most citedX-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs

3 citations · 4 across the 5 of their papers we have counts for

collaborators

11 papers

cs.RO2026

Advances and Innovations in the Multi-Agent Robotic System (MARS) Challenge

Li Kang, Heng Zhou, Xiufeng Song +41

Recent advancements in multimodal large language models and vision-languageaction models have significantly driven progress in Embodied AI. As the field transitions toward more com…

cs.CV2025

Actial: Activate Spatial Reasoning Ability of Multimodal Large Language Models

Xiaoyu Zhan, Wenxuan Huang, Hao Sun +11

Recent advances in Multimodal Large Language Models (MLLMs) have significantly improved 2D visual understanding, prompting interest in their application to complex 3D reasoning tas…

cs.CL2025

LatentEvolve: Self-Evolving Test-Time Scaling in Latent Space

Guibin Zhang, Fanci Meng, Guancheng Wan +5

Test-time Scaling (TTS) has been demonstrated to significantly enhance the reasoning capabilities of Large Language Models (LLMs) during the inference phase without altering model…

cs.CL2025

Eigen-1: Adaptive Multi-Agent Refinement with Monitor-Based RAG for Scientific Reasoning

Xiangru Tang, Wanghan Xu, Yujie Wang +13

Large language models (LLMs) have recently shown strong progress on scientific reasoning, yet two major bottlenecks remain. First, explicit retrieval fragments reasoning, imposing…

cs.CL2025

SciReasoner: Laying the Scientific Reasoning Ground Across Disciplines

Yizhou Wang, Chen Tang, Han Deng +29

We present a scientific reasoning foundation model that aligns natural language with heterogeneous scientific representations. The model is pretrained on a 206B-token corpus spanni…

cs.CL20251 cited

SSRL: Self-Search Reinforcement Learning

Yuchen Fan, Kaiyan Zhang, Heng Zhou +15

We investigate the potential of large language models (LLMs) to serve as efficient simulators for agentic search tasks in reinforcement learning (RL), thereby reducing dependence o…