Tootfinder

TacMan-Turbo: Proactive Tactile Control for Robust and Efficient Articulated Object Manipulation
Zihang Zhao, Zhenghao Qi, Yuyang Li, Leiyao Cui, Zhi Han, Lecheng Ruan, Yixin Zhu
https://arxiv.org/abs/2508.02204

TacMan-Turbo: Proactive Tactile Control for Robust and Efficient Articulated Object Manipulation
Adept manipulation of articulated objects is essential for robots to operate successfully in human environments. Such manipulation requires both effectiveness -- reliable operation despite uncertain object structures -- and efficiency -- swift execution with minimal redundant steps and smooth actions. Existing approaches struggle to achieve both objectives simultaneously: methods relying on predefined kinematic models lack effectiveness when encountering structural variations, while tactile-inf…

HandOver: Enabling Precise Selection & Manipulation of 3D Objects with Mouse and Hand Tracking
Esen K. T\"ut\"unc\"u, Mar Gonzalez-Franco, Eric J. Gonzalez
https://arxiv.org/abs/2508.00211

HandOver: Enabling Precise Selection & Manipulation of 3D Objects with Mouse and Hand Tracking
We present HandOver, an extended reality (XR) interaction technique designed to unify the precision of traditional mouse input for object selection with the expressiveness of hand-tracking for object manipulation. With HandOver, the mouse is used to drive a depth-aware 3D cursor enabling precise and restful targeting -by hovering their hand over the mouse, the user can then seamlessly transition into direct 3D manipulation of the target object. In a formal user study, we compare HandOver agains…

Generation and manipulation of photon number wave packets in photonic cavities
Luca Nimmesgern, Moritz Cygorek, Doris E. Reiter, Vollrath Martin Axt
https://arxiv.org/abs/2509.03083

Generation and manipulation of photon number wave packets in photonic cavities
Quantum emitters inside optical cavities can create not only fixed photon number states but also photon number wave packets, which are states with a finite photon number distribution that oscillates in time. These states emerge when the emitter is driven by an external field while coupled to the cavity. We show that by rapidly changing the driving strength, new wave packets can be generated, allowing multiple packets to coexist and evolve independently. We classify the resulting wave packet beh…

The Role of Embodiment in Intuitive Whole-Body Teleoperation for Mobile Manipulation
Sophia Bianchi Moyen, Rickmer Krohn, Sophie Lueth, Kay Pompetzki, Jan Peters, Vignesh Prasad, Georgia Chalvatzaki
https://arxiv.org/abs/2509.03222

The Role of Embodiment in Intuitive Whole-Body Teleoperation for Mobile Manipulation
Intuitive Teleoperation interfaces are essential for mobile manipulation robots to ensure high quality data collection while reducing operator workload. A strong sense of embodiment combined with minimal physical and cognitive demands not only enhances the user experience during large-scale data collection, but also helps maintain data quality over extended periods. This becomes especially crucial for challenging long-horizon mobile manipulation tasks that require whole-body coordination. We co…

The fastverse is a suite of complementary high-performance packages for statistical computing and data manipulation in R. #rstats

GitHub - fastverse/fastverse: An Extensible Suite of High-Performance and Low-Dependency Packages for Statistical Computing and Data Manipulation in R
An Extensible Suite of High-Performance and Low-Dependency Packages for Statistical Computing and Data Manipulation in R - fastverse/fastverse

Demonstrating Visual Information Manipulation Attacks in Augmented Reality: A Hands-On Miniature City-Based Setup
Yanming Xiu, Maria Gorlatova
https://arxiv.org/abs/2509.02933 h…

Demonstrating Visual Information Manipulation Attacks in Augmented Reality: A Hands-On Miniature City-Based Setup
Augmented reality (AR) enhances user interaction with the real world but also presents vulnerabilities, particularly through Visual Information Manipulation (VIM) attacks. These attacks alter important real-world visual cues, leading to user confusion and misdirected actions. In this demo, we present a hands-on experience using a miniature city setup, where users interact with manipulated AR content via the Meta Quest 3. The demo highlights the impact of VIM attacks on user decision-making and …

Freitag: Wikipedia-Untersuchung auf Manipulation, Copilot für Samsungs Smart-TVs
Republikaner gegen Wikipedia Samsung-TVs mit Microsoft-KI Quantenobjekte im aktuellen Internet Ende von Plug-in-Hybriden Verbraucherschutz-Podcast

Improving Generalization of Language-Conditioned Robot Manipulation
Chenglin Cui, Chaoran Zhu, Changjae Oh, Andrea Cavallaro
https://arxiv.org/abs/2508.02405 https://

Improving Generalization of Language-Conditioned Robot Manipulation
The control of robots for manipulation tasks generally relies on visual input. Recent advances in vision-language models (VLMs) enable the use of natural language instructions to condition visual input and control robots in a wider range of environments. However, existing methods require a large amount of data to fine-tune VLMs for operating in unseen environments. In this paper, we present a framework that learns object-arrangement tasks from just a few demonstrations. We propose a two-stage f…

Graph neural networks for learning liquid simulations in dynamic scenes containing kinematic objects
Niteesh Midlagajni, Constantin A. Rothkopf
https://arxiv.org/abs/2509.03446 …

Graph neural networks for learning liquid simulations in dynamic scenes containing kinematic objects
Simulating particle dynamics with high fidelity is crucial for solving real-world interaction and control tasks involving liquids in design, graphics, and robotics. Recently, data-driven approaches, particularly those based on graph neural networks (GNNs), have shown progress in tackling such problems. However, these approaches are often limited to learning fluid behavior in static free-fall environments or simple manipulation settings involving primitive objects, often overlooking complex inte…

EvoEmo: Towards Evolved Emotional Policies for LLM Agents in Multi-Turn Negotiation
Yunbo Long, Liming Xu, Lukas Beckenbauer, Yuhan Liu, Alexandra Brintrup
https://arxiv.org/abs/2509.04310

EvoEmo: Towards Evolved Emotional Policies for LLM Agents in Multi-Turn Negotiation
Recent research on Chain-of-Thought (CoT) reasoning in Large Language Models (LLMs) has demonstrated that agents can engage in \textit{complex}, \textit{multi-turn} negotiations, opening new avenues for agentic AI. However, existing LLM agents largely overlook the functional role of emotions in such negotiations, instead generating passive, preference-driven emotional responses that make them vulnerable to manipulation and strategic exploitation by adversarial counterparts. To address this gap,…

In-context learning for the classification of manipulation techniques in phishing emails
Antony Dalmiere (LAAS-TRUST, LAAS), Guillaume Auriol (LAAS-TRUST, INSA Toulouse), Vincent Nicomette (LAAS-TSF, LAAS), Pascal Marchand (LERASS)
https://arxiv.org/abs/2506.22515

In-context learning for the classification of manipulation techniques in phishing emails
Traditional phishing detection often overlooks psychological manipulation. This study investigates using Large Language Model (LLM) In-Context Learning (ICL) for fine-grained classification of phishing emails based on a taxonomy of 40 manipulation techniques. Using few-shot examples with GPT-4o-mini on real-world French phishing emails (SignalSpam), we evaluated performance against a human-annotated test set (100 emails). The approach effectively identifies prevalent techniques (e.g., Baiting, …

DARTS: A Dual-View Attack Framework for Targeted Manipulation in Federated Sequential Recommendation
Qitao Qin, Yucong Luo, Zhibo Chu
https://arxiv.org/abs/2507.01383

DARTS: A Dual-View Attack Framework for Targeted Manipulation in Federated Sequential Recommendation
Federated recommendation (FedRec) preserves user privacy by enabling decentralized training of personalized models, but this architecture is inherently vulnerable to adversarial attacks. Significant research has been conducted on targeted attacks in FedRec systems, motivated by commercial and social influence considerations. However, much of this work has largely overlooked the differential robustness of recommendation models. Moreover, our empirical findings indicate that existing targeted att…

PUSHtap: PIM-based In-Memory HTAP with Unified Data Storage Format
Yilong Zhao, Mingyu Gao, Huanchen Zhang, Fangxin Liu, Gongye Chen, He Xian, Haibing Guan, Li Jiang
https://arxiv.org/abs/2508.02309

PUSHtap: PIM-based In-Memory HTAP with Unified Data Storage Format
Hybrid transaction/analytical processing (HTAP) is an emerging database paradigm that supports both online transaction processing (OLTP) and online analytical processing (OLAP) workloads. Computing-intensive OLTP operations, involving row-wise data manipulation, are suitable for row-store format. In contrast, memory-intensive OLAP operations, which are column-centric, benefit from column-store format. This \emph{data-format dilemma} prevents HTAP systems from concurrently achieving three design…

@… For those of you that manually installed 7.5RC1, these are the additional changes since that version:
• [Crash] On tab strip manipulation
• [Crash][Search][Sync] In search engines code, triggered by sync (VB-118299)
• [Crash][macOS] On adding an new account (VB-118293)
• [Menus][Tabs] The tab bar context menu is no longer accessible: pa…

