Jindou Chen
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View article: Children explore conservatively when learning novel word extensions
Children explore conservatively when learning novel word extensions Open
Children are active, curious learners. How might children’s curiosity shape their curriculum during word learning? Past research suggests that children’s tendency to explore can lead them to discover novel information during learning. This…
View article: Children explore conservatively when learning novel word extensions
Children explore conservatively when learning novel word extensions Open
Children are active, curious learners. How might children’s curiosity shape their curriculum during word learning? Past research suggests that children’s tendency to explore can lead them to discover novel information during learning. This…
View article: Blockchain and FEF-Based Lightweight Anonymous Authentication Protocol for Wireless Medical Sensor Networks
Blockchain and FEF-Based Lightweight Anonymous Authentication Protocol for Wireless Medical Sensor Networks Open
Authentication ensures the privacy of patients by enabling access control within wireless medical sensor networks. However, many schemes do not consider the resource-constrained environments, making those protocols unusable. Meanwhile, sen…
View article: Global prototype distillation for heterogeneous federated learning
Global prototype distillation for heterogeneous federated learning Open
Federated learning is a distributed machine learning paradigm where the goal is to collaboratively train a high quality global model while private training data remains local over distributed clients. However, heterogenous data distributio…
View article: FedGPD: Global Prototype Distillation InHeterogeneous Federated Learning
FedGPD: Global Prototype Distillation InHeterogeneous Federated Learning Open
Federated learning is a distributed machine learning paradigm where the goal is to collaboratively train a high quality globalmodel while private training data remains local over distributed clients. However, heterogenous data distribution…
View article: Can Large Language Models Serve as Rational Players in Game Theory? A Systematic Analysis
Can Large Language Models Serve as Rational Players in Game Theory? A Systematic Analysis Open
Game theory, as an analytical tool, is frequently utilized to analyze human behavior in social science research. With the high alignment between the behavior of Large Language Models (LLMs) and humans, a promising research direction is to …
View article: Can Large Language Models Serve as Rational Players in Game Theory? A Systematic Analysis
Can Large Language Models Serve as Rational Players in Game Theory? A Systematic Analysis Open
Game theory, as an analytical tool, is frequently utilized to analyze human behavior in social science research. With the high alignment between the behavior of Large Language Models (LLMs) and humans, a promising research direction is to …
View article: Task-Level Thinking Steps Help Large Language Models for Challenging Classification Task
Task-Level Thinking Steps Help Large Language Models for Challenging Classification Task Open
Large language models (LLMs) have shown incredible performance on many tasks such as dialogue generation, commonsense reasoning and question answering. In-context learning (ICL) is an important paradigm for adapting LLMs to the downstream …