{"id":3610,"date":"2025-09-20T21:42:33","date_gmt":"2025-09-20T21:42:33","guid":{"rendered":"https:\/\/172-234-197-23.ip.linodeusercontent.com\/?page_id=3610"},"modified":"2025-09-20T21:42:33","modified_gmt":"2025-09-20T21:42:33","slug":"openbench-ar","status":"publish","type":"page","link":"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/?page_id=3610","title":{"rendered":"OpenBench-AR"},"content":{"rendered":"\n<div data-wp-interactive=\"core\/file\" class=\"wp-block-file\"><object data-wp-bind--hidden=\"!state.hasPdfPreview\" hidden class=\"wp-block-file__embed\" data=\"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/wp-content\/uploads\/2025\/09\/paper_OpenBench\u2011AR.pdf\" type=\"application\/pdf\" style=\"width:100%;height:600px\" aria-label=\"Embed of paper_OpenBench\u2011AR.\"><\/object><a id=\"wp-block-file--media-6346992c-7e75-453d-8998-6ad558b0f010\" href=\"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/wp-content\/uploads\/2025\/09\/paper_OpenBench\u2011AR.pdf\">paper_OpenBench\u2011AR<\/a><a href=\"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/wp-content\/uploads\/2025\/09\/paper_OpenBench\u2011AR.pdf\" class=\"wp-block-file__button wp-element-button\" download aria-describedby=\"wp-block-file--media-6346992c-7e75-453d-8998-6ad558b0f010\">Download<\/a><\/div>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Research on radio-frequency (RF) sensing for augmented reality (AR) has produced a variety of prototypes\u2014from<br>RF-driven casualty triage to threat detection\u2014but the lack<br>of standardized datasets and evaluation frameworks hampers<br>reproducibility. Machine learning workflows are often fragmented and informal; datasets, code and configurations are<br>loosely coupled, making it difficult to trace experiments and<br>reproduce results [1]. Reproducibility requires capturing not just<br>data and code, but also the process and decisions behind an<br>experiment [2]. We introduce OpenBench-AR, an open-source<br>benchmark suite that provides standardized RF traces, JSON<br>metrics and LaTeX figure\/table autogeneration for RF-to-AR<br>systems. OpenBench-AR packages a client simulator, exporters<br>and a README.md that guide users through dataset reproduction<br>and one-command generation of evaluation figures. We demonstrate OpenBench-AR on prior RF-AR pipelines, showing how<br>researchers can reproduce latency, frame rate and power results<br>across hardware. Our artifact is ready for artifact evaluation<br>tracks at ReproNLP\/MLSys and systems demo workshops.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Research on radio-frequency (RF) sensing for augmented reality (AR) has produced a variety of prototypes\u2014fromRF-driven casualty triage to threat detection\u2014but the lackof standardized datasets and evaluation frameworks hampersreproducibility. Machine learning workflows are often fragmented and informal; datasets, code and configurations areloosely coupled, making it difficult to trace experiments andreproduce results [1]. Reproducibility requires capturing not&hellip;&nbsp;<\/p>\n","protected":false},"author":2,"featured_media":2676,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"neve_meta_sidebar":"","neve_meta_container":"","neve_meta_enable_content_width":"","neve_meta_content_width":0,"neve_meta_title_alignment":"","neve_meta_author_avatar":"","neve_post_elements_order":"","neve_meta_disable_header":"","neve_meta_disable_footer":"","neve_meta_disable_title":"","footnotes":""},"class_list":["post-3610","page","type-page","status-publish","has-post-thumbnail","hentry"],"_links":{"self":[{"href":"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/index.php?rest_route=\/wp\/v2\/pages\/3610","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=3610"}],"version-history":[{"count":0,"href":"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/index.php?rest_route=\/wp\/v2\/pages\/3610\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/index.php?rest_route=\/wp\/v2\/media\/2676"}],"wp:attachment":[{"href":"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=3610"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}