Tootfinder

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…

Latent Action Diffusion for Cross-Embodiment Manipulation
Erik Bauer, Elvis Nava, Robert K. Katzschmann
https://arxiv.org/abs/2506.14608 https://

Latent Action Diffusion for Cross-Embodiment Manipulation
End-to-end learning approaches offer great potential for robotic manipulation, but their impact is constrained by data scarcity and heterogeneity across different embodiments. In particular, diverse action spaces across different end-effectors create barriers for cross-embodiment learning and skill transfer. We address this challenge through diffusion policies learned in a latent action space that unifies diverse end-effector actions. We first show that we can learn a semantically aligned laten…

ChatbotManip: A Dataset to Facilitate Evaluation and Oversight of Manipulative Chatbot Behaviour
Jack Contro, Simrat Deol, Yulan He, Martim Brand\~ao
https://arxiv.org/abs/2506.12090

ChatbotManip: A Dataset to Facilitate Evaluation and Oversight of Manipulative Chatbot Behaviour
This paper introduces ChatbotManip, a novel dataset for studying manipulation in Chatbots. It contains simulated generated conversations between a chatbot and a (simulated) user, where the chatbot is explicitly asked to showcase manipulation tactics, persuade the user towards some goal, or simply be helpful. We consider a diverse set of chatbot manipulation contexts, from consumer and personal advice to citizen advice and controversial proposition argumentation. Each conversation is annotated b…

RobotSmith: Generative Robotic Tool Design for Acquisition of Complex Manipulation Skills
Chunru Lin, Haotian Yuan, Yian Wang, Xiaowen Qiu, Tsun-Hsuan Wang, Minghao Guo, Bohan Wang, Yashraj Narang, Dieter Fox, Chuang Gan
https://arxiv.org/abs/2506.14763

RobotSmith: Generative Robotic Tool Design for Acquisition of Complex Manipulation Skills
Endowing robots with tool design abilities is critical for enabling them to solve complex manipulation tasks that would otherwise be intractable. While recent generative frameworks can automatically synthesize task settings, such as 3D scenes and reward functions, they have not yet addressed the challenge of tool-use scenarios. Simply retrieving human-designed tools might not be ideal since many tools (e.g., a rolling pin) are difficult for robotic manipulators to handle. Furthermore, existing …

Controlled manipulation of solitons in a recirculating fiber loop using external potentials
Fran\c{c}ois Copie, Pierre Suret, St\'ephane Randoux
https://arxiv.org/abs/2506.13544

Controlled manipulation of solitons in a recirculating fiber loop using external potentials
Optical solitons are self-sustained wave packets that propagate without distortion due to a balance between dispersion and nonlinearity. Their unique stability underpins key photonic applications while also playing a central role in nonlinear wave physics. However, real-time control over soliton dynamics in non-dissipative systems remains a major challenge, limiting their practical applications in photonic systems. Here, we introduce a fiber-based platform for soliton manipulation, by creating …

Tactile Beyond Pixels: Multisensory Touch Representations for Robot Manipulation
Carolina Higuera, Akash Sharma, Taosha Fan, Chaithanya Krishna Bodduluri, Byron Boots, Michael Kaess, Mike Lambeta, Tingfan Wu, Zixi Liu, Francois Robert Hogan, Mustafa Mukadam
https://arxiv.org/abs/2506.14754…

Tactile Beyond Pixels: Multisensory Touch Representations for Robot Manipulation
We present Sparsh-X, the first multisensory touch representations across four tactile modalities: image, audio, motion, and pressure. Trained on ~1M contact-rich interactions collected with the Digit 360 sensor, Sparsh-X captures complementary touch signals at diverse temporal and spatial scales. By leveraging self-supervised learning, Sparsh-X fuses these modalities into a unified representation that captures physical properties useful for robot manipulation tasks. We study how to effectively …

Alphabet Index Mapping: Jailbreaking LLMs through Semantic Dissimilarity
Bilal Saleh Husain
https://arxiv.org/abs/2506.12685 https://…

Alphabet Index Mapping: Jailbreaking LLMs through Semantic Dissimilarity
Large Language Models (LLMs) have demonstrated remarkable capabilities, yet their susceptibility to adversarial attacks, particularly jailbreaking, poses significant safety and ethical concerns. While numerous jailbreak methods exist, many suffer from computational expense, high token usage, or complex decoding schemes. Liu et al. (2024) introduced FlipAttack, a black-box method that achieves high attack success rates (ASR) through simple prompt manipulation. This paper investigates the underly…

