7 papers
Lucy: edgerunning agentic web search on mobile with machine generated task vectors
Alan Dao, Dinh Bach Vu, Alex Nguyen +1
Small language models (SLMs) are inherently limited in knowledge-intensive tasks due to their constrained capacity. While test-time computation offers a path to enhanced performanc…
Jan-nano Technical Report
Alan Dao, Dinh Bach Vu
Most language models face a fundamental tradeoff where powerful capabilities require substantial computational resources. We shatter this constraint with Jan-nano, a 4B parameter l…
Speechless: Speech Instruction Training Without Speech for Low Resource Languages
Alan Dao, Dinh Bach Vu, Huy Hoang Ha +6
The rapid growth of voice assistants powered by large language models (LLM) has highlighted a need for speech instruction data to train these systems. Despite the abundance of spee…
Ichigo: Mixed-Modal Early-Fusion Realtime Voice Assistant
Alan Dao, Dinh Bach Vu, Huy Hoang Ha
Large Language Models (LLMs) have revolutionized natural language processing, but their application to speech-based tasks remains challenging due to the complexities of integrating…
AlphaSpace: Enabling Robotic Actions through Semantic Tokenization and Symbolic Reasoning
Alan Dao, Dinh Bach Vu, Bui Quang Huy
This paper presents AlphaSpace, a novel methodology designed to enhance the spatial reasoning capabilities of language models for robotic manipulation in 3D Cartesian space. AlphaS…
PoseLess: Depth-Free Vision-to-Joint Control via Direct Image Mapping with VLM
Alan Dao, Dinh Bach Vu, Tuan Le Duc Anh +1
This paper introduces PoseLess, a novel framework for robot hand control that eliminates the need for explicit pose estimation by directly mapping 2D images to joint angles using p…