ArtGS:3D Gaussian Splatting for Interactive Visual-Physical Modeling and Manipulation of Articulated Objects
Qiaojun Yu, Xibin Yuan, Yu jiang, Junting Chen, Dongzhe Zheng, Ce Hao, Yang You, Yixing Chen, Yao Mu, Liu Liu, Cewu Lu
https://arxiv.org/abs/2507.02600

ArtGS:3D Gaussian Splatting for Interactive Visual-Physical Modeling and Manipulation of Articulated Objects
Articulated object manipulation remains a critical challenge in robotics due to the complex kinematic constraints and the limited physical reasoning of existing methods. In this work, we introduce ArtGS, a novel framework that extends 3D Gaussian Splatting (3DGS) by integrating visual-physical modeling for articulated object understanding and interaction. ArtGS begins with multi-view RGB-D reconstruction, followed by reasoning with a vision-language model (VLM) to extract semantic and structura…

Localizing Audio-Visual Deepfakes via Hierarchical Boundary Modeling
Xuanjun Chen, Shih-Peng Cheng, Jiawei Du, Lin Zhang, Xiaoxiao Miao, Chung-Che Wang, Haibin Wu, Hung-yi Lee, Jyh-Shing Roger Jang
https://arxiv.org/abs/2508.02000

Localizing Audio-Visual Deepfakes via Hierarchical Boundary Modeling
Audio-visual temporal deepfake localization under the content-driven partial manipulation remains a highly challenging task. In this scenario, the deepfake regions are usually only spanning a few frames, with the majority of the rest remaining identical to the original. To tackle this, we propose a Hierarchical Boundary Modeling Network (HBMNet), which includes three modules: an Audio-Visual Feature Encoder that extracts discriminative frame-level representations, a Coarse Proposal Generator th…

A Midsummer Meme's Dream: Investigating Market Manipulations in the Meme Coin Ecosystem
Alberto Maria Mongardini, Alessandro Mei
https://arxiv.org/abs/2507.01963

A Midsummer Meme's Dream: Investigating Market Manipulations in the Meme Coin Ecosystem
From viral jokes to a billion-dollar phenomenon, meme coins have become one of the most popular segments in cryptocurrency markets. Unlike utility-focused crypto assets like Bitcoin or Ethereum, meme coins derive value primarily from community sentiment, making them vulnerable to manipulation. This study presents a cross-chain analysis of the meme coin ecosystem, examining 34,988 tokens across Ethereum, BNB Smart Chain, Solana, and Base. We characterize the tokenomics of meme coins and track th…

The effect of dephasing and spin-lattice relaxation during the switching processes in quantum antiferromagnets
Asliddin Khudoyberdiev, G\"otz S. Uhrig
https://arxiv.org/abs/2508.00430

The effect of dephasing and spin-lattice relaxation during the switching processes in quantum antiferromagnets
The control of antiferromagnetic order can pave the way to large storage capacity as well as fast manipulation of stored data. Here achieving a steady-state of sublattice magnetization after switching is crucial to prevent loss of stored data. The present theoretical approach aims to obtain instantaneous stable states of the order after reorienting the Néel vector in open quantum antiferromagnets using time-dependent Schwinger boson mean-field theory. The Lindblad formalism is employed to coup…

Network Prebunking Problem: Optimizing Prebunking Targets to Suppress the Spread of Misinformation in Social Networks
Satoshi Furutani, Toshiki Shibahara, Mitsuaki Akiyama, Masaki Aida
https://arxiv.org/abs/2508.01124

Network Prebunking Problem: Optimizing Prebunking Targets to Suppress the Spread of Misinformation in Social Networks
As a countermeasure against misinformation that undermines the healthy use of social media, a preventive intervention known as prebunking has recently attracted attention in the field of psychology. Prebunking aims to strengthen individuals' cognitive resistance to misinformation by presenting weakened doses of misinformation or by teaching common manipulation techniques before they encounter actual misinformation. Despite the growing body of evidence supporting its effectiveness in reducing su…

MoTo: A Zero-shot Plug-in Interaction-aware Navigation for General Mobile Manipulation
Zhenyu Wu, Angyuan Ma, Xiuwei Xu, Hang Yin, Yinan Liang, Ziwei Wang, Jiwen Lu, Haibin Yan
https://arxiv.org/abs/2509.01658

MoTo: A Zero-shot Plug-in Interaction-aware Navigation for General Mobile Manipulation
Mobile manipulation stands as a core challenge in robotics, enabling robots to assist humans across varied tasks and dynamic daily environments. Conventional mobile manipulation approaches often struggle to generalize across different tasks and environments due to the lack of large-scale training. However, recent advances in manipulation foundation models demonstrate impressive generalization capability on a wide range of fixed-base manipulation tasks, which are still limited to a fixed setting…

Cascaded frequency conversion of highly charged femtosecond spatiotemporal optical vortices
Qingqing Liang, Qiyuan Zhang, Dan Wang, Enliang Zhang, Jianhua Hu, Ming Wang, Jinxin Wu, Grover A. Swartzlander, Yi Liu
https://arxiv.org/abs/2507.02471

Cascaded frequency conversion of highly charged femtosecond spatiotemporal optical vortices
The degrees of freedom inherent in spatiotemporal optical vortices (STOV's) afford intriguing opportunties to manipulate complex light fields for broad applications such as optical communication, light-matter interactions, particle manipulation, quantum optics, and electron acceleration in the relativistic regime. Unlike previous studies examining the second harmonic generation (SHG) of STOV's having an input topological charge (TC) l^{\left(ω\right)}=1, here we experimentally demonstrate casc…

Tunable Majorana corner states driven by superconducting phase bias in a vertical Josephson junction
Cheng-Ming Miao, Yu-Hao Wan, Ying-Tao Zhang, Qing-Feng Sun
https://arxiv.org/abs/2509.03949

Tunable Majorana corner states driven by superconducting phase bias in a vertical Josephson junction
The realization and manipulation of Majorana zero modes is a key step in achieving topological quantum computation. In this paper, we demonstrate the existence of Majorana corner states in a superconductor-insulators-superconductor vertical Josephson junction. The position of these Majorana corner states can be precisely and easily controlled by the superconducting phase bias, which be confirmed through both numerical and edge state theoretical analysis. In addition, we propose a protocol for a…

🍮 Wissen zum Nachtisch: 🍨
Retröt: Der #Kapitalismus braucht für #Wachstum und #Gewinnmaximierung schier endlosen

Die Tricks der Verkäufer: So schützen Sie sich vor Manipulation
Verkäufertricks erkennen: Tipps und Tricks, wie Sie sich vor Manipulation schützen

Two-dimensional magnetic tunnel p-n junctions for low-power electronics
Wenkai Zhu, Ziao Wang, Tiangui Hu, Zakhar R. Kudrynskyi, Tong Zhou, Zakhar D. Kovalyuk, Ce Hu, Hailong Lin, Xiaodong Li, Yongcheng Deng, Quanshan Lv, Lixia Zhao, Amalia Patane, Igor Zutic, Houzhi Zheng, Kaiyou Wang
https://arxiv.org/abs/2509.04206

Two-dimensional magnetic tunnel p-n junctions for low-power electronics
For decades, semiconductors and their heterostructures have underpinned both fundamental and applied research across all areas of electronics. Two-dimensional, 2D (atomically thin) semiconductors have now the potential to push further the miniaturization of electronic components, enabling the development of more efficient electronics. Here, we report on a giant anomalous zero-bias spin voltage in magnetic tunnel junctions based on 2D materials. The generation, manipulation and detection of elec…

The MolecularWeb Universe: Web-Based, Immersive, Multiuser Molecular Graphics And Modeling, for Education and Work in Chemistry, Structural Biology, and Materials Sciences
Luciano A. Abriata
https://arxiv.org/abs/2509.04056

The MolecularWeb Universe: Web-Based, Immersive, Multiuser Molecular Graphics And Modeling, for Education and Work in Chemistry, Structural Biology, and Materials Sciences
Molecular visualization software has long supported research and education in chemical and structural sciences, but consumer devices constrained to 2D inputs and outputs pose two major challenges: they poorly convey 3D nature, and 3D manipulation is very difficult. eXtended Reality (XR, including AR and VR) offers new ways to see and interact with molecules in three dimensions. This chapter presents the "MolecularWeb" ecosystem (https://molecularweb.org), a set of web-based tools for immersive …

Fast variational knowledge graph embedding
Pulak Ranjan Giri, Mori Kurokawa, Kazuhiro Saito
https://arxiv.org/abs/2507.02472 https://…

Fast variational knowledge graph embedding
Embedding of a knowledge graph(KG) entities and relations in the form of vectors is an important aspect for the manipulation of the KG database for several downstream tasks, such as link prediction, knowledge graph completion, and recommendation. Because of the growing size of the knowledge graph databases, it has become a daunting task for the classical computer to train a model efficiently. Quantum computer can help speedup the embedding process of the KGs by encoding the entities into a vari…