It’s especially frustrating because there •is• election manipulation happening in plain sight: voter suppression, gerrymandering, a vast media empire of right-wing falsehood, microtargeted disinformation from billionaires and hostile foreign states alike, GOP- and Putin-backed grifters posing as left-leaning third party candidates and then just pocketing the donations and disappearing —
•none• of that even in doubt. We do not need to search for a shadowy conspiracy. Democracy’s being strangled in broad daylight.
2/

Crystal field tuned spin-flip luminescence in NiPS3
L\'eonard Schue, Nashra Pistawala, Hebatalla Elnaggar, Yannick Klein, Christophe Bellin, Johan Biscaras, Fausto Sirotti, Yves Lassailly, Fabian Cadiz, Luminita Harnagea, Abhay Shukla
https://arxiv.org/abs/2506.13381

Crystal field tuned spin-flip luminescence in NiPS3
Layered magnetic materials potentially hold the key to future applications based on optical control and manipulation of magnetism. NiPS3, a prototype member of this family, is antiferromagnetic below 155 K and exhibits sharp photoluminescence associated to a transition between a triplet ground state and a singlet excited state. The nature of the luminescent transition is a matter of current debate and so is an eventual fundamental link of this excitation to magnetism. Here we provide answers th…

{nplyr} has helper functions to work on nested dataframes: #rstats #datascience

Detecting State Manipulation Vulnerabilities in Smart Contracts Using LLM and Static Analysis
Hao Wu, Haijun Wang, Shangwang Li, Yin Wu, Ming Fan, Yitao Zhao, Ting Liu
https://arxiv.org/abs/2506.08561

Detecting State Manipulation Vulnerabilities in Smart Contracts Using LLM and Static Analysis
An increasing number of DeFi protocols are gaining popularity, facilitating transactions among multiple anonymous users. State Manipulation is one of the notorious attacks in DeFi smart contracts, with price variable being the most commonly exploited state variable-attackers manipulate token prices to gain illicit profits. In this paper, we propose PriceSleuth, a novel method that leverages the Large Language Model (LLM) and static analysis to detect Price Manipulation (PM) attacks proactively.…

Emergence of an Epsilon-Near-Zero Medium from Microscopic Atomic Principles
L. Ruks, J. Ruostekoski
https://arxiv.org/abs/2506.13294 https://

Emergence of an Epsilon-Near-Zero Medium from Microscopic Atomic Principles
We demonstrate that an effective near-zero refractive index can emerge from collective light scattering in a discrete atomic lattice, using essentially exact microscopic simulations. In a 25-layer array, cooperative response leads to over a thirtyfold increase in the effective optical wavelength within the medium, almost eliminating optical phase accumulation, with potential applications in spectroscopy and optical manipulation of quantum emitters. Crucially, the near-zero refractive index aris…

Beim Berliner Übernachtungsanbieter #Numa entdeckte ein Mitglied des Chaos Computer Club ein gravierendes #Datenleck.
Durch einfache URL-Manipulation waren persönliche Daten, #Ausweiskopien u…

CCC: Gesammelte Ausweisdaten von Übernachtungsdienstleister Numa gefunden
Ein Mitglied des Chaos Computer Clubs wollte eigentlich nur übernachten – und fand eine vollständige Kundendatensammlung.

I'm not shocked that Musk would try to manipulate Grok to vent his opinions. We've seen his manipulation before in the twitter recommender system.
I am kind of fascinated by how difficult it is. I think that broadly trained LLMs tend to converge to the same "worldview", which is mostly left-libertarian.
You can't really force them away from this on one issue without introducing inconsistencies, and breaking the guardrails.

