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20212026
most citedInternLM2 Technical Report

29 citations · 42 across the 31 of their papers we have counts for

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6 papers · 1 filter

cs.RO2026

HiMe: Hierarchical Embodied Memory for Long-Horizon Vision-Language-Action Control

Li Ji, Siyin Wang, Pengfang Qian +5

Current Vision-Language-Action (VLA) models excel at robotic manipulation but often struggle with non-Markovian tasks requiring long-term memory and reasoning due to their reliance…

cs.RO2026

Advancing Omnimodal Embodied Agents from Isolated Skills to Everyday Physical Autonomy

Junhao Shi, Zezheng Huai, Siyin Wang +7

Building persistent embodied agents in unstructured environments demands unified orchestration of heterogeneous tools spanning both cyber (APIs, IoT) and physical (manipulation, na…

cs.RO2026

World Action Models: The Next Frontier in Embodied AI

Siyin Wang, Junhao Shi, Zhaoyang Fu +11

Vision-Language-Action (VLA) models have achieved strong semantic generalization for embodied policy learning, yet they learn reactive observation-to-action mappings without explic…

cs.RO2025

RoboOmni: Proactive Robot Manipulation in Omni-modal Context

Siyin Wang, Jinlan Fu, Feihong Liu +11

Recent advances in Multimodal Large Language Models (MLLMs) have driven rapid progress in Vision-Language-Action (VLA) models for robotic manipulation. Although effective in many s…

cs.RO2025

LIBERO-Plus: In-depth Robustness Analysis of Vision-Language-Action Models

Senyu Fei, Siyin Wang, Junhao Shi +10

Visual-Language-Action (VLA) models report impressive success rates on robotic manipulation benchmarks, yet these results may mask fundamental weaknesses in robustness. We perform…

cs.RO2024

VLABench: A Large-Scale Benchmark for Language-Conditioned Robotics Manipulation with Long-Horizon Reasoning Tasks

Shiduo Zhang, Zhe Xu, Peiju Liu +8

General-purposed embodied agents are designed to understand the users' natural instructions or intentions and act precisely to complete universal tasks. Recently, methods based on…