper":"/paper/2505.18412"},"observation_digest":"sha256:b323dd7dd8939e6daec608f2397922413d7710a741333451cce246530742f78d","observation_id":"40611876-dc04-4238-9fd5-caad3c6ccf9d","resolution":{"observed_at":"2026-08-07T14:35:19.222475Z","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":"2026-08-07T14:35:18.958696Z","title":"A review of the evidence underpin- ning the use of visual and auditory feedback for computer technology in post- stroke upper-limb rehabilitation,","venue":null,"work_id":"cee4d694-9bca-402e-8dcf-78f5105e5177","year":2011},"citing_paper":{"arxiv_id":"2505.18412","last_updated":"2025-05-23T22:39:10Z","snapshot_observed_at":"2026-08-11T16:39:24.237050Z","submitted_at":"2025-05-23T22:39:10Z","title":"Rehabilitation Exercise Quality Assessment and Feedback Generation Using Large Language Models with Prompt Engineering","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T14:35:16.381862Z"},"links":{"citing_paper":"/paper/2505.18412"},"observation_digest":"sha256:b3308d85a70c74a6ee366ccceeb16c1c947e3240555e02d93c3f05198e750842","observation_id":"801420e7-edff-4088-bf5a-9f6efe612bc7","resolution":{"observed_at":"2026-08-07T14:35:19.043793Z","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":"2026-08-07T14:35:18.775381Z","title":"Finerehab: A multi- modality and multi-task dataset for rehabilitation analysis,","venue":null,"work_id":"5cef0264-6351-4d5f-ad79-8007bab2a4c5","year":2024},"citing_paper":{"arxiv_id":"2505.18412","last_updated":"2025-05-23T22:39:10Z","snapshot_observed_at":"2026-08-11T16:39:24.237050Z","submitted_at":"2025-05-23T22:39:10Z","title":"Rehabilitation Exercise Quality Assessment and Feedback Generation Using Large Language Models with Prompt Engineering","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T14:35:16.472199Z"},"links":{"citing_paper":"/paper/2505.18412"},"observation_digest":"sha256:03b560accb0e087be28c9b186305148eac0ff4071b64e269d7649f3c5263f4e4","observation_id":"65dc85ed-7770-4235-b737-c2717b800b2f","resolution":{"observed_at":"2026-08-07T14:35:18.838139Z","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":"2026-08-07T14:35:18.606013Z","title":"Intellirehabds (irds)—a dataset of physical rehabilitation movements,","venue":null,"work_id":"90c331b2-7080-4d9d-a1a2-29539d43c15d","year":2021},"citing_paper":{"arxiv_id":"2505.18412","last_updated":"2025-05-23T22:39:10Z","snapshot_observed_at":"2026-08-11T16:39:24.237050Z","submitted_at":"2025-05-23T22:39:10Z","title":"Rehabilitation Exercise Quality Assessment and Feedback Generation Using Large Language Models with Prompt Engineering","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T14:35:16.563775Z"},"links":{"citing_paper":"/paper/2505.18412"},"observation_digest":"sha256:f042a0a83179b43b6ca6446a4aeffabbc3fa2e43674b4308a32076109d57e369","observation_id":"64de692d-cc18-4de8-8ae3-3e4c352f59c1","resolution":{"observed_at":"2026-08-07T14:35:18.684477Z","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":"2026-08-07T14:35:18.401953Z","title":"Prompt engineering paradigms for medical applications: Scoping review,","venue":null,"work_id":"3d92069a-450c-496e-82fe-fe4fdb8bfa05","year":2024},"citing_paper":{"arxiv_id":"2505.18412","last_updated":"2025-05-23T22:39:10Z","snapshot_observed_at":"2026-08-11T16:39:24.237050Z","submitted_at":"2025-05-23T22:39:10Z","title":"Rehabilitation Exercise Quality Assessment and Feedback Generation Using Large Language Models with Prompt Engineering","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T14:35:16.656747Z"},"links":{"citing_paper":"/paper/2505.18412"},"observation_digest":"sha256:afe07880887d0f1cadd4c0a209642a82341908a1f1ae5e171a9b9cf9ae935d0b","observation_id":"e46788e6-7f9b-40ba-be62-631ffdc58bce","resolution":{"observed_at":"2026-08-07T14:35:18.489779Z","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":"2026-08-07T14:35:18.205645Z","title":"Language models are few-shot learners,","venue":null,"work_id":"a4e3a1a9-1cd4-4cad-8260-527caeade84c","year":1901},"citing_paper":{"arxiv_id":"2505.18412","last_updated":"2025-05-23T22:39:10Z","snapshot_observed_at":"2026-08-11T16:39:24.237050Z","submitted_at":"2025-05-23T22:39:10Z","title":"Rehabilitation Exercise Quality Assessment and Feedback Generation Using Large Language Models with Prompt