Propose and Rectify: A Forensics-Driven MLLM Framework for Image Manipulation Localization
Keyang Zhang, Chenqi Kong, Hui Liu, Bo Ding, Xinghao Jiang, Haoliang Li
https://arxiv.org/abs/2508.17976

Propose and Rectify: A Forensics-Driven MLLM Framework for Image Manipulation Localization
The increasing sophistication of image manipulation techniques demands robust forensic solutions that can both reliably detect alterations and precisely localize tampered regions. Recent Multimodal Large Language Models (MLLMs) show promise by leveraging world knowledge and semantic understanding for context-aware detection, yet they struggle with perceiving subtle, low-level forensic artifacts crucial for accurate manipulation localization. This paper presents a novel Propose-Rectify framework…

Language Arithmetics: Towards Systematic Language Neuron Identification and Manipulation
Daniil Gurgurov, Katharina Trinley, Yusser Al Ghussin, Tanja Baeumel, Josef van Genabith, Simon Ostermann
https://arxiv.org/abs/2507.22608

Language Arithmetics: Towards Systematic Language Neuron Identification and Manipulation
Large language models (LLMs) exhibit strong multilingual abilities, yet the neural mechanisms behind language-specific processing remain unclear. We analyze language-specific neurons in Llama-3.1-8B, Mistral-Nemo-12B, and Aya-Expanse-8B & 32B across 21 typologically diverse languages, identifying neurons that control language behavior. Using the Language Activation Probability Entropy (LAPE) method, we show that these neurons cluster in deeper layers, with non-Latin scripts showing greater spec…

Manipulation: Strafrechtliche Ermittlungen gegen X in Frankreich
Wegen Einmischung in innere Angelegenheiten samt betrügerischen Ausleitens von Daten ermittelt Frankreich gegen X. Dieses kooperiert nicht.
ht…

Manip4Care: Robotic Manipulation of Human Limbs for Solving Assistive Tasks
Yubin Koh, Ahmed H. Qureshi
https://arxiv.org/abs/2508.02649 https://arxiv.org/…

Manip4Care: Robotic Manipulation of Human Limbs for Solving Assistive Tasks
Enabling robots to grasp and reposition human limbs can significantly enhance their ability to provide assistive care to individuals with severe mobility impairments, particularly in tasks such as robot-assisted bed bathing and dressing. However, existing assistive robotics solutions often assume that the human remains static or quasi-static, limiting their effectiveness. To address this issue, we present Manip4Care, a modular simulation pipeline that enables robotic manipulators to grasp and r…

Yikes, there is always so much infosec news but Metacurity helps a lot with the overload.
Check out today's issue for the cybersecurity developments you should know, including
--Cyber insurance premiums dropped for the first time in 2024,
--CyberAv3ngers shift to psychological manipulation,
--Another hacker hits Paraguay,
--50% of ransomware payments are less than expected,
--Pro-Russian group was reportedly behind Norwegian dam hack,
--UK 2025 …

Cyber insurance premiums dropped for the first time in 2024
CyberAv3ngers shift to psychological manipulation, Another hacker hits Paraguay, 50% of ransomware payments are less than expected, Pro-Russian group was reportedly behind Norwegian dam hack, UK 2025 strategy calls for stronger cyber capabilities, Hackers abuse Trezor's support form, much more

End-to-End Low-Level Neural Control of an Industrial-Grade 6D Magnetic Levitation System
Philipp Hartmann, Jannick Strangh\"oner, Klaus Neumann
https://arxiv.org/abs/2509.01388

End-to-End Low-Level Neural Control of an Industrial-Grade 6D Magnetic Levitation System
Magnetic levitation is poised to revolutionize industrial automation by integrating flexible in-machine product transport and seamless manipulation. It is expected to become the standard drive for automated manufacturing. However, controlling such systems is inherently challenging due to their complex, unstable dynamics. Traditional control approaches, which rely on hand-crafted control engineering, typically yield robust but conservative solutions, with their performance closely tied to the ex…

Automated Construction of Artificial Lattice Structures with Designer Electronic States
Ganesh Narasimha, Mykola Telychko, Wooin Yang, Arthur P. Baddorf, P. Ganesh, An-Ping Li, Rama Vasudevan
https://arxiv.org/abs/2508.02581

Automated Construction of Artificial Lattice Structures with Designer Electronic States
Manipulating matter with a scanning tunneling microscope (STM) enables creation of atomically defined artificial structures that host designer quantum states. However, the time-consuming nature of the manipulation process, coupled with the sensitivity of the STM tip, constrains the exploration of diverse configurations and limits the size of designed features. In this study, we present a reinforcement learning (RL)-based framework for creating artificial structures by spatially manipulating car…

»Pariser Staatsanwaltschaft – Frankreich ermittelt gegen X wegen mutmaßlicher Manipulation:
Der Algorithmus der Plattform soll zum Zweck ausländischer Einflussnahme geändert worden sein. Der Name von CEO Elon Musk wurde nicht explizit erwähnt«
Da bin ich mal gespannt wie das auskommt. Dass X Manipulation ist, ist nicht neu aber wurde noch nie handfest belegt und auch deswegen wurde es von Musk übernommen.
🧑‍⚖️

Frankreich ermittelt gegen X wegen mutmaßlicher Manipulation
Der Algorithmus der Plattform soll zum Zweck ausländischer Einflussnahme geändert worden sein. Der Name von CEO Elon Musk wurde nicht explizit erwähnt

Tunneling induced giant Photonic Spin Hall effect in quantum wells
Fazal Badshah, Imed Boukhris, Mohamed Sultan Al-Buriah, Yuan Zhou, Muhammad Idrees, Ziauddin
https://arxiv.org/abs/2509.03844

Tunneling induced giant Photonic Spin Hall effect in quantum wells
We propose a theoretical investigation of the photonic spin Hall effect (PSHE) in a mid-infrared probe field by employing an asymmetric double AlGaAsGaAs quantum well as the intracavity medium. The system is designed such that an external control beam together with tunable tunneling barriers regulates the quantum interference of the probe tunneling process. This configuration enables precise manipulation of the PSHE for both horizontally and vertically polarized components of light. Our analysi…

The Manipulative Power of Voice Characteristics: Investigating Deceptive Patterns in Mandarin Chinese Female Synthetic Speech
Shuning Zhang (Tsinghua University, Beijing, China), Han Chen (Wuhan Institute of Technology, Wuhan, China), Yabo Wang (Tsinghua University, Beijing, China), Yiqun Xu (Tsinghua University, Beijing, China), Jiaqi Bai (Tsinghua University, Beijing, China), Yuanyuan Wu (Shanghai Jiaotong University, Shanghai, China), Shixuan Li (Tsinghua University, Beijing, China)…

The Manipulative Power of Voice Characteristics: Investigating Deceptive Patterns in Mandarin Chinese Female Synthetic Speech
Pervasive voice interaction enables deceptive patterns through subtle voice characteristics, yet empirical investigation into this manipulation lags behind, especially within major non-English language contexts. Addressing this gap, our study presents the first systematic investigation into voice characteristic-based dark patterns employing female synthetic voices in Mandarin Chinese. This focus is crucial given the prevalence of female personas in commercial assistants and the prosodic signifi…

Optimal Benchmark Design under Costly Manipulation
\'Angel Hernando-Veciana
https://arxiv.org/abs/2506.22142 https://arxiv.org/pd…

Optimal Benchmark Design under Costly Manipulation
Price benchmarks are used to incorporate market price trends into contracts, but their use can create opportunities for manipulation by parties involved in the contract. This paper examines this issue using a realistic and tractable model inspired by smart contracts on blockchains like Ethereum. In our model, manipulation costs depend on two factors: the magnitude of adjustments to individual prices (variable costs) and the number of prices adjusted (fixed costs). We find that a weighted mean i…

Language-Guided Long Horizon Manipulation with LLM-based Planning and Visual Perception
Changshi Zhou, Haichuan Xu, Ningquan Gu, Zhipeng Wang, Bin Cheng, Pengpeng Zhang, Yanchao Dong, Mitsuhiro Hayashibe, Yanmin Zhou, Bin He
https://arxiv.org/abs/2509.02324

Language-Guided Long Horizon Manipulation with LLM-based Planning and Visual Perception
Language-guided long-horizon manipulation of deformable objects presents significant challenges due to high degrees of freedom, complex dynamics, and the need for accurate vision-language grounding. In this work, we focus on multi-step cloth folding, a representative deformable-object manipulation task that requires both structured long-horizon planning and fine-grained visual perception. To this end, we propose a unified framework that integrates a Large Language Model (LLM)-based planner, a V…

Tensor Manipulation Unit (TMU): Reconfigurable, Near-Memory Tensor Manipulation for High-Throughput AI SoC
Weiyu Zhou, Zheng Wang, Chao Chen, Yike Li, Yongkui Yang, Zhuoyu Wu, Anupam Chattopadhyay
https://arxiv.org/abs/2506.14364

