https://ygao36buffalo.github.io/tags/imwut/IMWUTHugo Blox Builder (https://hugoblox.com)en-usSat, 04 Jul 2026 00:30:00 +0800https://ygao36buffalo.github.io/media/icon_hu7729264130191091259.pnghttps://ygao36buffalo.github.io/tags/imwut/https://ygao36buffalo.github.io/post/imwut2026-twopapers/Sat, 04 Jul 2026 00:30:00 +0800https://ygao36buffalo.github.io/post/imwut2026-twopapers/ <details class="print:hidden xl:hidden" open> <summary>Table of Contents</summary> <div class="text-sm"> <nav id="TableOfContents"> <ul> <li><a href="#overview">Overview</a></li> </ul> </nav> </div> </details> <h2 id="overview">Overview</h2> <p>We are excited to share that two of our papers have been accepted to <strong>Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (ACM IMWUT)</strong> and will be presented at <strong>UbiComp 2026</strong>.</p> <ul> <li><strong>HoloHand: Bidirectional Motion–Language Modeling for Semantic Hand Interaction in Immersive Environments</strong></li> <li><strong>EmbodiedRecall: A Ring-to-Glasses System for Preserving Valuable, Fleeting Moments in Daily Activities</strong></li> </ul> <p>More details will be added as the final publication information and conference program become available.</p>https://ygao36buffalo.github.io/post/hmotiongpt2026/Wed, 17 Jun 2026 00:00:00 +0000https://ygao36buffalo.github.io/post/hmotiongpt2026/ <details class="print:hidden xl:hidden" open> <summary>Table of Contents</summary> <div class="text-sm"> <nav id="TableOfContents"> <ul> <li><a href="#overview">Overview</a></li> </ul> </nav> </div> </details> <h2 id="overview">Overview</h2> <p>We are excited to share that our paper, <strong>HMotionGPT: Aligning Hand Motions and Natural Language for Activity Understanding with Smart Rings</strong>, has been accepted to <strong>Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (ACM IMWUT)</strong>.</p> <p>The paper will be presented at <strong>UbiComp 2026</strong> in <strong>Shanghai, China</strong>.</p> <p>HMotionGPT studies how smart-ring motion signals can be aligned with natural language to support hand-centric activity understanding, including activity classification, motion captioning, and instruction-following interaction with wearable sensing data.</p> <p>Publication page: <a href="https://ygao36buffalo.github.io/publication/hmotiongpt-2026/">HMotionGPT</a></p> <p>Project page: <a href="https://github.com/SCUT-HAI/HMotionGPT" target="_blank" rel="noopener">HMotionGPT Open-Source Project</a></p>