6 papers · 1 filter
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…
ReZero: Enhancing LLM search ability by trying one-more-time
Alan Dao, Thinh Le
Retrieval-Augmented Generation (RAG) improves Large Language Model (LLM) performance on knowledge-intensive tasks but depends heavily on initial search query quality. Current metho…
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…
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…