Tensor Manipulation Unit (TMU): Reconfigurable, Near-Memory Tensor Manipulation for High-Throughput AI SoC
While recent advances in AI SoC design have focused heavily on accelerating tensor computation, the equally critical task of tensor manipulation, centered on high,volume data movement with minimal computation, remains underexplored. This work addresses that gap by introducing the Tensor Manipulation Unit (TMU), a reconfigurable, near-memory hardware block designed to efficiently execute data-movement-intensive operators. TMU manipulates long datastreams in a memory-to-memory fashion using a RIS…

AC-DiT: Adaptive Coordination Diffusion Transformer for Mobile Manipulation
Sixiang Chen, Jiaming Liu, Siyuan Qian, Han Jiang, Lily Li, Renrui Zhang, Zhuoyang Liu, Chenyang Gu, Chengkai Hou, Pengwei Wang, Zhongyuan Wang, Shanghang Zhang
https://arxiv.org/abs/2507.01961

AC-DiT: Adaptive Coordination Diffusion Transformer for Mobile Manipulation
Recently, mobile manipulation has attracted increasing attention for enabling language-conditioned robotic control in household tasks. However, existing methods still face challenges in coordinating mobile base and manipulator, primarily due to two limitations. On the one hand, they fail to explicitly model the influence of the mobile base on manipulator control, which easily leads to error accumulation under high degrees of freedom. On the other hand, they treat the entire mobile manipulation …

🍮 Wissen zum Nachtisch: 🍨
Retröt: Der #Kapitalismus braucht für #Wachstum und #Gewinnmaximierung schier endlosen

Die Tricks der Verkäufer: So schützen Sie sich vor Manipulation
Verkäufertricks erkennen: Tipps und Tricks, wie Sie sich vor Manipulation schützen

Strategic Deflection: Defending LLMs from Logit Manipulation
Yassine Rachidy, Jihad Rbaiti, Youssef Hmamouche, Faissal Sehbaoui, Amal El Fallah Seghrouchni
https://arxiv.org/abs/2507.22160

Strategic Deflection: Defending LLMs from Logit Manipulation
With the growing adoption of Large Language Models (LLMs) in critical areas, ensuring their security against jailbreaking attacks is paramount. While traditional defenses primarily rely on refusing malicious prompts, recent logit-level attacks have demonstrated the ability to bypass these safeguards by directly manipulating the token-selection process during generation. We introduce Strategic Deflection (SDeflection), a defense that redefines the LLM's response to such advanced attacks. Instead…

Einige der zuletzt hier besonders häufig geteilten #News:
Manipulation: Strafrechtliche Ermittlungen gegen X in Frankreich

Light Manipulation via Tunable Collective Quantum States in Waveguide-Coupled Bragg and Anti-Bragg Superatoms
Zhengqi Niu, Wei Nie, Daqiang Bao, Xiaoliang He, Wanpeng Gao, Kuang Liu, I. -C. Hoi, Yu-xi Liu, Xiaoming Xie, Zhen Wang, Zhi-Rong Lin
https://arxiv.org/abs/2507.00935

Light Manipulation via Tunable Collective Quantum States in Waveguide-Coupled Bragg and Anti-Bragg Superatoms
A many-body quantum system which consists of collective quantum states, such as superradiant and subradiant states, behaves as a multi-level superatom in light-matter interaction. In this work, we experimentally study one-dimensional superatoms in waveguide quantum electrodynamics with a periodic array of superconducting artificial atoms. We engineer the periodic atomic array with two distinct nearest-neighbor spacings, i.e., $d$=$λ_0/2$ and $d$=$λ_0/4$, which correspond to Bragg and anti-Bra…

Manipulation as in Simulation: Enabling Accurate Geometry Perception in Robots
Minghuan Liu, Zhengbang Zhu, Xiaoshen Han, Peng Hu, Haotong Lin, Xinyao Li, Jingxiao Chen, Jiafeng Xu, Yichu Yang, Yunfeng Lin, Xinghang Li, Yong Yu, Weinan Zhang, Tao Kong, Bingyi Kang
https://arxiv.org/abs/2509.02530

Manipulation as in Simulation: Enabling Accurate Geometry Perception in Robots
Modern robotic manipulation primarily relies on visual observations in a 2D color space for skill learning but suffers from poor generalization. In contrast, humans, living in a 3D world, depend more on physical properties-such as distance, size, and shape-than on texture when interacting with objects. Since such 3D geometric information can be acquired from widely available depth cameras, it appears feasible to endow robots with similar perceptual capabilities. Our pilot study found that using…

ManiFlow: A General Robot Manipulation Policy via Consistency Flow Training
Ge Yan, Jiyue Zhu, Yuquan Deng, Shiqi Yang, Ri-Zhao Qiu, Xuxin Cheng, Marius Memmel, Ranjay Krishna, Ankit Goyal, Xiaolong Wang, Dieter Fox
https://arxiv.org/abs/2509.01819

ManiFlow: A General Robot Manipulation Policy via Consistency Flow Training
This paper introduces ManiFlow, a visuomotor imitation learning policy for general robot manipulation that generates precise, high-dimensional actions conditioned on diverse visual, language and proprioceptive inputs. We leverage flow matching with consistency training to enable high-quality dexterous action generation in just 1-2 inference steps. To handle diverse input modalities efficiently, we propose DiT-X, a diffusion transformer architecture with adaptive cross-attention and AdaLN-Zero c…

Inkjet Printed Liquid Crystal Droplet for Complex Beam Manipulation
Mengmeng Li, Chao He, Steve J. Elston, Yifei Ma, Bohan Chen, Zimo Zhao, Xuke Qiu, Alfonso A. Castrej\'on-Pita, Stephen M. Morris
https://arxiv.org/abs/2507.21826

Inkjet Printed Liquid Crystal Droplet for Complex Beam Manipulation
The inkjet-fabricated liquid crystal (LC) droplet device not only capitalizes on the intrinsic birefringence properties of liquid crystals but also leverages the hemispherical shape of droplet devices on substrates. This configuration facilitates self-alignment of the LC director under the influence of surface tension. The LC droplet devices we fabricated are capable of intricate beam manipulation, encompassing both generation and analysis of light beams. Such devices possess substantial prospe…

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Die Tricks der Verkäufer: So schützen Sie sich vor Manipulation
Verkäufertricks erkennen: Tipps und Tricks, wie Sie sich vor Manipulation schützen

TypeTele: Releasing Dexterity in Teleoperation by Dexterous Manipulation Types
Yuhao Lin, Yi-Lin Wei, Haoran Liao, Mu Lin, Chengyi Xing, Hao Li, Dandan Zhang, Mark Cutkosky, Wei-Shi Zheng
https://arxiv.org/abs/2507.01857

TypeTele: Releasing Dexterity in Teleoperation by Dexterous Manipulation Types
Dexterous teleoperation plays a crucial role in robotic manipulation for real-world data collection and remote robot control. Previous dexterous teleoperation mostly relies on hand retargeting to closely mimic human hand postures. However, these approaches may fail to fully leverage the inherent dexterity of dexterous hands, which can execute unique actions through their structural advantages compared to human hands. To address this limitation, we propose TypeTele, a type-guided dexterous teleo…

All-in-One Slider for Attribute Manipulation in Diffusion Models
Weixin Ye, Hongguang Zhu, Wei Wang, Yahui Liu, Mengyu Wang
https://arxiv.org/abs/2508.19195 https://

All-in-One Slider for Attribute Manipulation in Diffusion Models
Text-to-image (T2I) diffusion models have made significant strides in generating high-quality images. However, progressively manipulating certain attributes of generated images to meet the desired user expectations remains challenging, particularly for content with rich details, such as human faces. Some studies have attempted to address this by training slider modules. However, they follow a One-for-One manner, where an independent slider is trained for each attribute, requiring additional tra…

PRISM: Programmatic Reasoning with Image Sequence Manipulation for LVLM Jailbreaking
Quanchen Zou, Zonghao Ying, Moyang Chen, Wenzhuo Xu, Yisong Xiao, Yakai Li, Deyue Zhang, Dongdong Yang, Zhao Liu, Xiangzheng Zhang
https://arxiv.org/abs/2507.21540

PRISM: Programmatic Reasoning with Image Sequence Manipulation for LVLM Jailbreaking
The increasing sophistication of large vision-language models (LVLMs) has been accompanied by advances in safety alignment mechanisms designed to prevent harmful content generation. However, these defenses remain vulnerable to sophisticated adversarial attacks. Existing jailbreak methods typically rely on direct and semantically explicit prompts, overlooking subtle vulnerabilities in how LVLMs compose information over multiple reasoning steps. In this paper, we propose a novel and effective jai…

HumanoidGen: Data Generation for Bimanual Dexterous Manipulation via LLM Reasoning
Zhi Jing, Siyuan Yang, Jicong Ao, Ting Xiao, Yugang Jiang, Chenjia Bai
https://arxiv.org/abs/2507.00833

HumanoidGen: Data Generation for Bimanual Dexterous Manipulation via LLM Reasoning
For robotic manipulation, existing robotics datasets and simulation benchmarks predominantly cater to robot-arm platforms. However, for humanoid robots equipped with dual arms and dexterous hands, simulation tasks and high-quality demonstrations are notably lacking. Bimanual dexterous manipulation is inherently more complex, as it requires coordinated arm movements and hand operations, making autonomous data collection challenging. This paper presents HumanoidGen, an automated task creation and…

Mehr Präzision bei DNA-Manipulation: KI half bei der Entwicklung
Ein neues Verfahren soll präzise Manipulationen an großen DNA-Abschnitten erlauben. Zum Beweis stellten die Forscher herbizidresistenten Reis her.

