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Found 7 papers, 3 papers with code
Solution-oriented Agent-based Models Generation with Verifier-assisted Iterative In-context Learning
In SAGE, we introduce an semi-structured conceptual representation expliciting the intricate structures of ABMs and an objective representation to guide LLMs in modeling scenarios and proposing hypothetical solutions through in-context learning.
General Automatic Solution Generation of Social Problems
Given the escalating intricacy and multifaceted nature of contemporary social systems, manually generating solutions to address pertinent social issues has become a formidable task.
Dance of SNN and ANN: Solving binding problem by combining spike timing and reconstructive attention
In this paper, we propose a brain-inspired hybrid neural network (HNN) that introduces temporal binding theory originated from neuroscience into ANNs by integrating spike timing dynamics (via spiking neural networks, SNNs) with reconstructive attention (by ANNs).
Approximate synchronization of coupled multi-valued logical networks
According to the initial state set from which both systems start, two kinds of approximate synchronization problem, local approximate synchronization and global approximate synchronization, are proposed for the first time.
Towards Both Accurate and Robust Neural Networks without Extra Data
The AFS model achieves a benign accuracy improvement of ~6% on CIFAR-10 and ~10% on CIFAR-100 with comparable or even stronger robustness than the state-of-the-art adversarial training methods.
Brain-inspired global-local learning incorporated with neuromorphic computing
We demonstrate the advantages of this model in multiple different tasks, including few-shot learning, continual learning, and fault-tolerance learning in neuromorphic vision sensors.
Adversarial symmetric GANs: bridging adversarial samples and adversarial networks
Generative adversarial networks have achieved remarkable performance on various tasks but suffer from training instability.
