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[2602.22514] SignVLA: A Gloss-Free Vision-Language-Action Framework for Real-Time Sign Language-Guided Robotic Manipulation
Summary
The paper presents SignVLA, a novel gloss-free Vision-Language-Action framework for real-time robotic manipulation guided by sign language, enhancing human-robot interaction.
Why It Matters
This research is significant as it addresses the limitations of traditional sign language recognition systems by eliminating the need for gloss annotations, thereby improving the efficiency and naturalness of human-robot communication. It also opens pathways for more inclusive technology that can better serve the deaf and hard-of-hearing communities.
Key Takeaways
- Introduces a gloss-free framework for sign language-driven robotic interaction.
- Reduces annotation costs and information loss compared to traditional methods.
- Focuses on real-time finger-spelling for reliable robotic control.
- Demonstrates effective grounding of sign-derived instructions into robotic actions.
- Supports future integration of advanced sign language models for improved understanding.
Computer Science > Robotics arXiv:2602.22514 (cs) [Submitted on 26 Feb 2026] Title:SignVLA: A Gloss-Free Vision-Language-Action Framework for Real-Time Sign Language-Guided Robotic Manipulation Authors:Xinyu Tan, Ningwei Bai, Harry Gardener, Zhengyang Zhong, Luoyu Zhang, Liuhaichen Yang, Zhekai Duan, Monkgogi Galeitsiwe, Zezhi Tang View a PDF of the paper titled SignVLA: A Gloss-Free Vision-Language-Action Framework for Real-Time Sign Language-Guided Robotic Manipulation, by Xinyu Tan and 8 other authors View PDF HTML (experimental) Abstract:We present, to our knowledge, the first sign language-driven Vision-Language-Action (VLA) framework for intuitive and inclusive human-robot interaction. Unlike conventional approaches that rely on gloss annotations as intermediate supervision, the proposed system adopts a gloss-free paradigm and directly maps visual sign gestures to semantic instructions. This design reduces annotation cost and avoids the information loss introduced by gloss representations, enabling more natural and scalable multimodal interaction. In this work, we focus on a real-time alphabet-level finger-spelling interface that provides a robust and low-latency communication channel for robotic control. Compared with large-scale continuous sign language recognition, alphabet-level interaction offers improved reliability, interpretability, and deployment feasibility in safety-critical embodied environments. The proposed pipeline transforms continuous gesture streams...