Analysis of Drone-Assisted Building Inspection Training in VR vs 2D Monitor Display: an EEG Study
Pengkun Liu, Jackson Greene, Jiali Huang, Pingbo Tang, Yu Hou
https://arxiv.org/abs/2507.01471

Analysis of Drone-Assisted Building Inspection Training in VR vs 2D Monitor Display: an EEG Study
Researchers have been using simulation-based methods for drone-assisted inspection training. Multiple brain regions are associated with information processes and decision-making, and the connectivity of these regions may further influence inspectors' performance. However, researchers do not understand the pathways of the information flows when drone pilots process the maintenance and manipulation of information, which may affect the efficiency of tacit knowledge transfer. This study aims to rev…

H-RDT: Human Manipulation Enhanced Bimanual Robotic Manipulation
Hongzhe Bi, Lingxuan Wu, Tianwei Lin, Hengkai Tan, Zhizhong Su, Hang Su, Jun Zhu
https://arxiv.org/abs/2507.23523

H-RDT: Human Manipulation Enhanced Bimanual Robotic Manipulation
Imitation learning for robotic manipulation faces a fundamental challenge: the scarcity of large-scale, high-quality robot demonstration data. Recent robotic foundation models often pre-train on cross-embodiment robot datasets to increase data scale, while they face significant limitations as the diverse morphologies and action spaces across different robot embodiments make unified training challenging. In this paper, we present H-RDT (Human to Robotics Diffusion Transformer), a novel approach …

Robotic Manipulation by Imitating Generated Videos Without Physical Demonstrations
Shivansh Patel, Shraddhaa Mohan, Hanlin Mai, Unnat Jain, Svetlana Lazebnik, Yunzhu Li
https://arxiv.org/abs/2507.00990

Robotic Manipulation by Imitating Generated Videos Without Physical Demonstrations
This work introduces Robots Imitating Generated Videos (RIGVid), a system that enables robots to perform complex manipulation tasks--such as pouring, wiping, and mixing--purely by imitating AI-generated videos, without requiring any physical demonstrations or robot-specific training. Given a language command and an initial scene image, a video diffusion model generates potential demonstration videos, and a vision-language model (VLM) automatically filters out results that do not follow the comm…

Emotional Manipulation by AI Companions
Julian De Freitas, Zeliha O\u{g}uz-U\u{g}uralp, Ahmet Kaan-U\u{g}uralp
https://arxiv.org/abs/2508.19258 https://arx…

Emotional Manipulation by AI Companions
AI-companion apps such as Replika, Chai, and Character.ai promise relational benefits-yet many boast session lengths that rival gaming platforms while suffering high long-run churn. What conversational design features increase consumer engagement, and what trade-offs do they pose for marketers? We combine a large-scale behavioral audit with four preregistered experiments to identify and test a conversational dark pattern we call emotional manipulation: affect-laden messages that surface precise…

U-ARM : Ultra low-cost general teleoperation interface for robot manipulation
Yanwen Zou, Zhaoye Zhou, Chenyang Shi, Zewei Ye, Junda Huang, Yan Ding, Bo Zhao
https://arxiv.org/abs/2509.02437

U-ARM : Ultra low-cost general teleoperation interface for robot manipulation
We propose U-Arm, a low-cost and rapidly adaptable leader-follower teleoperation framework designed to interface with most of commercially available robotic arms. Our system supports teleoperation through three structurally distinct 3D-printed leader arms that share consistent control logic, enabling seamless compatibility with diverse commercial robot configurations. Compared with previous open-source leader-follower interfaces, we further optimized both the mechanical design and servo selecti…

Optical charge state manipulation of lead-vacancy centers in diamond
Yiyang Chen, Yoshiyuki Miyamoto, Eiki Ota, Ryotaro Abe, Takashi Taniguchi, Shinobu Onoda, Mutsuko Hatano, Takayuki Iwasaki
https://arxiv.org/abs/2508.18991

Optical charge state manipulation of lead-vacancy centers in diamond
Group-IV vacancy centers in diamond exhibit excellent optical and spin coherence properties, making them highly promising and scalable spin qubit candidates. Since only specific charge states are magneto-optically active, control over the charge state is fundamental for quantum applications. Here, we realize the charge state control of lead-vacancy centers (PbV) through multi-color laser irradiation. We achieve tunable population manipulation of the negatively charged state from 0 to 89%, pavin…

RoboEval: Where Robotic Manipulation Meets Structured and Scalable Evaluation
Yi Ru Wang, Carter Ung, Grant Tannert, Jiafei Duan, Josephine Li, Amy Le, Rishabh Oswal, Markus Grotz, Wilbert Pumacay, Yuquan Deng, Ranjay Krishna, Dieter Fox, Siddhartha Srinivasa
https://arxiv.org/abs/2507.00435…

RoboEval: Where Robotic Manipulation Meets Structured and Scalable Evaluation
We present RoboEval, a simulation benchmark and structured evaluation framework designed to reveal the limitations of current bimanual manipulation policies. While prior benchmarks report only binary task success, we show that such metrics often conceal critical weaknesses in policy behavior -- such as poor coordination, slipping during grasping, or asymmetric arm usage. RoboEval introduces a suite of tiered, semantically grounded tasks decomposed into skill-specific stages, with variations tha…

DexWrist: A Robotic Wrist for Constrained and Dynamic Manipulation
Martin Peticco, Gabriella Ulloa, John Marangola, Pulkit Agrawal
https://arxiv.org/abs/2507.01008

DexWrist: A Robotic Wrist for Constrained and Dynamic Manipulation
We present the DexWrist, a compliant robotic wrist designed to advance robotic manipulation in highly-constrained environments, enable dynamic tasks, and speed up data collection. DexWrist is designed to be close to the functional capabilities of the human wrist and achieves mechanical compliance and a greater workspace as compared to existing robotic wrist designs. The DexWrist can supercharge policy learning by (i) enabling faster teleoperation and therefore making data collection more scalab…

Lightweight Fingernail Haptic Device: Unobstructed Fingerpad Force and Vibration Feedback for Enhanced Virtual Dexterous Manipulation
Yunxiu Xu, Siyu Wang, Shoichi Hasegawa
https://arxiv.org/abs/2506.21417

Lightweight Fingernail Haptic Device: Unobstructed Fingerpad Force and Vibration Feedback for Enhanced Virtual Dexterous Manipulation
This study presents a lightweight, wearable fingertip haptic device that provides physics-based haptic feedback for dexterous manipulation in virtual environments without hindering real-world interactions. The device, designed with thin strings and actuators attached to the fingernails, ensures minimal weight (1.55 g per finger) and preserves finger flexibility. Integrating the software with a physics engine renders multiple types of haptic feedback (grip force, collision, and sliding vibration…

Periodic robust robotic rock chop via virtual model control
Yi Zhang, Fumiya Iida, Fulvio Forni
https://arxiv.org/abs/2508.02604 https://arxiv.org/pdf/2508…

Periodic robust robotic rock chop via virtual model control
Robotic cutting is a challenging contact-rich manipulation task where the robot must simultaneously negotiate unknown object mechanics, large contact forces, and precise motion requirements. We introduce a new virtual-model control scheme that enables knife rocking motion for robot manipulators, without pre-planned trajectories or precise information of the environment. Motion is generated through interconnection with virtual mechanisms, given by virtual springs, dampers, and masses arranged in…

cVLA: Towards Efficient Camera-Space VLAs
Max Argus, Jelena Bratulic, Houman Masnavi, Maxim Velikanov, Nick Heppert, Abhinav Valada, Thomas Brox
https://arxiv.org/abs/2507.02190

cVLA: Towards Efficient Camera-Space VLAs
Vision-Language-Action (VLA) models offer a compelling framework for tackling complex robotic manipulation tasks, but they are often expensive to train. In this paper, we propose a novel VLA approach that leverages the competitive performance of Vision Language Models (VLMs) on 2D images to directly infer robot end-effector poses in image frame coordinates. Unlike prior VLA models that output low-level controls, our model predicts trajectory waypoints, making it both more efficient to train and…

