8 papers
HELIX: Model-Harness Co-evolution for Recursive Self-Improvement
Tianyu Fan, Chao Huang
Scaling agent capability has largely focused on improving the model, yet an interactive agent acts through a runtime harness that mediates context, tools, control flow, and stoppin…
Uncertainty-Aware Token Importance Estimation in Spiking Transformers
Wenxuan Liu, Zecheng Hao, Tong Bu +2
Spiking transformers have shown strong potential for neuromorphic vision, yet their token processing across multiple spiking steps still introduces substantial redundancy and infer…
PredNext: Explicit Cross-View Temporal Prediction for Unsupervised Learning in Spiking Neural Networks
Yiting Dong, Jianhao Ding, Zijie Xu +3
Spiking Neural Networks (SNNs), with their temporal processing capabilities and biologically plausible dynamics, offer a natural platform for unsupervised representation learning.…
Proxy Target: Bridging the Gap Between Discrete Spiking Neural Networks and Continuous Control
Zijie Xu, Tong Bu, Zecheng Hao +2
Spiking Neural Networks (SNNs) offer low-latency and energy-efficient decision making on neuromorphic hardware, making them attractive for Reinforcement Learning (RL) in resource-c…
General Self-Prediction Enhancement for Spiking Neurons
Zihan Huang, Zijie Xu, Yihan Huang +7
Spiking Neural Networks (SNNs) are highly energy-efficient due to event-driven, sparse computation, but their training is challenged by spike non-differentiability and trade-offs a…
Differential Coding for Training-Free ANN-to-SNN Conversion
Zihan Huang, Wei Fang, Tong Bu +6
Spiking Neural Networks (SNNs) exhibit significant potential due to their low energy consumption. Converting Artificial Neural Networks (ANNs) to SNNs is an efficient way to achiev…