42 citations · 43 across the 22 of their papers we have counts for
7 papers · 1 filter
Population-Aligned Persona Generation for LLM-based Social Simulation
Zhengyu Hu, Jianxun Lian, Zheyuan Xiao +7
Recent advances in large language models (LLMs) have enabled human-like social simulations at unprecedented scale and fidelity, offering new opportunities for computational social…
GraphFedMIG: Tackling Class Imbalance in Federated Graph Learning via Mutual Information-Guided Generation
Xinrui Li, Qilin Fan, Tianfu Wang +3
Federated graph learning (FGL) enables multiple clients to collaboratively train powerful graph neural networks without sharing their private, decentralized graph data. Inherited f…
Virne: A Comprehensive Benchmark for RL-based Network Resource Allocation in NFV
Tianfu Wang, Liwei Deng, Xi Chen +7
Resource allocation (RA) is critical to efficient service deployment in Network Function Virtualization (NFV), a transformative networking paradigm. Recently, deep Reinforcement Le…
Unveiling the Learning Mind of Language Models: A Cognitive Framework and Empirical Study
Zhengyu Hu, Jianxun Lian, Zheyuan Xiao +5
Large language models (LLMs) have shown impressive capabilities across tasks such as mathematics, coding, and reasoning, yet their learning ability, which is crucial for adapting t…
CoderAgent: Simulating Student Behavior for Personalized Programming Learning with Large Language Models
Yi Zhan, Qi Liu, Weibo Gao +5
Personalized programming tutoring, such as exercise recommendation, can enhance learners' efficiency, motivation, and outcomes, which is increasingly important in modern digital ed…
A Framework for Benchmarking and Aligning Task-Planning Safety in LLM-Based Embodied Agents
Yuting Huang, Leilei Ding, Zhipeng Tang +5
Large Language Models (LLMs) exhibit substantial promise in enhancing task-planning capabilities within embodied agents due to their advanced reasoning and comprehension. However,…
LLM-powered Multi-agent Framework for Goal-oriented Learning in Intelligent Tutoring System
Tianfu Wang, Yi Zhan, Jianxun Lian +5
Intelligent Tutoring Systems (ITSs) have revolutionized education by offering personalized learning experiences. However, as goal-oriented learning, which emphasizes efficiently ac…