Towards Bio-Inspired Robotic Trajectory Planning via Self-Supervised RNN
Miroslav Cibula, Krist\'ina Malinovsk\'a, Matthias Kerzel
https://arxiv.org/abs/2507.02171

Towards Bio-Inspired Robotic Trajectory Planning via Self-Supervised RNN
Trajectory planning in robotics is understood as generating a sequence of joint configurations that will lead a robotic agent, or its manipulator, from an initial state to the desired final state, thus completing a manipulation task while considering constraints like robot kinematics and the environment. Typically, this is achieved via sampling-based planners, which are computationally intensive. Recent advances demonstrate that trajectory planning can also be performed by supervised sequence l…

MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects
Yuying Zhang, Kevin Sebastian Luck, Francesco Verdoja, Ville Kyrki, Joni Pajarinen
https://arxiv.org/abs/2507.21796

MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects
Mobile manipulation is a critical capability for robots operating in diverse, real-world environments. However, manipulating deformable objects and materials remains a major challenge for existing robot learning algorithms. While various benchmarks have been proposed to evaluate manipulation strategies with rigid objects, there is still a notable lack of standardized benchmarks that address mobile manipulation tasks involving deformable objects. To address this gap, we introduce MoDeSuite, th…

FrankenBot: Brain-Morphic Modular Orchestration for Robotic Manipulation with Vision-Language Models
Shiyi Wang, Wenbo Li, Yiteng Chen, Qingyao Wu, Huiping Zhuang
https://arxiv.org/abs/2506.21627

FrankenBot: Brain-Morphic Modular Orchestration for Robotic Manipulation with Vision-Language Models
Developing a general robot manipulation system capable of performing a wide range of tasks in complex, dynamic, and unstructured real-world environments has long been a challenging task. It is widely recognized that achieving human-like efficiency and robustness manipulation requires the robotic brain to integrate a comprehensive set of functions, such as task planning, policy generation, anomaly monitoring and handling, and long-term memory, achieving high-efficiency operation across all funct…

Quadratic Programming-Based Posture Manipulation and Thrust-vectoring for Agile Dynamic Walking on Narrow Pathways
Chenghao Wang, Eric Sihite, Kaushik Venkatesh Krishnamurthy, Shreyansh Pitroda, Adarsh Salagame, Alireza Ramezani, Morteza Gharib
https://arxiv.org/abs/2507.23203

Quadratic Programming-Based Posture Manipulation and Thrust-vectoring for Agile Dynamic Walking on Narrow Pathways
There has been significant advancement in legged robot's agility where they can show impressive acrobatic maneuvers, such as parkour. These maneuvers rely heavily on posture manipulation. To expand the stability and locomotion plasticity, we use the multi-modal ability in our legged-aerial platform, the Husky Beta, to perform thruster-assisted walking. This robot has thrusters on each of its sagittal knee joints which can be used to stabilize its frontal dynamic as it walks. In this work, we pe…

PAC Bench: Do Foundation Models Understand Prerequisites for Executing Manipulation Policies?
Atharva Gundawar, Som Sagar, Ransalu Senanayake
https://arxiv.org/abs/2506.23725

PAC Bench: Do Foundation Models Understand Prerequisites for Executing Manipulation Policies?
Vision-Language Models (VLMs) are increasingly pivotal for generalist robot manipulation, enabling tasks such as physical reasoning, policy generation, and failure detection. However, their proficiency in these high-level applications often assumes a deep understanding of low-level physical prerequisites, a capability that remains largely unverified. For robots to perform actions reliably, they must comprehend intrinsic object properties (e.g., material, weight), action affordances (e.g., grasp…

RoboInspector: Unveiling the Unreliability of Policy Code for LLM-enabled Robotic Manipulation
Chenduo Ying, Linkang Du, Peng Cheng, Yuanchao Shu
https://arxiv.org/abs/2508.21378

RoboInspector: Unveiling the Unreliability of Policy Code for LLM-enabled Robotic Manipulation
Large language models (LLMs) demonstrate remarkable capabilities in reasoning and code generation, enabling robotic manipulation to be initiated with just a single instruction. The LLM carries out various tasks by generating policy code required to control the robot. Despite advances in LLMs, achieving reliable policy code generation remains a significant challenge due to the diverse requirements of real-world tasks and the inherent complexity of user instructions. In practice, different users …

CLASP: General-Purpose Clothes Manipulation with Semantic Keypoints
Yuhong Deng, Chao Tang, Cunjun Yu, Linfeng Li, David Hsu
https://arxiv.org/abs/2507.19983 https://

CLASP: General-Purpose Clothes Manipulation with Semantic Keypoints
Clothes manipulation, such as folding or hanging, is a critical capability for home service robots. Despite recent advances, most existing methods remain limited to specific tasks and clothes types, due to the complex, high-dimensional geometry of clothes. This paper presents CLothes mAnipulation with Semantic keyPoints (CLASP), which aims at general-purpose clothes manipulation over different clothes types, T-shirts, shorts, skirts, long dresses, ... , as well as different tasks, folding, flat…

A Nonlinear MPC Framework for Loco-Manipulation of Quadrupedal Robots with Non-Negligible Manipulator Dynamics
Ruturaj Sambhus, Kapi Ketan Mehta, Ali MirMohammad Sadeghi, Basit Muhammad Imran, Jeeseop Kim, Taizoon Chunawala, Vittorio Pastore, Sujith Vijayan, Kaveh Akbari Hamed
https://arxiv.org/abs/2507.22042…

A Nonlinear MPC Framework for Loco-Manipulation of Quadrupedal Robots with Non-Negligible Manipulator Dynamics
Model predictive control (MPC) combined with reduced-order template models has emerged as a powerful tool for trajectory optimization in dynamic legged locomotion. However, loco-manipulation tasks performed by legged robots introduce additional complexity, necessitating computationally efficient MPC algorithms capable of handling high-degree-of-freedom (DoF) models. This letter presents a computationally efficient nonlinear MPC (NMPC) framework tailored for loco-manipulation tasks of quadrupeda…

Autonomous Aerial Manipulation at Arbitrary Pose in SE(3) with Robust Control and Whole-body Planning
Dongjae Lee, Byeongjun Kim, H. Jin Kim
https://arxiv.org/abs/2508.19608 htt…

Autonomous Aerial Manipulation at Arbitrary Pose in SE(3) with Robust Control and Whole-body Planning
Aerial manipulators based on conventional multirotors can conduct manipulation only in small roll and pitch angles due to the underactuatedness of the multirotor base. If the multirotor base is capable of hovering at arbitrary orientation, the robot can freely locate itself at any point in $\mathsf{SE}(3)$, significantly extending its manipulation workspace and enabling a manipulation task that was originally not viable. In this work, we present a geometric robust control and whole-body motion …

Integration of Robot and Scene Kinematics for Sequential Mobile Manipulation Planning
Ziyuan Jiao, Yida Niu, Zeyu Zhang, Yangyang Wu, Yao Su, Yixin Zhu, Hangxin Liu, Song-Chun Zhu
https://arxiv.org/abs/2508.18627

Integration of Robot and Scene Kinematics for Sequential Mobile Manipulation Planning
We present a Sequential Mobile Manipulation Planning (SMMP) framework that can solve long-horizon multi-step mobile manipulation tasks with coordinated whole-body motion, even when interacting with articulated objects. By abstracting environmental structures as kinematic models and integrating them with the robot's kinematics, we construct an Augmented Configuration Apace (A-Space) that unifies the previously separate task constraints for navigation and manipulation, while accounting for the jo…

Dynamics-Compliant Trajectory Diffusion for Super-Nominal Payload Manipulation
Anuj Pasricha, Joewie Koh, Jay Vakil, Alessandro Roncone
https://arxiv.org/abs/2508.21375 https://…

Dynamics-Compliant Trajectory Diffusion for Super-Nominal Payload Manipulation
Nominal payload ratings for articulated robots are typically derived from worst-case configurations, resulting in uniform payload constraints across the entire workspace. This conservative approach severely underutilizes the robot's inherent capabilities -- our analysis demonstrates that manipulators can safely handle payloads well above nominal capacity across broad regions of their workspace while staying within joint angle, velocity, acceleration, and torque limits. To address this gap betwe…

Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference
Yixuan Huang, Novella Alvina, Mohanraj Devendran Shanthi, Tucker Hermans
https://arxiv.org/abs/2509.01746

Fail2Progress: Learning from Real-World Robot Failures with Stein Variational Inference
Skill effect models for long-horizon manipulation tasks are prone to failures in conditions not covered by training data distributions. Therefore, enabling robots to reason about and learn from failures is necessary. We investigate the problem of efficiently generating a dataset targeted to observed failures. After fine-tuning a skill effect model on this dataset, we evaluate the extent to which the model can recover from failures and minimize future failures. We propose Fail2Progress, an appro…

HERMES: Human-to-Robot Embodied Learning from Multi-Source Motion Data for Mobile Dexterous Manipulation
Zhecheng Yuan, Tianming Wei, Langzhe Gu, Pu Hua, Tianhai Liang, Yuanpei Chen, Huazhe Xu
https://arxiv.org/abs/2508.20085

