6 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…
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…
AlphaMaze: Enhancing Large Language Models' Spatial Intelligence via GRPO
Alan Dao, Dinh Bach Vu
Large Language Models (LLMs) have demonstrated impressive capabilities in language processing, yet they often struggle with tasks requiring genuine visual spatial reasoning. In thi…