Peng Li

GAUSS: Graph-Assisted Uncertainty Quantification using Structure and Semantics for Long-Form Generation in LLMs

High-dimensional Bayesian Optimization via Semi-supervised Learning with Optimized Unlabeled Data Sampling

Composing Recurrent Spiking Neural Networks using Locally-Recurrent Motifs and Risk-Mitigating Architectural Optimization

UPAR: A Kantian-Inspired Prompting Framework for Enhancing Large Language Model Capabilities

DISTA: DENOISING SPIKING TRANSFORMER WITH INTRINSIC PLASTICITY AND SPATIOTEMPORAL ATTENTION

Systolic Array Acceleration of Spiking Neural Networks with Application-Independent Split-Time Temporal Coding