Robotics and embodied AI

Manipulation, locomotion, sim-to-real transfer and autonomous driving: learning systems that have to survive physics.

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arXiv Machine Learning

Jun 2

World Models: A Comprehensive Survey of Architectures, Methodologies, Reasoning Paradigms, and Applications

arXiv:2606. 00133v1 Announce Type: new Abstract: World models, internal simulators that learn the structure and dynamics of an environment, have emerged as a central paradigm in the pursuit of artificial general intelligence, enabling agents to predict, plan, and reason within learned representations.

By Arif Hassan Zidan, Yi Pan, Hanqi Jiang, Ruiyu Yan, Wei Ruan, Zihao Wu, Lifeng Chen, Weihang You, Xinliang Li, Bowen Chen, Huawen Hu, Peilong Wang, Sizhuang Liu, Jing Zhang, Siyuan Li, Zhengliang Liu, Yu Bao, Lin Zhao, Lichao Sun, Dajiang Zhu, Xiang Li, Jinglei Lv, Quanzheng Li, Wei Liu, Tianming Liu, Wei Zhang

llms agents diffusion reinforcement-learning robotics multimodal benchmarks safety

arXiv Machine Learning

Jun 2

GLENS: Global Search via Learning from Solver Iterates with Diffusion Models

arXiv:2606. 00366v1 Announce Type: new Abstract: We consider the problem of generating a large collection of initial guesses for local minima of multimodal non-convex continuous optimization problems.

By Anjian Li, Bartolomeo Stellato, Ryne Beeson

diffusion robotics multimodal benchmarks

arXiv Machine Learning

Jun 2

Partial Fairness Awareness: Belief-Guided Strategic Mechanism for Strategic Agents

arXiv:2606. 00826v1 Announce Type: new Abstract: Strategic machine learning investigates scenarios where agents manipulate their features to receive favorable decisions from predictive models.

By Xinpeng Lv, Chunyuan Zheng, Yunxin Mao, Renzhe Xu, Hao Zou, Shanzhi Gu, Liyang Xu, Huan Chen, Yuanlong Chen, Wenjing Yang, Haotian Wang

agents robotics safety

arXiv Machine Learning

Jun 2

Learning-based Directed Graph Abstraction of Combinatorial Spaces for Order-Preserving Search in Mixed-Combinatorial Nonlinear Optimization

arXiv:2606. 01425v1 Announce Type: new Abstract: Mixed-combinatorial nonlinear programming (MCNLP) problems arise in many engineering design and planning applications, e.

By Gishnu Madhu, Feng Liu, Souma Chowdhury

robotics benchmarks

arXiv Machine Learning

Jun 2

DeepLatent: Think with Images via Parallel Latent Visual Reasoning

arXiv:2606. 00562v1 Announce Type: cross Abstract: The emerging paradigm of "thinking with images" embeds visual states into intermediate reasoning steps, defining a new frontier for Vision-Language Models.

By Dongchen Lu, Zhimo Li, Mao Shu, Huo Cao

llms rag reinforcement-learning robotics efficiency multimodal benchmarks

arXiv Machine Learning

Jun 2

World-Task Factorization for Robot Learning

arXiv:2606. 02027v1 Announce Type: cross Abstract: Robot learning must produce policies that generalize to new combinations of constraints, teammates, and environments.

By Eduardo Sebasti\'an, Adrian Pfisterer, Vito Mengers, Oliver Brock, Amanda Prorok

robotics

arXiv Machine Learning

Jun 2

IstGPT: LLM-based Anomaly Detection for Spatial-Temporal Graph in Industrial Systems

arXiv:2606. 01691v1 Announce Type: cross Abstract: Industrial Internet systems face increasing threats from sophisticated industrial control system (ICS) attacks, resulting in critical safety incidents.

By Yuchen Zhang, Ning Xi, Pengbin Feng, Shigang Liu, Jianfeng Ma, Yulong Shen, Yanan Sun, Xiaolin Zhou

llms robotics multimodal benchmarks safety

arXiv AI

Jun 2

Co-Fusion4D: Spatio-temporal Collaborative Fusion for Robust 3D Object Detection

arXiv:2605. 20301v2 Announce Type: replace-cross Abstract: In autonomous driving, 3D object detection is essential for accurate perception and reliable decision-making.

By Wenxuan Li, Qin Zou, Shoubing Chen, Chi Chen, Yingyi Yang, Qingxiang Meng

agents computer-vision robotics benchmarks safety

arXiv AI

Jun 2

Bridging the Sim-to-Real Gap in Semiconductor Visual Program Synthesis via Input Binarization

arXiv:2606. 02434v1 Announce Type: new Abstract: Precise parametric control over circuit geometry is essential for semiconductor inspection, yet obtaining sufficient real training data remains costly.

By Yusuke Ohtsubo, Kota Dohi, Koichiro Yawata, Koki Takeshita, Tatsuya Sasaki

llms diffusion robotics multimodal safety

arXiv AI

Jun 2

DiscourseFlip: An Oblique Discourse-Level Opinion Manipulation Attack against Black-box Retrieval-Augmented Generation

arXiv:2606. 01212v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) systems are widely deployed and increasingly influential, but their reliance on external corpora exposes new security risks from poisoned retrieval content.

