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20242026
most citedDELTA: Decomposed Efficient Long-Term Robot Task Planning using Large Language Models

6 citations · 6 across the 9 of their papers we have counts for

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7 papers · 1 filter

cs.RO2026

What Should Embodied Agents Remember? Benchmarking and Evaluating Memory Modality for Embodied Agents

Junxiang Wang, Yuchen Liu, Yi Wu +6

Memory allows large language model (LLM) agents to use past experience, often stored as textual records, when responding to requests. For embodied agents that control robots, visua…

cs.RO2026

BiRoAD: Learning Shared and Role-Adaptive Representations for Bimanual Manipulation

Yan Shen, Yuchen Liu, Feng Jiang +5

Bimanual manipulation requires policies that coordinate two arms while adapting their functional roles to scene geometry, object configuration, and task context. Learning such scen…

cs.RO2026

RoboWM-Bench: A Benchmark for Evaluating World Models in Robotic Manipulation

Feng Jiang, Yang Chen, Kyle Xu +8

Recent advances in large-scale video world models have enabled increasingly realistic future prediction, raising the prospect of using generated videos as scalable supervision for…

cs.RO2026

BiPreManip: Learning Affordance-Based Bimanual Preparatory Manipulation through Anticipatory Collaboration

Yan Shen, Feng Jiang, Zichen He +5

Many everyday objects are difficult to directly grasp (e.g., a flat iPad) or manipulate functionally (e.g., opening the cap of a pen lying on a desk). Such tasks require sequential…

cs.RO2025

Context-Aware Human Behavior Prediction Using Multimodal Large Language Models: Challenges and Insights

Yuchen Liu, Lino Lerch, Luigi Palmieri +4

Predicting human behavior in shared environments is crucial for safe and efficient human-robot interaction. Traditional data-driven methods to that end are pre-trained on domain-sp…

cs.RO2024

Towards Human Awareness in Robot Task Planning with Large Language Models

Yuchen Liu, Luigi Palmieri, Sebastian Koch +2

The recent breakthroughs in the research on Large Language Models (LLMs) have triggered a transformation across several research domains. Notably, the integration of LLMs has great…

cs.RO2024★ 6 cited

DELTA: Decomposed Efficient Long-Term Robot Task Planning using Large Language Models

Yuchen Liu, Luigi Palmieri, Sebastian Koch +2

Recent advancements in Large Language Models (LLMs) have sparked a revolution across many research fields. In robotics, the integration of common-sense knowledge from LLMs into tas…