20 citations · 157 across the 47 of their papers we have counts for
9 papers · 1 filter
Large Language Model-Enhanced Algorithm Selection: Towards Comprehensive Algorithm Representation
Xingyu Wu, Yan Zhong, Jibin Wu +2
Algorithm selection, a critical process of automated machine learning, aims to identify the most suitable algorithm for solving a specific problem prior to execution. Mainstream al…
LC-TTFS: Towards Lossless Network Conversion for Spiking Neural Networks with TTFS Coding
Qu Yang, Malu Zhang, Jibin Wu +2
The biological neurons use precise spike times, in addition to the spike firing rate, to communicate with each other. The time-to-first-spike (TTFS) coding is inspired by such biol…
Delayed Memory Unit: Modelling Temporal Dependency Through Delay Gate
Pengfei Sun, Jibin Wu, Malu Zhang +2
Recurrent Neural Networks (RNNs) are widely recognized for their proficiency in modeling temporal dependencies, making them highly prevalent in sequential data processing applicati…
Typing to Listen at the Cocktail Party: Text-Guided Target Speaker Extraction
Xiang Hao, Jibin Wu, Jianwei Yu +2
Humans can easily isolate a single speaker from a complex acoustic environment, a capability referred to as the "Cocktail Party Effect." However, replicating this ability has been…
Spiking-LEAF: A Learnable Auditory front-end for Spiking Neural Networks
Zeyang Song, Jibin Wu, Malu Zhang +2
Brain-inspired spiking neural networks (SNNs) have demonstrated great potential for temporal signal processing. However, their performance in speech processing remains limited due…
Unleashing the Potential of Spiking Neural Networks for Sequential Modeling with Contextual Embedding
Xinyi Chen, Jibin Wu, Huajin Tang +2
The human brain exhibits remarkable abilities in integrating temporally distant sensory inputs for decision-making. However, existing brain-inspired spiking neural networks (SNNs)…
TC-LIF: A Two-Compartment Spiking Neuron Model for Long-Term Sequential Modelling
Shimin Zhang, Qu Yang, Chenxiang Ma +3
The identification of sensory cues associated with potential opportunities and dangers is frequently complicated by unrelated events that separate useful cues by long delays. As a…
Long Short-term Memory with Two-Compartment Spiking Neuron
Shimin Zhang, Qu Yang, Chenxiang Ma +3
The identification of sensory cues associated with potential opportunities and dangers is frequently complicated by unrelated events that separate useful cues by long delays. As a…
A Hybrid Neural Coding Approach for Pattern Recognition with Spiking Neural Networks
Xinyi Chen, Qu Yang, Jibin Wu +2
Recently, brain-inspired spiking neural networks (SNNs) have demonstrated promising capabilities in solving pattern recognition tasks. However, these SNNs are grounded on homogeneo…