activity
20232026
most citedMulti-Agent Systems for Robotic Autonomy with LLMs

1 citations · 2 across the 5 of their papers we have counts for

collaborators

7 papers

cs.AI2026

EvolvingBrain: An Adaptive Skill System for Multi-modal Agents Self-Evolution in Open Worlds

Runxuan Liu, Jingqi Shi, Baoxin Wang +10

Multi-modal agents have made significant progress in interacting with open worlds. However, their ability to self-evolve remains limited. Supervised fine-tuning enables imitation b…

cs.AI2026

SAKI: Maximal-Coupling-Routed Teacher Supervision for On-Policy Distillation

Miteto Wei, Xiaohan Wang, Zehao Chen +7

On-policy distillation (OPD) reduces train-test state mismatch by training a student on its own generated trajectories, but weak students may visit teacher-misaligned prefixes wher…

cs.SE2026

The Evolution of Tool Use in LLM Agents: From Single-Tool Call to Multi-Tool Orchestration

Haoyuan Xu, Chang Li, Xinyan Ma +12

Tool use enables large language models (LLMs) to access external information, invoke software systems, and act in digital environments beyond what can be solved from model paramete…

cs.SD2026

UniWhisper: Efficient Continual Multi-task Training for Robust Universal Audio Representation

Yuxuan Chen, Peize He, Haoyuan Yu +1

A universal audio representation should capture fine-grained speech cues and high-level semantics for environmental sounds and music in a single encoder. Existing encoders often ex…

cs.CV2025

MonitorVLM:A Vision Language Framework for Safety Violation Detection in Mining Operations

Jiang Wu, Sichao Wu, Yinsong Ma +4

Industrial accidents, particularly in high-risk domains such as surface and underground mining, are frequently caused by unsafe worker behaviors. Traditional manual inspection rema…

cs.RO2025★ 1 cited

Multi-Agent Systems for Robotic Autonomy with LLMs

Junhong Chen, Ziqi Yang, Haoyuan G Xu +2

Since the advent of Large Language Models (LLMs), various research based on such models have maintained significant academic attention and impact, especially in AI and robotics. In…

cs.RO2023★ 1 cited

Integrated Drill Boom Hole-Seeking Control via Reinforcement Learning

Haoqi Yan, Haoyuan Xu, Hongbo Gao +3

Intelligent drill boom hole-seeking is a promising technology for enhancing drilling efficiency, mitigating potential safety hazards, and relieving human operators. Most existing i…