most citedKARMA: Augmenting Embodied AI Agents with Long-and-short Term Memory Systems

2 citations · 2 across the 9 of their papers we have counts for

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cs.RO2026

Which Trajectory Is Safer? Combining Rule and Learning for Safety Evaluation

Xuewen Luo, Linlian Jiang, Bo Yu +3

Collision rate remains a dominant metric for evaluating autonomous driving trajectory safety, but its binary nature obscures substantial safety differences among collision-free tra…

cs.RO2026

EagleVLA: Towards Onboard Real-Time Robot Control via Foresight-Aligned Asynchronous Inference

Zebin Yang, Qi Wang, Yunhe Wang +6

Vision-Language-Action (VLA) models have achieved impressive performance on diverse embodied tasks. However, deploying VLA models on low-power onboard devices, such as the Jetson O…

cs.RO2026

KnowDiffuser: A Knowledge-Guided Diffusion Planner with LLM Reasoning

Fan Ding, Xuewen Luo, Fengze Yang +4

Recent advancements in Language Models (LMs) have demonstrated strong semantic reasoning capabilities, enabling their application in high-level decision-making for autonomous drivi…

cs.RO2026

KEEP: A KV-Cache-Centric Memory Management System for Efficient Embodied Planning

Zebin Yang, Tong Xie, Baotong Lu +3

Memory-augmented Large Language Models (LLMs) have demonstrated remarkable capability for complex and long-horizon embodied planning. By keeping track of past experiences and envir…

cs.RO2024

DaDu-E: Rethinking the Role of Large Language Model in Robotic Computing Pipeline

Wenhao Sun, Sai Hou, Zixuan Wang +6

Performing complex tasks in open environments remains challenging for robots, even when using large language models (LLMs) as the core planner. Many LLM-based planners are ineffici…

cs.RO2024★ 2 cited

KARMA: Augmenting Embodied AI Agents with Long-and-short Term Memory Systems

Zixuan Wang, Bo Yu, Junzhe Zhao +6

Embodied AI agents responsible for executing interconnected, long-sequence household tasks often face difficulties with in-context memory, leading to inefficiencies and errors in t…