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cs.AI2026
iFLYTEK-Embodied-Omni Technical Report
Yuan Zhang, Jingfei Ni, Guanchen Lu +12
General-purpose embodied agents must understand multimodal instructions, anticipate how their environment will evolve, and produce precise control actions over extended horizons. E…
cs.AI2024
CLSP: High-Fidelity Contrastive Language-State Pre-training for Agent State Representation
Fuxian Huang, Qi Zhang, Shaopeng Zhai +6
With the rapid development of artificial intelligence, multimodal learning has become an important research area. For intelligent agents, the state is a crucial modality to convey…
cs.AI2024
Building Open-Ended Embodied Agent via Language-Policy Bidirectional Adaptation
Shaopeng Zhai, Jie Wang, Tianyi Zhang +6
Building embodied agents on integrating Large Language Models (LLMs) and Reinforcement Learning (RL) have revolutionized human-AI interaction: researchers can now leverage language…