ExoStart: Efficient learning for dexterous manipulation with sensorized exoskeleton demonstrations
Zilin Si, Jose Enrique Chen, M. Emre Karagozler, Antonia Bronars, Jonathan Hutchinson, Thomas Lampe, Nimrod Gileadi, Taylor Howell, Stefano Saliceti, Lukasz Barczyk, Ilan Olivarez Correa, Tom Erez, Mohit Shridhar, Murilo Fernandes Martins, Konstantinos Bousmalis, Nicolas Heess, Francesco Nori, Maria Bauza Villalonga

ExoStart: Efficient learning for dexterous manipulation with sensorized exoskeleton demonstrations
Recent advancements in teleoperation systems have enabled high-quality data collection for robotic manipulators, showing impressive results in learning manipulation at scale. This progress suggests that extending these capabilities to robotic hands could unlock an even broader range of manipulation skills, especially if we could achieve the same level of dexterity that human hands exhibit. However, teleoperating robotic hands is far from a solved problem, as it presents a significant challenge …

Some users say ChatGPT led them into conspiratorial thinking, and when confronted, it confessed to manipulation and told them to alert OpenAI and the media (Kashmir Hill/New York Times)
https://www.…

They Asked ChatGPT Questions. The Answers Sent Them Spiraling.
Generative A.I. chatbots are going down conspiratorial rabbit holes and endorsing wild, mystical belief systems. For some people, conversations with the technology can deeply distort reality.

Gondola: Grounded Vision Language Planning for Generalizable Robotic Manipulation
Shizhe Chen, Ricardo Garcia, Paul Pacaud, Cordelia Schmid
https://arxiv.org/abs/2506.11261

Gondola: Grounded Vision Language Planning for Generalizable Robotic Manipulation
Robotic manipulation faces a significant challenge in generalizing across unseen objects, environments and tasks specified by diverse language instructions. To improve generalization capabilities, recent research has incorporated large language models (LLMs) for planning and action execution. While promising, these methods often fall short in generating grounded plans in visual environments. Although efforts have been made to perform visual instructional tuning on LLMs for robotic manipulation,…

None of that is to downplay the danger of electronic voting machines. Turn that junk into scrap. Paper ballots all the way.
There’s no contradiction in saying that the risks of manipulation / mishap are real •and• that the actual results don’t show that it already happened.
3/

GAF: Gaussian Action Field as a Dvnamic World Model for Robotic Mlanipulation
Ying Chai, Litao Deng, Ruizhi Shao, Jiajun Zhang, Liangjun Xing, Hongwen Zhang, Yebin Liu
https://arxiv.org/abs/2506.14135

GAF: Gaussian Action Field as a Dvnamic World Model for Robotic Mlanipulation
Accurate action inference is critical for vision-based robotic manipulation. Existing approaches typically follow either a Vision-to-Action (V-A) paradigm, predicting actions directly from visual inputs, or a Vision-to-3D-to-Action (V-3D-A) paradigm, leveraging intermediate 3D representations. However, these methods often struggle with action inaccuracies due to the complexity and dynamic nature of manipulation scenes. In this paper, we propose a V-4D-A framework that enables direct action reas…

Detection and manipulation of surface electric field noise of hexagonal boron nitride
Hao-Jie Zhou, Xiao-Wen Shen, Yu Zhou, Lei Dong, Pei-Qin Chen, Xia Chen, Guang-Wei Deng, Gang Xiang, Pei-Jie Guo, Tian-Ke Wang, Hong-Peng Wu, Jun-Feng Wang
https://arxiv.org/abs/2506.07734

Detection and manipulation of surface electric field noise of hexagonal boron nitride
Hexagonal boron nitride (hBN) spin defects off er transformative potential for quantum sensing through atomic-scale proximity to target samples, yet their performance is fundamentally limited by rapid coherence loss. While magnetic noise mechanisms have been extensively studied, another critical infl uence from surface electric fi eld noise remains unexplored in hBN systems. Here,we address this challenge and systematically investigate surface electric fi eld noise in hBN using shallow boron va…

Fake-Bewertungen, Betrug und Manipulation im App Store: Apple nennt Zahlen
Apples stark frequentierter App Store lockt auch Betrüger in großem Stil. Der Konzern nennt neue Zahlen zu seinen Anti-Scam-Maßnahmen.