Engineering","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T14:35:16.750851Z"},"links":{"citing_paper":"/paper/2505.18412"},"observation_digest":"sha256:ba2ecbeff21f8f5e296904608293d6c59ca0c2967d943763d9997d7e82d25a1a","observation_id":"801fe0b6-7143-4903-a44f-c01c04eba680","resolution":{"observed_at":"2026-08-07T14:35:18.294364Z","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":"2302.13971","last_updated":"2023-02-27T17:11:15Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-02-27T17:11:15Z","title":"LLaMA: Open and Efficient Foundation Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.13971","snapshot_observed_at":"2026-08-07T14:35:16.828160Z","title":"Llama: Open and efficient foundation language models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.18412","last_updated":"2025-05-23T22:39:10Z","snapshot_observed_at":"2026-08-11T16:39:24.237050Z","submitted_at":"2025-05-23T22:39:10Z","title":"Rehabilitation Exercise Quality Assessment and Feedback Generation Using Large Language Models with Prompt Engineering","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T14:35:16.828160Z"},"links":{"cited_paper":"/paper/2302.13971","citing_paper":"/paper/2505.18412"},"observation_digest":"sha256:c4b9b93f87946eb5a9d273e3072c6a22e7a3ea72edb168e69f698bbea5b330ad","observation_id":"386daf4a-f2c2-407a-b7d1-c888dcb1c622","resolution":{"observed_at":"2026-08-07T14:35:16.828160Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.13063","last_updated":"2024-03-17T04:38:48Z","snapshot_observed_at":"2026-07-06T15:45:39.649725Z","submitted_at":"2023-06-22T17:31:44Z","title":"Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.13063","snapshot_observed_at":"2026-08-07T14:35:16.896409Z","title":"Can llms express their uncertainty? an empirical evaluation of confidence elicitation in llms,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.18412","last_updated":"2025-05-23T22:39:10Z","snapshot_observed_at":"2026-08-11T16:39:24.237050Z","submitted_at":"2025-05-23T22:39:10Z","title":"Rehabilitation Exercise Quality Assessment and Feedback Generation Using Large Language Models with Prompt Engineering","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T14:35:16.896409Z"},"links":{"cited_paper":"/paper/2306.13063","citing_paper":"/paper/2505.18412"},"observation_digest":"sha256:3930373c02605cec69d5223ce247850396ba0cc7eb23eaf0950ca48cd11bbf1b","observation_id":"3f53881a-d9c9-4898-abb4-a99ffcc68626","resolution":{"observed_at":"2026-08-07T14:35:16.896409Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.03441","last_updated":"2024-06-05T16:35:30Z","snapshot_observed_at":"2026-08-12T23:49:25.575651Z","submitted_at":"2024-06-05T16:35:30Z","title":"Cycles of Thought: Measuring LLM Confidence through Stable Explanations","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.03441","snapshot_observed_at":"2026-08-07T14:35:16.971038Z","title":"Cycles of thought: Measuring llm confidence through stable explanations,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.18412","last_updated":"2025-05-23T22:39:10Z","snapshot_observed_at":"2026-08-11T16:39:24.237050Z","submitted_at":"2025-05-23T22:39:10Z","title":"Rehabilitation Exercise Quality Assessment and Feedback Generation Using Large Language Models with Prompt Engineering","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T14:35:16.971038Z"},"links":{"cited_paper":"/paper/2406.03441","citing_paper":"/paper/2505.18412"},"observation_digest":"sha256:ee179c7017d2eeba0f11619fd18a409bd7b416a642cb35dab25f948b2327c45c","observation_id":"73ed5d5e-3626-4220-bf1e-2b96c5fb59f3","resolution":{"observed_at":"2026-08-07T14:35:16.971038Z","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":"2026-08-07T14:35:18.049127Z","title":"Chain-of-thought prompting elicits reasoning in large language models,","venue":null,"work_id":"88a641f5-938a-46e9-a624-70b785f140a9","year":2022},"citing_paper":{"arxiv_id":"2505.18412","last_updated":"2025-05-23T22:39:10Z","snapshot_observed_at":"2026-08-11T16:39:24.237050Z","submitted_at":"2025-05-23T22:39:10Z","title":"Rehabilitation Exercise Quality Assessment and Feedback Generation Using Large Language Models with Prompt Engineering","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T14:35:17.046598Z"},"links":{"citing_paper":"/paper/2505.18412"},"observation_digest":"sha256:fab338f5e87fbaca2a5470b7a663946d997698dc85bf67fb0329ac715f46f6dd","observation_id":"1b3e0dbd-685b-4f37-a798-8d432b91e8fd","resolution":{"observed_at":"2026-08-07T14:35:18.109190Z","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":"2026-08-07T14:35:17.877916Z","title":"Probabilistic