By Yuyang Gong, Miaokun Chen, Jiawei Liu, Zhuo Chen, Guoxiu He, Wei Lu, XiaoFeng Wang, Xiaozhong Liu

rag agents robotics

arXiv Machine Learning

Jun 2

Discrete Diffusion VLA: Bringing Discrete Diffusion to Action Decoding in Vision-Language-Action Policies

arXiv:2508. 20072v4 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models adapt large vision-language backbones to map images and instructions into robot actions.

By Zhixuan Liang, Yizhuo Li, Tianshuo Yang, Chengyue Wu, Sitong Mao, Liuao Pei, Tian Nian, Shunbo Zhou, Xiaokang Yang, Jiangmiao Pang, Yao Mu, Ping Luo

llms diffusion robotics multimodal

arXiv Machine Learning

Jun 2

Domain Adaptation with a Single Vision-Language Embedding

arXiv:2410. 21361v2 Announce Type: replace-cross Abstract: Domain adaptation has been extensively investigated in computer vision but still requires access to target data at the training time, which might be difficult to obtain in real-world autonomous driving scenarios, especially under rare or adverse conditions.

By Mohammad Fahes, Tuan-Hung Vu, Andrei Bursuc, Patrick P\'erez, Raoul de Charette

rag agents computer-vision robotics fine-tuning multimodal

arXiv Machine Learning

Jun 2

Adversarial Dual On-Policy Distillation from Expressive Teacher

arXiv:2605. 27095v2 Announce Type: replace Abstract: Learning from demonstrations in embodied control is often cast as behavioral cloning, and recent diffusion or flow-matching policies improve this paradigm by modeling multi-modal expert actions.

By Zhenglin Wan, Jingxuan Wu, Xingrui Yu, Chubin Zhang, Mingcong Lei, Bo An, Ivor W. Tsang, Yang You

diffusion robotics efficiency multimodal benchmarks safety

arXiv Machine Learning

Jun 2

Coarse-to-Fine Compositional Diffusion for Long-Horizon Planning

arXiv:2606. 00837v1 Announce Type: cross Abstract: Diffusion models provide strong priors for generating structured data, but many tasks require outputs beyond the scale on which these models are typically trained.

By Byoungwoo Park, Utkarsh A. Mishra, Jaemoo Choi, Juho Lee, Yongxin Chen

diffusion robotics

arXiv Machine Learning

Jun 2

Behavior Cloning of MPC for 3-DOF Robotic Manipulators

arXiv:2606. 00383v1 Announce Type: cross Abstract: While Model Predictive Control (MPC) provides strong stability and robustness, it imposes a significant computational burden on real-time systems.

By Theo Guegan, Dexter Wen Jie Teo

robotics efficiency

arXiv Machine Learning

Jun 2

HOIST: Humanoid Optimization with Imitation and Sample-efficient Tuning for Manipulating Suspended Loads

arXiv:2606. 00252v1 Announce Type: cross Abstract: Manipulating suspended payloads with humanoid robots is challenging because the robot can only influence an underactuated, oscillatory load through whole-body motion and intermittent contact.

By Songyang Liu, Shunyu Yao, Dingyuan Huang, Shuai Li

reinforcement-learning robotics multimodal

arXiv Machine Learning

Jun 2

Modeling Robotics Dataset Construction as an Artifact-Based Build Process

arXiv:2606. 00162v1 Announce Type: cross Abstract: Robotic systems generate large volumes of multimodal sensor data, but converting ROS bag recordings into machine learning datasets is often handled by ad hoc sequential scripts, creating engineering overhead and slow iteration cycles.

By Leon Pohl, Lukas Beer, George Sebastian, Mirko Maehlisch

robotics multimodal

arXiv Machine Learning

Jun 2

PaintBench: Deterministic Evaluation of Precise Visual Editing

arXiv:2606. 00188v1 Announce Type: cross Abstract: While current multimodal models are proficient at open-ended visual editing, executing precise single-answer edits remains an important obstacle.

By Kai Xu, Ellis Brown, Shrikar Madhu, Rob Fergus, He He, Saining Xie

robotics multimodal benchmarks safety

arXiv Machine Learning

Jun 2

Evaluating Real-World Generalizability of Algorithm Selection Models

arXiv:2606. 02016v1 Announce Type: new Abstract: Algorithm Selection (AS) aims to automatically identify the most suitable optimization algorithm for a given problem instance by leveraging measurable problem characteristics and historical performance data.

By Gjorgjina Cenikj, Jakub Kudela, Eva Tuba, Tome Eftimov

robotics benchmarks

arXiv Machine Learning

Jun 2

RDA: Reward Design Agent for Reinforcement Learning

arXiv:2606. 01672v1 Announce Type: new Abstract: Reinforcement learning has enabled the acquisition of impressive robotic skills, but typically requires hand-crafted reward functions that are slow to design and difficult to align with human intentions.

By Hojoon Lee, Ajay Subramanian, Ben Abbatematteo, Vijay Veerabadran, Pedro Matias, Karl Ridgeway, Nitin Kamra

llms agents reinforcement-learning robotics multimodal

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