HERMES: Human-to-Robot Embodied Learning from Multi-Source Motion Data for Mobile Dexterous Manipulation
Leveraging human motion data to impart robots with versatile manipulation skills has emerged as a promising paradigm in robotic manipulation. Nevertheless, translating multi-source human hand motions into feasible robot behaviors remains challenging, particularly for robots equipped with multi-fingered dexterous hands characterized by complex, high-dimensional action spaces. Moreover, existing approaches often struggle to produce policies capable of adapting to diverse environmental conditions.…

LaVA-Man: Learning Visual Action Representations for Robot Manipulation
Chaoran Zhu, Hengyi Wang, Yik Lung Pang, Changjae Oh
https://arxiv.org/abs/2508.19391 https://

LaVA-Man: Learning Visual Action Representations for Robot Manipulation
Visual-textual understanding is essential for language-guided robot manipulation. Recent works leverage pre-trained vision-language models to measure the similarity between encoded visual observations and textual instructions, and then train a model to map this similarity to robot actions. However, this two-step approach limits the model to capture the relationship between visual observations and textual instructions, leading to reduced precision in manipulation tasks. We propose to learn visua…

Articulated Object Estimation in the Wild
Abdelrhman Werby, Martin B\"uchner, Adrian R\"ofer, Chenguang Huang, Wolfram Burgard, Abhinav Valada
https://arxiv.org/abs/2509.01708

Articulated Object Estimation in the Wild
Understanding the 3D motion of articulated objects is essential in robotic scene understanding, mobile manipulation, and motion planning. Prior methods for articulation estimation have primarily focused on controlled settings, assuming either fixed camera viewpoints or direct observations of various object states, which tend to fail in more realistic unconstrained environments. In contrast, humans effortlessly infer articulation by watching others manipulate objects. Inspired by this, we introd…

SafeBimanual: Diffusion-based Trajectory Optimization for Safe Bimanual Manipulation
Haoyuan Deng, Wenkai Guo, Qianzhun Wang, Zhenyu Wu, Ziwei Wang
https://arxiv.org/abs/2508.18268

SafeBimanual: Diffusion-based Trajectory Optimization for Safe Bimanual Manipulation
Bimanual manipulation has been widely applied in household services and manufacturing, which enables the complex task completion with coordination requirements. Recent diffusion-based policy learning approaches have achieved promising performance in modeling action distributions for bimanual manipulation. However, they ignored the physical safety constraints of bimanual manipulation, which leads to the dangerous behaviors with damage to robots and objects. To this end, we propose a test-time tr…

Physics-Informed Machine Learning with Adaptive Grids for Optical Microrobot Depth Estimation
Lan Wei, Lou Genoud, Dandan Zhang
https://arxiv.org/abs/2509.02343 https://

Physics-Informed Machine Learning with Adaptive Grids for Optical Microrobot Depth Estimation
Optical microrobots actuated by optical tweezers (OT) offer great potential for biomedical applications such as cell manipulation and microscale assembly. These tasks demand accurate three-dimensional perception to ensure precise control in complex and dynamic biological environments. However, the transparent nature of microrobots and low-contrast microscopic imaging challenge conventional deep learning methods, which also require large annotated datasets that are costly to obtain. To address t…

Align-Then-stEer: Adapting the Vision-Language Action Models through Unified Latent Guidance
Yang Zhang, Chenwei Wang, Ouyang Lu, Yuan Zhao, Yunfei Ge, Zhenglong Sun, Xiu Li, Chi Zhang, Chenjia Bai, Xuelong Li
https://arxiv.org/abs/2509.02055

Align-Then-stEer: Adapting the Vision-Language Action Models through Unified Latent Guidance
Vision-Language-Action (VLA) models pre-trained on large, diverse datasets show remarkable potential for general-purpose robotic manipulation. However, a primary bottleneck remains in adapting these models to downstream tasks, especially when the robot's embodiment or the task itself differs from the pre-training data. This discrepancy leads to a significant mismatch in action distributions, demanding extensive data and compute for effective fine-tuning. To address this challenge, we introduce …

Adaptive Articulated Object Manipulation On The Fly with Foundation Model Reasoning and Part Grounding
Xiaojie Zhang, Yuanfei Wang, Ruihai Wu, Kunqi Xu, Yu Li, Liuyu Xiang, Hao Dong, Zhaofeng He
https://arxiv.org/abs/2507.18276

Adaptive Articulated Object Manipulation On The Fly with Foundation Model Reasoning and Part Grounding
Articulated objects pose diverse manipulation challenges for robots. Since their internal structures are not directly observable, robots must adaptively explore and refine actions to generate successful manipulation trajectories. While existing works have attempted cross-category generalization in adaptive articulated object manipulation, two major challenges persist: (1) the geometric diversity of real-world articulated objects complicates visual perception and understanding, and (2) variation…

Bipedalism for Quadrupedal Robots: Versatile Loco-Manipulation through Risk-Adaptive Reinforcement Learning
Yuyou Zhang, Radu Corcodel, Ding Zhao
https://arxiv.org/abs/2507.20382

Bipedalism for Quadrupedal Robots: Versatile Loco-Manipulation through Risk-Adaptive Reinforcement Learning
Loco-manipulation of quadrupedal robots has broadened robotic applications, but using legs as manipulators often compromises locomotion, while mounting arms complicates the system. To mitigate this issue, we introduce bipedalism for quadrupedal robots, thus freeing the front legs for versatile interactions with the environment. We propose a risk-adaptive distributional Reinforcement Learning (RL) framework designed for quadrupedal robots walking on their hind legs, balancing worst-case conserva…

AutoRing: Imitation Learning--based Autonomous Intraocular Foreign Body Removal Manipulation with Eye Surgical Robot
Yue Wang, Wenjie Deng, Haotian Xue, Di Cui, Yiqi Chen, Mingchuan Zhou, Haochao Ying, Jian Wu
https://arxiv.org/abs/2508.19191

AutoRing: Imitation Learning--based Autonomous Intraocular Foreign Body Removal Manipulation with Eye Surgical Robot
Intraocular foreign body removal demands millimeter-level precision in confined intraocular spaces, yet existing robotic systems predominantly rely on manual teleoperation with steep learning curves. To address the challenges of autonomous manipulation (particularly kinematic uncertainties from variable motion scaling and variation of the Remote Center of Motion (RCM) point), we propose AutoRing, an imitation learning framework for autonomous intraocular foreign body ring manipulation. Our appr…

Long-VLA: Unleashing Long-Horizon Capability of Vision Language Action Model for Robot Manipulation
Yiguo Fan, Pengxiang Ding, Shuanghao Bai, Xinyang Tong, Yuyang Zhu, Hongchao Lu, Fengqi Dai, Wei Zhao, Yang Liu, Siteng Huang, Zhaoxin Fan, Badong Chen, Donglin Wang
https://arxiv.org/abs/2508.19958 …

Long-VLA: Unleashing Long-Horizon Capability of Vision Language Action Model for Robot Manipulation
Vision-Language-Action (VLA) models have become a cornerstone in robotic policy learning, leveraging large-scale multimodal data for robust and scalable control. However, existing VLA frameworks primarily address short-horizon tasks, and their effectiveness on long-horizon, multi-step robotic manipulation remains limited due to challenges in skill chaining and subtask dependencies. In this work, we introduce Long-VLA, the first end-to-end VLA model specifically designed for long-horizon robotic…

Robotic Manipulation of a Rotating Chain with Bottom End Fixed
Qi Jing Chen, Shilin Shan, Quang-Cuong Pham
https://arxiv.org/abs/2506.18355 https://…

Robotic Manipulation of a Rotating Chain with Bottom End Fixed
This paper studies the problem of using a robot arm to manipulate a uniformly rotating chain with its bottom end fixed. Existing studies have investigated ideal rotational shapes for practical applications, yet they do not discuss how these shapes can be consistently achieved through manipulation planning. Our work presents a manipulation strategy for stable and consistent shape transitions. We find that the configuration space of such a chain is homeomorphic to a three-dimensional cube. Using …

Kinematic Model Optimization via Differentiable Contact Manifold for In-Space Manipulation
Abhay Negi, Omey M. Manyar, Satyandra K. Gupta
https://arxiv.org/abs/2506.17458

Kinematic Model Optimization via Differentiable Contact Manifold for In-Space Manipulation
Robotic manipulation in space is essential for emerging applications such as debris removal and in-space servicing, assembly, and manufacturing (ISAM). A key requirement for these tasks is the ability to perform precise, contact-rich manipulation under significant uncertainty. In particular, thermal-induced deformation of manipulator links and temperature-dependent encoder bias introduce kinematic parameter errors that significantly degrade end-effector accuracy. Traditional calibration techniq…