medical predictions of large language models,","venue":null,"work_id":"100c7e42-a2b1-4f5a-a758-c63e7a4f3e63","year":2024},"citing_paper":{"arxiv_id":"2505.18412","last_updated":"2025-05-23T22:39:10Z","snapshot_observed_at":"2026-08-11T16:39:24.237050Z","submitted_at":"2025-05-23T22:39:10Z","title":"Rehabilitation Exercise Quality Assessment and Feedback Generation Using Large Language Models with Prompt Engineering","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T14:35:17.115125Z"},"links":{"citing_paper":"/paper/2505.18412"},"observation_digest":"sha256:603f24a2a5893c2811fc1d6e4b910c6f6b221324b6a4b1a775e70c1f1b06b8ac","observation_id":"26b2fe8a-ed10-453b-864f-2fb5a3ebb80b","resolution":{"observed_at":"2026-08-07T14:35:17.953895Z","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":"2026-08-07T14:35:17.679389Z","title":"Role play with large language mod- els,","venue":null,"work_id":"a7fca597-b154-4b28-be0b-95edeaef7cb5","year":2023},"citing_paper":{"arxiv_id":"2505.18412","last_updated":"2025-05-23T22:39:10Z","snapshot_observed_at":"2026-08-11T16:39:24.237050Z","submitted_at":"2025-05-23T22:39:10Z","title":"Rehabilitation Exercise Quality Assessment and Feedback Generation Using Large Language Models with Prompt Engineering","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T14:35:17.185039Z"},"links":{"citing_paper":"/paper/2505.18412"},"observation_digest":"sha256:e7aa11ae4eba6840cd763aff4a61fe0c67efc8749cda49eaeb35d6a30a82c916","observation_id":"a7804cab-1e24-49a0-a8df-225a91900e99","resolution":{"observed_at":"2026-08-07T14:35:17.772975Z","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":"2026-08-07T14:35:17.494665Z","title":"Gpt-4o announcement,","venue":null,"work_id":"585285b8-9028-4c38-8a3e-138ef04128ff","year":2024},"citing_paper":{"arxiv_id":"2505.18412","last_updated":"2025-05-23T22:39:10Z","snapshot_observed_at":"2026-08-11T16:39:24.237050Z","submitted_at":"2025-05-23T22:39:10Z","title":"Rehabilitation Exercise Quality Assessment and Feedback Generation Using Large Language Models with Prompt Engineering","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T14:35:17.269124Z"},"links":{"citing_paper":"/paper/2505.18412"},"observation_digest":"sha256:89200d81e1fc263f342e50bb1c3d202ced5320672b20acc9b19bada94fe6fc7e","observation_id":"9c81f546-5e1e-49b7-bb40-0e68761a5b28","resolution":{"observed_at":"2026-08-07T14:35:17.561887Z","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":"2403.09972","last_updated":"2024-09-27T08:22:21Z","snapshot_observed_at":"2026-08-13T00:53:48.384402Z","submitted_at":"2024-03-15T02:38:26Z","title":"Think Twice Before Trusting: Self-Detection for Large Language Models through Comprehensive Answer Reflection","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.09972","snapshot_observed_at":"2026-08-07T14:35:17.349932Z","title":"Think twice be- fore assure: Confidence estimation for large language models through reflection on multiple answers,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.18412","last_updated":"2025-05-23T22:39:10Z","snapshot_observed_at":"2026-08-11T16:39:24.237050Z","submitted_at":"2025-05-23T22:39:10Z","title":"Rehabilitation Exercise Quality Assessment and Feedback Generation Using Large Language Models with Prompt Engineering","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T14:35:17.349932Z"},"links":{"cited_paper":"/paper/2403.09972","citing_paper":"/paper/2505.18412"},"observation_digest":"sha256:3142afa9309e5fc246bd16dec5d650a4fa2e6d7fa82b2b77806321ff33347655","observation_id":"5dd206a4-0bde-42cc-9853-86c454382b9c","resolution":{"observed_at":"2026-08-07T14:35:17.349932Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2505.18412","last_updated":"2025-05-23T22:39:10Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-11T16:39:24.237050Z","submitted_at":"2025-05-23T22:39:10Z","title":"Rehabilitation Exercise Quality Assessment and Feedback Generation Using Large Language Models with Prompt Engineering"},"reference_resolution":{"displayed":41,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":7,"verified_exact":0,"verified_fuzzy":34},"total_outbound_references":41},"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 15 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2505.18412."}