5 papers
DiffuSpeech: Silent Thought, Spoken Answer via Unified Speech-Text Diffusion
Yuxuan Lou, Ziming Wu, Yaochen Wang +6
Current speech language models generate responses directly without explicit reasoning, leading to errors that cannot be corrected once audio is produced. We introduce \textbf{``Sil…
MoST: Mixing Speech and Text with Modality-Aware Mixture of Experts
Yuxuan Lou, Kai Yang, Yang You
We present MoST (Mixture of Speech and Text), a novel multimodal large language model that seamlessly integrates speech and text processing through our proposed Modality-Aware Mixt…
Memory Transfer Planning: LLM-driven Context-Aware Code Adaptation for Robot Manipulation
Tomoyuki Kagaya, Subramanian Lakshmi, Yuxuan Lou +6
Large language models (LLMs) are increasingly explored in robot manipulation, but many existing methods struggle to adapt to new environments. Many systems require either environme…
MoNE: Replacing Redundant Experts with Lightweight Novices for Structured Pruning of MoE
Geng Zhang, Yuxuan Han, Yuxuan Lou +3
Mixture-of-Experts (MoE) enables efficient scaling of large language models by activating only a subset of experts per input token. However, deploying MoE-based models incurs signi…
EnvBridge: Bridging Diverse Environments with Cross-Environment Knowledge Transfer for Embodied AI
Tomoyuki Kagaya, Yuxuan Lou, Thong Jing Yuan +8
In recent years, Large Language Models (LLMs) have demonstrated high reasoning capabilities, drawing attention for their applications as agents in various decision-making processes…