Reflective VLM Planning for Dual-Arm Desktop Cleaning: Bridging Open-Vocabulary Perception and Precise Manipulation
Yufan Liu, Yi Wu, Gweneth Ge, Haoliang Cheng, Rui Liu
https://arxiv.org/abs/2506.17328

Reflective VLM Planning for Dual-Arm Desktop Cleaning: Bridging Open-Vocabulary Perception and Precise Manipulation
Desktop cleaning demands open-vocabulary recognition and precise manipulation for heterogeneous debris. We propose a hierarchical framework integrating reflective Vision-Language Model (VLM) planning with dual-arm execution via structured scene representation. Grounded-SAM2 facilitates open-vocabulary detection, while a memory-augmented VLM generates, critiques, and revises manipulation sequences. These sequences are converted into parametric trajectories for five primitives executed by coordin…

Object-Centric Mobile Manipulation through SAM2-Guided Perception and Imitation Learning
Wang Zhicheng, Satoshi Yagi, Satoshi Yamamori, Jun Morimoto
https://arxiv.org/abs/2507.10899

Object-Centric Mobile Manipulation through SAM2-Guided Perception and Imitation Learning
Imitation learning for mobile manipulation is a key challenge in the field of robotic manipulation. However, current mobile manipulation frameworks typically decouple navigation and manipulation, executing manipulation only after reaching a certain location. This can lead to performance degradation when navigation is imprecise, especially due to misalignment in approach angles. To enable a mobile manipulator to perform the same task from diverse orientations, an essential capability for buildin…

HyperTASR: Hypernetwork-Driven Task-Aware Scene Representations for Robust Manipulation
Li Sun, Jiefeng Wu, Feng Chen, Ruizhe Liu, Yanchao Yang
https://arxiv.org/abs/2508.18802 …

HyperTASR: Hypernetwork-Driven Task-Aware Scene Representations for Robust Manipulation
Effective policy learning for robotic manipulation requires scene representations that selectively capture task-relevant environmental features. Current approaches typically employ task-agnostic representation extraction, failing to emulate the dynamic perceptual adaptation observed in human cognition. We present HyperTASR, a hypernetwork-driven framework that modulates scene representations based on both task objectives and the execution phase. Our architecture dynamically generates representa…

MemoryVLA: Perceptual-Cognitive Memory in Vision-Language-Action Models for Robotic Manipulation
Hao Shi, Bin Xie, Yingfei Liu, Lin Sun, Fengrong Liu, Tiancai Wang, Erjin Zhou, Haoqiang Fan, Xiangyu Zhang, Gao Huang
https://arxiv.org/abs/2508.19236

MemoryVLA: Perceptual-Cognitive Memory in Vision-Language-Action Models for Robotic Manipulation
Temporal context is essential for robotic manipulation because such tasks are inherently non-Markovian, yet mainstream VLA models typically overlook it and struggle with long-horizon, temporally dependent tasks. Cognitive science suggests that humans rely on working memory to buffer short-lived representations for immediate control, while the hippocampal system preserves verbatim episodic details and semantic gist of past experience for long-term memory. Inspired by these mechanisms, we propose…

Novel Pigeon-inspired 3D Obstacle Detection and Avoidance Maneuver for Multi-UAV Systems
Reza Ahmadvand, Sarah Safura Sharif, Yaser Mike Banad
https://arxiv.org/abs/2507.00443

Novel Pigeon-inspired 3D Obstacle Detection and Avoidance Maneuver for Multi-UAV Systems
Recent advances in multi-agent systems manipulation have demonstrated a rising demand for the implementation of multi-UAV systems in urban areas, which are always subjected to the presence of static and dynamic obstacles. Inspired by the collective behavior of tilapia fish and pigeons, the focus of the presented research is on the introduction of a nature-inspired collision-free formation control for a multi-UAV system, considering the obstacle avoidance maneuvers. The developed framework in th…

Language-Enhanced Mobile Manipulation for Efficient Object Search in Indoor Environments
Liding Zhang, Zeqi Li, Kuanqi Cai, Qian Huang, Zhenshan Bing, Alois Knoll
https://arxiv.org/abs/2508.20899

Language-Enhanced Mobile Manipulation for Efficient Object Search in Indoor Environments
Enabling robots to efficiently search for and identify objects in complex, unstructured environments is critical for diverse applications ranging from household assistance to industrial automation. However, traditional scene representations typically capture only static semantics and lack interpretable contextual reasoning, limiting their ability to guide object search in completely unfamiliar settings. To address this challenge, we propose a language-enhanced hierarchical navigation framework …

Robot Excavation and Manipulation of Geometrically Cohesive Granular Media
Laura Treers, Daniel Soto, Joonha Hwang, Michael A. D. Goodisman, Daniel I. Goldman
https://arxiv.org/abs/2507.19999

Robot Excavation and Manipulation of Geometrically Cohesive Granular Media
Construction throughout history typically assumes that its blueprints and building blocks are pre-determined. However, recent work suggests that alternative approaches can enable new paradigms for structure formation. Aleatory architectures, or those which rely on the properties of their granular building blocks rather than pre-planned design or computation, have thus far relied on human intervention for their creation. We imagine that robotic swarms could be valuable to create such aleatory st…

Prompt-to-Product: Generative Assembly via Bimanual Manipulation
Ruixuan Liu, Philip Huang, Ava Pun, Kangle Deng, Shobhit Aggarwal, Kevin Tang, Michelle Liu, Deva Ramanan, Jun-Yan Zhu, Jiaoyang Li, Changliu Liu
https://arxiv.org/abs/2508.21063

Prompt-to-Product: Generative Assembly via Bimanual Manipulation
Creating assembly products demands significant manual effort and expert knowledge in 1) designing the assembly and 2) constructing the product. This paper introduces Prompt-to-Product, an automated pipeline that generates real-world assembly products from natural language prompts. Specifically, we leverage LEGO bricks as the assembly platform and automate the process of creating brick assembly structures. Given the user design requirements, Prompt-to-Product generates physically buildable brick…

Heterogeneous object manipulation on nonlinear soft surface through linear controller
Pratik Ingle, Kasper St{\o}y, Andres Fai\~na
https://arxiv.org/abs/2507.14967

Heterogeneous object manipulation on nonlinear soft surface through linear controller
Manipulation surfaces indirectly control and reposition objects by actively modifying their shape or properties rather than directly gripping objects. These surfaces, equipped with dense actuator arrays, generate dynamic deformations. However, a high-density actuator array introduces considerable complexity due to increased degrees of freedom (DOF), complicating control tasks. High DOF restrict the implementation and utilization of manipulation surfaces in real-world applications as the mainten…

DefFusionNet: Learning Multimodal Goal Shapes for Deformable Object Manipulation via a Diffusion-based Probabilistic Model
Bao Thach, Siyeon Kim, Britton Jordan, Mohanraj Shanthi, Tanner Watts, Shing-Hei Ho, James M. Ferguson, Tucker Hermans, Alan Kuntz
https://arxiv.org/abs/2506.18779

DefFusionNet: Learning Multimodal Goal Shapes for Deformable Object Manipulation via a Diffusion-based Probabilistic Model
Deformable object manipulation is critical to many real-world robotic applications, ranging from surgical robotics and soft material handling in manufacturing to household tasks like laundry folding. At the core of this important robotic field is shape servoing, a task focused on controlling deformable objects into desired shapes. The shape servoing formulation requires the specification of a goal shape. However, most prior works in shape servoing rely on impractical goal shape acquisition meth…

PinchBot: Long-Horizon Deformable Manipulation with Guided Diffusion Policy
Alison Bartsch, Arvind Car, Amir Barati Farimani
https://arxiv.org/abs/2507.17846 https://

PinchBot: Long-Horizon Deformable Manipulation with Guided Diffusion Policy
Pottery creation is a complicated art form that requires dexterous, precise and delicate actions to slowly morph a block of clay to a meaningful, and often useful 3D goal shape. In this work, we aim to create a robotic system that can create simple pottery goals with only pinch-based actions. This pinch pottery task allows us to explore the challenges of a highly multi-modal and long-horizon deformable manipulation task. To this end, we present PinchBot, a goal-conditioned diffusion policy mode…

Spatial Policy: Guiding Visuomotor Robotic Manipulation with Spatial-Aware Modeling and Reasoning
Yijun Liu, Yuwei Liu, Yuan Meng, Jieheng Zhang, Yuwei Zhou, Ye Li, Jiacheng Jiang, Kangye Ji, Shijia Ge, Zhi Wang, Wenwu Zhu
https://arxiv.org/abs/2508.15874

Spatial Policy: Guiding Visuomotor Robotic Manipulation with Spatial-Aware Modeling and Reasoning
Vision-centric hierarchical embodied models have demonstrated strong potential for long-horizon robotic control. However, existing methods lack spatial awareness capabilities, limiting their effectiveness in bridging visual plans to actionable control in complex environments. To address this problem, we propose Spatial Policy (SP), a unified spatial-aware visuomotor robotic manipulation framework via explicit spatial modeling and reasoning. Specifically, we first design a spatial-conditioned em…