15 citations · 24 across the 9 of their papers we have counts for
9 papers
ERR+: Sequential Entropy Resolution for Efficient and Decisive LLM Reasoning
Xin Jiang, Minhao Wang, Wen Wu +4
Large reasoning models achieve strong performance on complex tasks by generating extended chain-of-thought (CoT) traces via reinforcement learning with verifiable rewards (RLVR). W…
RMoA: Optimizing Mixture-of-Agents through Diversity Maximization and Residual Compensation
Zhentao Xie, Chengcheng Han, Jinxin Shi +4
Although multi-agent systems based on large language models show strong capabilities on multiple tasks, they are still limited by high computational overhead, information loss, and…
A Survey on the Optimization of Large Language Model-based Agents
Shangheng Du, Jiabao Zhao, Jinxin Shi +4
With the rapid development of Large Language Models (LLMs), LLM-based agents have been widely adopted in various fields, becoming essential for autonomous decision-making and inter…
MindScope: Exploring cognitive biases in large language models through Multi-Agent Systems
Zhentao Xie, Jiabao Zhao, Yilei Wang +4
Detecting cognitive biases in large language models (LLMs) is a fascinating task that aims to probe the existing cognitive biases within these models. Current methods for detecting…
FairMonitor: A Dual-framework for Detecting Stereotypes and Biases in Large Language Models
Yanhong Bai, Jiabao Zhao, Jinxin Shi +3
Detecting stereotypes and biases in Large Language Models (LLMs) is crucial for enhancing fairness and reducing adverse impacts on individuals or groups when these models are appli…
A Survey of Explainable Knowledge Tracing
Yanhong Bai, Jiabao Zhao, Tingjiang Wei +2
With the long term accumulation of high quality educational data, artificial intelligence has shown excellent performance in knowledge tracing. However, due to the lack of interpre…
A Soft Contrastive Learning-based Prompt Model for Few-shot Sentiment Analysis
Jingyi Zhou, Jie Zhou, Jiabao Zhao +5
Few-shot text classification has attracted great interest in both academia and industry due to the lack of labeled data in many fields. Different from general text classification (…
CGMI: Configurable General Multi-Agent Interaction Framework
Shi Jinxin, Zhao Jiabao, Wang Yilei +3
Benefiting from the powerful capabilities of large language models (LLMs), agents based on LLMs have shown the potential to address domain-specific tasks and emulate human behavior…
FairMonitor: A Four-Stage Automatic Framework for Detecting Stereotypes and Biases in Large Language Models
Yanhong Bai, Jiabao Zhao, Jinxin Shi +3
Detecting stereotypes and biases in Large Language Models (LLMs) can enhance fairness and reduce adverse impacts on individuals or groups when these LLMs are applied. However, the…