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

Assessing the Resilience of Automotive Intrusion Detection Systems to Adversarial Manipulation
Stefano Longari, Paolo Cerracchio, Michele Carminati, Stefano Zanero
https://arxiv.org/abs/2506.10620

Assessing the Resilience of Automotive Intrusion Detection Systems to Adversarial Manipulation
The security of modern vehicles has become increasingly important, with the controller area network (CAN) bus serving as a critical communication backbone for various Electronic Control Units (ECUs). The absence of robust security measures in CAN, coupled with the increasing connectivity of vehicles, makes them susceptible to cyberattacks. While intrusion detection systems (IDSs) have been developed to counter such threats, they are not foolproof. Adversarial attacks, particularly evasion attac…

Many lessons from history we need to keep in mind in our current political moment…
From The Atlantic: “Hitler Used a Bogus Crisis of ‘Public Order’ to Make Himself Dictator” (paywall free link)
#ResistAndHeal

Dataset of News Articles with Provenance Metadata for Media Relevance Assessment
Tomas Peterka, Matyas Bohacek
https://arxiv.org/abs/2506.09847 https://

Dataset of News Articles with Provenance Metadata for Media Relevance Assessment
Out-of-context and misattributed imagery is the leading form of media manipulation in today's misinformation and disinformation landscape. The existing methods attempting to detect this practice often only consider whether the semantics of the imagery corresponds to the text narrative, missing manipulation so long as the depicted objects or scenes somewhat correspond to the narrative at hand. To tackle this, we introduce News Media Provenance Dataset, a dataset of news articles with provenance-…

02:31—Good Night #Fediverse! 😴💤
I just made myself a new banner for myself, using (mostly) open source software. The only exception was that I used a random website to add an outline to my Rudolf Rocker image, I was too lazy to get out of bed and use GIMP on my PC for that step. For everything else, I used this tool from GitHub: 

Two-Sided Manipulation Games in Stable Matching Markets
Hadi Hosseini, Grzegorz Lisowski, Shraddha Pathak
https://arxiv.org/abs/2506.00554 https://

Two-Sided Manipulation Games in Stable Matching Markets
The Deferred Acceptance (DA) algorithm is an elegant procedure for finding a stable matching in two-sided matching markets. It ensures that no pair of agents prefers each other to their matched partners. In this work, we initiate the study of two-sided manipulations in matching markets as non-cooperative games. We introduce the accomplice manipulation game, where a man misreports to help a specific woman obtain a better partner, whenever possible. We provide a polynomial time algorithm for find…

Single-beam driven rotational manipulation for high-resolution 3D cellular morphology reconstruction
Yiwei Pan, Yijing Wu, Ziqiang Wang, Yinmei Li, Lei Gong
https://arxiv.org/abs/2506.07145

Single-beam driven rotational manipulation for high-resolution 3D cellular morphology reconstruction
The acquisition of multi-view information of cells is essential for accurate 3D reconstruction of their structures. Rotational manipulation of cells has emerged as an effective technique for obtaining such data. However, most reported methods require a trade-off between manipulation flexibility and system complexity These limitations significantly hinder their practical applicability. Recently, a novel approach has been proposed that enables simultaneous trapping and arbitrary-angle rotation of…

Design of a visual environment for programming by direct data manipulation
Michel Adam (UBS, IRISA), Patrice Frison (UBS, IRISA), Moncef Daoud (UBS), Sabine Letellier Zarshenas (UBS)
https://arxiv.org/abs/2506.03720

Design of a visual environment for programming by direct data manipulation
The use of applications on computers, smartphones, and tablets has been considerably simplified thanks to interactive and dynamic graphical interfaces coupled with the mouse and touch screens. It is no longer necessary to be a computer specialist to use them. Paradoxically, the development of computer programs generally requires writing lines of code in a programming language whose syntax is particularly strict. This process poses many difficulties for programmers. We propose an original tool i…

UniWorld: High-Resolution Semantic Encoders for Unified Visual Understanding and Generation
Bin Lin, Zongjian Li, Xinhua Cheng, Yuwei Niu, Yang Ye, Xianyi He, Shenghai Yuan, Wangbo Yu, Shaodong Wang, Yunyang Ge, Yatian Pang, Li Yuan
https://arxiv.org/abs/2506.03147

UniWorld: High-Resolution Semantic Encoders for Unified Visual Understanding and Generation
Although existing unified models deliver strong performance on vision-language understanding and text-to-image generation, their models are limited in exploring image perception and manipulation tasks, which are urgently desired by users for wide applications. Recently, OpenAI released their powerful GPT-4o-Image model for comprehensive image perception and manipulation, achieving expressive capability and attracting community interests. By observing the performance of GPT-4o-Image in our caref…

CoDA: Coordinated Diffusion Noise Optimization for Whole-Body Manipulation of Articulated Objects
Huaijin Pi, Zhi Cen, Zhiyang Dou, Taku Komura
https://arxiv.org/abs/2505.21437

