6 papers
VoLN: Vision-Only Long-Horizon Navigation---Paradigm, Benchmark, and Method
Jiabin Lou, Haopeng Wang, Yuanshuai Wang +6
Vision-and-Language Navigation (VLN) enables embodied agents to follow natural-language instructions. However, route-level instructions commonly encode spatial priors, such as orie…
AERIS: Aerial-Edge Role-Driven Intelligence at Runtime via Orchestrated Language-Model Swarm
Jiabin Lou, Haopeng Wang, Xinyu Liu +3
Integrating large language models into robotic systems holds promise for enhancing autonomy, yet practical deployment remains constrained by strict heartbeat-constrained scheduling…
FBOS-RL: Feedback-Driven Bi-Objective Synergistic Reinforcement Learning
Xikai Zhang, Yongzhi Li, Likang Xiao +6
Reinforcement learning has become a cornerstone for aligning and unlocking the reasoning capabilities of large-scale models. At its core, the training loop of GRPO and its variants…
Learning to Adapt SFT Data for Better Reasoning Generalization
Lisong Sun, Li Wang, Chen Zhang +4
Large language models (LLMs) have achieved remarkable progress, with post-training playing a crucial role in enhancing their reasoning capabilities. Among post-training paradigms,…
Symmetry-Guided Multi-Agent Inverse Reinforcement Learning
Yongkai Tian, Yirong Qi, Xin Yu +2
In robotic systems, the performance of reinforcement learning depends on the rationality of predefined reward functions. However, manually designed reward functions often lead to p…
Neural Algorithmic Reasoners informed Large Language Model for Multi-Agent Path Finding
Pu Feng, Size Wang, Yuhong Cao +3
The development and application of large language models (LLM) have demonstrated that foundational models can be utilized to solve a wide array of tasks. However, their performance…