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Exploiting instance-label dynamics through reciprocal anchored contrastive learning for few-shot relation extraction.

Neural networks : the official journal of the International Neural Network Society
In the domain of Few-shot Relation Extraction (FSRE), the primary objective is to distill relational facts from limited labeled datasets. This task has recently witnessed significant advancements through the integration of Pre-trained Language Models...

Memory flow-controlled knowledge tracing with three stages.

Neural networks : the official journal of the International Neural Network Society
Knowledge Tracing (KT), as a pivotal technology in intelligent education systems, analyzes students' learning data to infer their knowledge acquisition and predict their future performance. Recent advancements in KT recognize the importance of memory...

A novel voice in head actor critic reinforcement learning with human feedback framework for enhanced robot navigation.

Scientific reports
This work presents a novel Voice in Head (ViH) framework, that integrates Large Language Models (LLMs) and the power of semantic understanding to enhance robotic navigation and interaction within complex environments. Our system strategically combine...

Minimal Neural Network Conditions for Encoding Future Interactions.

International journal of neural systems
Space and time are fundamental attributes of the external world. Deciphering the brain mechanisms involved in processing the surrounding environment is one of the main challenges in neuroscience. This is particularly defiant when situations change ra...

Self-triggered neural tracking control for discrete-time nonlinear systems via adaptive critic learning.

Neural networks : the official journal of the International Neural Network Society
In this paper, a novel self-triggered optimal tracking control method is developed based on the online action-critic technique for discrete-time nonlinear systems. First, an augmented plant is constructed by integrating the system state with the refe...

How adaptive social robots influence cognitive, emotional, and self-regulated learning.

Scientific reports
As educational environments become more diverse, adaptive technologies like social robots hold promise for providing individual support to learners. This study investigated the role of adaptive teaching of a robot on students' learning outcomes, emot...

An accurate and fast learning approach in the biologically spiking neural network.

Scientific reports
Computations adapted from the interactions of neurons in the nervous system have the potential to be a strong foundation for building computers with cognitive functions including decision-making, generalization, and real-time learning. In this contex...

Memristor-based circuit design of interweaving mechanism of emotional memory in a hippocamp-brain emotion learning model.

Neural networks : the official journal of the International Neural Network Society
Endowing robots with human-like emotional and cognitive abilities has garnered widespread attention, driving deep investigations into the complexities of these processes. However, few studies have examined the intricate circuits that govern the inter...

Temporal Contrastive Learning through implicit non-equilibrium memory.

Nature communications
The backpropagation method has enabled transformative uses of neural networks. Alternatively, for energy-based models, local learning methods involving only nearby neurons offer benefits in terms of decentralized training, and allow for the possibili...

Learning in Wilson-Cowan Model for Metapopulation.

Neural computation
The Wilson-Cowan model for metapopulation, a neural mass network model, treats different subcortical regions of the brain as connected nodes, with connections representing various types of structural, functional, or effective neuronal connectivity be...