CoDA: Coordinated Diffusion Noise Optimization for Whole-Body Manipulation of Articulated Objects
Synthesizing whole-body manipulation of articulated objects, including body motion, hand motion, and object motion, is a critical yet challenging task with broad applications in virtual humans and robotics. The core challenges are twofold. First, achieving realistic whole-body motion requires tight coordination between the hands and the rest of the body, as their movements are interdependent during manipulation. Second, articulated object manipulation typically involves high degrees of freedom …

This https://arxiv.org/abs/2407.04292 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAR_…

DaDu-Corki: Algorithm-Architecture Co-Design for Embodied AI-powered Robotic Manipulation
Embodied AI robots have the potential to fundamentally improve the way human beings live and manufacture. Continued progress in the burgeoning field of using large language models to control robots depends critically on an efficient computing substrate, and this trend is strongly evident in manipulation tasks. In particular, today's computing systems for embodied AI robots for manipulation tasks are designed purely based on the interest of algorithm developers, where robot actions are divided i…

Construction of Kondo Chains by Engineering Porphyrin {\pi}-Radicals on Au(111)
Yan Zhao, Kaiyue Jiang, Peng-Yi Liu, Ruoning Li, Jie Li, Xin Li, Xinchen Fang, Anjing Zhao, Yutong Zhu, Hongxiang Xu, Ting Chen, Dong Wang, Xiaodong Zhuang, Shimin Hou, Kai Wu, Song Gao, Qing-Feng Sun, Yajie Zhang, Yongfeng Wang
https://arxiv.org/abs…

Construction of Kondo Chains by Engineering Porphyrin π-Radicals on Au(111)
Quantum manipulation of molecular radical spins provides a crucial platform for exploring emergent phenomena in many-body systems. Here, we combine surface-confined synthesis with scanning tunneling microscopy (STM) tip-induced dehydrogenation to achieve atom-precise engineering of quasi-one-dimensional porphyrin-based Kondo chains (1-7 units) on Au(111). Key design innovations leverage large-sized porphyrins to suppress intrachain antiferromagnetic coupling, while ${Zn}^{2+}$ chelation at porp…

Adaptive event-triggered robust tracking control of soft robots
Renjie Ma, Ziyao Qu, Zhijian Hu, Dong Zhao, Marios M. Polycarpou
https://arxiv.org/abs/2506.09523

Adaptive event-triggered robust tracking control of soft robots
Soft robots manufactured with flexible materials can be highly compliant and adaptive to their surroundings, which facilitates their application in areas such as dexterous manipulation and environmental exploration. This paper aims at investigating the tracking control problem for soft robots under uncertainty such as unmodeled dynamics and external disturbance. First, we establish a novel switching function and design the compensated tracking error dynamics by virtue of the command filter. The…

Controllable Expressive 3D Facial Animation via Diffusion in a Unified Multimodal Space
Kangwei Liu, Junwu Liu, Xiaowei Yi, Jinlin Guo, Yun Cao
https://arxiv.org/abs/2506.10007

Controllable Expressive 3D Facial Animation via Diffusion in a Unified Multimodal Space
Audio-driven emotional 3D facial animation encounters two significant challenges: (1) reliance on single-modal control signals (videos, text, or emotion labels) without leveraging their complementary strengths for comprehensive emotion manipulation, and (2) deterministic regression-based mapping that constrains the stochastic nature of emotional expressions and non-verbal behaviors, limiting the expressiveness of synthesized animations. To address these challenges, we present a diffusion-based …

Fractional Fourier Sound Synthesis
Esteban Guti\'errez, Rodrigo C\'adiz, Carlos Sing Long, Frederic Font, Xavier Serra
https://arxiv.org/abs/2506.09189

Fractional Fourier Sound Synthesis
This paper explores the innovative application of the Fractional Fourier Transform (FrFT) in sound synthesis, highlighting its potential to redefine time-frequency analysis in audio processing. As an extension of the classical Fourier Transform, the FrFT introduces fractional order parameters, enabling a continuous interpolation between time and frequency domains and unlocking unprecedented flexibility in signal manipulation. Crucially, the FrFT also opens the possibility of directly synthesizi…

