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cs.RO2026
JEDI: Joint-Embedding Demonstration Compression for In-Context Imitation Learning
Jiazhao Liang, Zhewen He, Shuaihang Yuan +2
In-context imitation learning (ICIL) adapts robot policies through test-time demonstrations, but long multimodal trajectories constrain how many examples fit in context. We ask wha…
cs.RO2025
Integrating Retrospective Framework in Multi-Robot Collaboration
Jiazhao Liang, Hao Huang, Yu Hao +4
Recent advancements in Large Language Models (LLMs) have demonstrated substantial capabilities in enhancing communication and coordination in multi-robot systems. However, existing…
cs.RO2024★ 3 cited
How Secure Are Large Language Models (LLMs) for Navigation in Urban Environments?
Congcong Wen, Jiazhao Liang, Shuaihang Yuan +6
In the field of robotics and automation, navigation systems based on Large Language Models (LLMs) have recently demonstrated impressive performance. However, the security aspects o…