activity
20242026
collaborators

7 papers

cs.RO2026

FSD-VLN: Fast-Slow Dual-System Modeling for Aerial Long-Horizon Vision-Language Navigation

Xueke Zhu, Qingyan Meng, Liutao Yu +4

Vision-Language Navigation (VLN) enables UAV autonomous navigation in unknown environments by mapping language instructions to real-time visual inputs. Compared with GPS-dependent…

cs.SD2026

SpikCommander: A High-performance Spiking Transformer with Multi-view Learning for Efficient Speech Command Recognition

Jiaqi Wang, Liutao Yu, Xiongri Shen +6

Spiking neural networks (SNNs) offer a promising path toward energy-efficient speech command recognition (SCR) by leveraging their event-driven processing paradigm. However, existi…

cs.NE2025

Spikingformer: A Key Foundation Model for Spiking Neural Networks

Chenlin Zhou, Liutao Yu, Zhaokun Zhou +5

Spiking neural networks (SNNs) offer a promising energy-efficient alternative to artificial neural networks, due to their event-driven spiking computation. However, some foundation…

cs.NE2025

Time-Evolving Dynamical System for Learning Latent Representations of Mouse Visual Neural Activity

Liwei Huang, ZhengYu Ma, Liutao Yu +2

Seeking high-quality representations with latent variable models (LVMs) to reveal the intrinsic correlation between neural activity and behavior or sensory stimuli has attracted mu…

cs.LG2024

Efficient Speech Command Recognition Leveraging Spiking Neural Network and Curriculum Learning-based Knowledge Distillation

Jiaqi Wang, Liutao Yu, Liwei Huang +6

The intrinsic dynamics and event-driven nature of spiking neural networks (SNNs) make them excel in processing temporal information by naturally utilizing embedded time sequences a…

cs.NE2024

Long-Range Feedback Spiking Network Captures Dynamic and Static Representations of the Visual Cortex under Movie Stimuli

Liwei Huang, Zhengyu Ma, Liutao Yu +2

Deep neural networks (DNNs) are widely used models for investigating biological visual representations. However, existing DNNs are mostly designed to analyze neural responses to st…