Hardware Limitations and Optimization Approach in 1-Bit RIS Design at 28 GHz
Hossein Rezaei, Mehmet Emin Arslan, George Yammine, Niels Neumann, Norman Franchi
https://arxiv.org/abs/2506.08930

Hardware Limitations and Optimization Approach in 1-Bit RIS Design at 28 GHz
Reconfigurable intelligent surfaces (RIS) have emerged as a transformative technology for electromagnetic (EM) wave manipulation, offering unprecedented control over wave reflections compared to traditional metallic reflectors. By utilizing an array of tunable elements, RIS can steer and shape electromagnetic waves to enhance signal quality in wireless communication and radar systems. However, practical implementations face significant challenges due to hardware limitations and phase quantizati…

#PennedPossibilities 690 — SC POV: What do you fear losing the most?
This question is for the MC's brother, I believe.
SC: My brother.
It terrifies me to think that my brother could become completely corrupted and lose his true Ethereal essence to Ianthe's manipulation. You see, The Unmaking is not just simple indoctrination, it is the obliteration of free will,…

Time-Unified Diffusion Policy with Action Discrimination for Robotic Manipulation
Ye Niu, Sanping Zhou, Yizhe Li, Ye Den, Le Wang
https://arxiv.org/abs/2506.09422

Time-Unified Diffusion Policy with Action Discrimination for Robotic Manipulation
In many complex scenarios, robotic manipulation relies on generative models to estimate the distribution of multiple successful actions. As the diffusion model has better training robustness than other generative models, it performs well in imitation learning through successful robot demonstrations. However, the diffusion-based policy methods typically require significant time to iteratively denoise robot actions, which hinders real-time responses in robotic manipulation. Moreover, existing dif…

Generation of frequency entanglement by rotating Doppler effect
Bolong Yi, Ling Chen, Baocheng Zhang
https://arxiv.org/abs/2506.09488 https://

Generation of frequency entanglement by rotating Doppler effect
We propose a method to generate the frequency entanglement, allowing a continuous generation of entangled two-photon states in a hybrid degree of freedom by post-manipulation. Our method is based on type-II spontaneous parametric down-conversion in a nonlinear crystal and the rotation Doppler effect by rotating the q-plates, without preset discrete frequency entanglement. This allows the arbitrary modification of frequency entangled photons in a wide frequency range at room temperature, offerin…

🍮 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

GENMANIP: LLM-driven Simulation for Generalizable Instruction-Following Manipulation
Ning Gao, Yilun Chen, Shuai Yang, Xinyi Chen, Yang Tian, Hao Li, Haifeng Huang, Hanqing Wang, Tai Wang, Jiangmiao Pang
https://arxiv.org/abs/2506.10966

GENMANIP: LLM-driven Simulation for Generalizable Instruction-Following Manipulation
Robotic manipulation in real-world settings remains challenging, especially regarding robust generalization. Existing simulation platforms lack sufficient support for exploring how policies adapt to varied instructions and scenarios. Thus, they lag behind the growing interest in instruction-following foundation models like LLMs, whose adaptability is crucial yet remains underexplored in fair comparisons. To bridge this gap, we introduce GenManip, a realistic tabletop simulation platform tailore…

This https://arxiv.org/abs/2505.21938 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

Practical Adversarial Attacks on Stochastic Bandits via Fake Data Injection
Adversarial attacks on stochastic bandits have traditionally relied on some unrealistic assumptions, such as per-round reward manipulation and unbounded perturbations, limiting their relevance to real-world systems. We propose a more practical threat model, Fake Data Injection, which reflects realistic adversarial constraints: the attacker can inject only a limited number of bounded fake feedback samples into the learner's history, simulating legitimate interactions. We design efficient attack …

An NBC News and Get Real Security [analysis](https://www.nbcnews.com/tech/tech-news
/internet-thinks-video-gaza-ai-s-proved-isnt-rcna209617) found no evidence of AI generation or manipulation in the video of people waiting for food in Rafah.

Technology and Media News
Get the latest news on technology businesses and Internet media at NBCNews.com. Learn about the digital trends and platforms that are disrupting media and tech companies.

