4 papers
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Guibin Zhang, Hejia Geng, Xiaohang Yu +22
The emergence of agentic reinforcement learning (Agentic RL) marks a paradigm shift from conventional reinforcement learning applied to large language models (LLM RL), reframing LL…
Khan-GCL: Kolmogorov-Arnold Network Based Graph Contrastive Learning with Hard Negatives
Zihu Wang, Boxun Xu, Hejia Geng +1
Graph contrastive learning (GCL) has demonstrated great promise for learning generalizable graph representations from unlabeled data. However, conventional GCL approaches face two…
ReSo: A Reward-driven Self-organizing LLM-based Multi-Agent System for Reasoning Tasks
Heng Zhou, Hejia Geng, Xiangyuan Xue +5
Multi-agent systems (MAS) have emerged as a promising approach for enhancing the reasoning capabilities of large language models in complex problem-solving; however, current MAS fr…
DS2TA: Denoising Spiking Transformer with Attenuated Spatiotemporal Attention
Boxun Xu, Hejia Geng, Yuxuan Yin +1
Vision Transformers (ViT) are current high-performance models of choice for various vision applications. Recent developments have given rise to biologically inspired spiking transf…