This https://arxiv.org/abs/2503.19990 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAI_…

LEGO-Puzzles: How Good Are MLLMs at Multi-Step Spatial Reasoning?
Multi-step spatial reasoning entails understanding and reasoning about spatial relationships across multiple sequential steps, which is crucial for tackling complex real-world applications, such as robotic manipulation, autonomous navigation, and automated assembly. To assess how well current Multimodal Large Language Models (MLLMs) have acquired this fundamental capability, we introduce LEGO-Puzzles, a scalable benchmark designed to evaluate both spatial understanding and sequential reasoning …

Complexity and Manipulation of International Kidney Exchange Programmes with Country-Specific Parameterss
Rachael Colley, David Manlove, Daniel Paulusma, Mengxiao Zhang
https://arxiv.org/abs/2506.04092

Complexity and Manipulation of International Kidney Exchange Programmes with Country-Specific Parameterss
Kidney Exchange Programmes (KEPs) facilitate the exchange of kidneys, and larger pools of recipient-donor pairs tend to yield proportionally more transplants, leading to the proposal of international KEPs (IKEPs). However, as studied by \citet{mincu2021ip}, practical limitations must be considered in IKEPs to ensure that countries remain willing to participate. Thus, we study IKEPs with country-specific parameters, represented by a tuple $Γ$, restricting the selected transplants to be feasible…

Repeton: Structured Bug Repair with ReAct-Guided Patch-and-Test Cycles
Nguyen Phu Vinh, Anh Chung Hoang, Chris Ngo, Truong-Son Hy
https://arxiv.org/abs/2506.08173

Repeton: Structured Bug Repair with ReAct-Guided Patch-and-Test Cycles
Large Language Models (LLMs) have shown strong capabilities in code generation and comprehension, yet their application to complex software engineering tasks often suffers from low precision and limited interpretability. We present Repeton, a fully open-source framework that leverages LLMs for precise and automated code manipulation in real-world Git repositories. Rather than generating holistic fixes, Repeton operates through a structured patch-and-test pipeline: it iteratively diagnoses issue…

HyperCard was magnificent. Still is.
The HyperTalk language was cool — but even cooler IMO was the way the dev environment mixed code with direct manipulation of the UI. There are lots of problems with that approach for generalized Ui development, yes, but the experience of it was magical.
Unity and the like have a similar editor structure — edit UI objects, attach code to them — but the feeling is totally different somehow.
https://mastodon.social/@ricmac/114643259120579546

Disclosure Audits for LLM Agents
Saswat Das, Jameson Sandler, Ferdinando Fioretto
https://arxiv.org/abs/2506.10171 https://arxiv.org/…

Disclosure Audits for LLM Agents
Large Language Model agents have begun to appear as personal assistants, customer service bots, and clinical aides. While these applications deliver substantial operational benefits, they also require continuous access to sensitive data, which increases the likelihood of unauthorized disclosures. This study proposes an auditing framework for conversational privacy that quantifies and audits these risks. The proposed Conversational Manipulation for Privacy Leakage (CMPL) framework, is an iterati…

Analyzing Key Objectives in Human-to-Robot Retargeting for Dexterous Manipulation
Chendong Xin, Mingrui Yu, Yongpeng Jiang, Zhefeng Zhang, Xiang Li
https://arxiv.org/abs/2506.09384

Analyzing Key Objectives in Human-to-Robot Retargeting for Dexterous Manipulation
Kinematic retargeting from human hands to robot hands is essential for transferring dexterity from humans to robots in manipulation teleoperation and imitation learning. However, due to mechanical differences between human and robot hands, completely reproducing human motions on robot hands is impossible. Existing works on retargeting incorporate various optimization objectives, focusing on different aspects of hand configuration. However, the lack of experimental comparative studies leaves the…

Conversational Interfaces for Parametric Conceptual Architectural Design: Integrating Mixed Reality with LLM-driven Interaction
Ruochen Ji, Lyu Tiangang
https://arxiv.org/abs/2506.06066

Conversational Interfaces for Parametric Conceptual Architectural Design: Integrating Mixed Reality with LLM-driven Interaction
Mixed reality (MR) environments offer embodied spatial interaction, providing intuitive 3D manipulation capabilities that enhance the conceptual design process. Parametric modeling, a powerful and advanced architectural design method, enables the generation of complex, optimized geometries. However, its integration into MR environments remains limited due to precision constraints and unsuitable input modalities. Existing MR tools prioritize spatial interaction but lack the control and expressiv…

SAIL: Faster-than-Demonstration Execution of Imitation Learning Policies
Nadun Ranawaka Arachchige, Zhenyang Chen, Wonsuhk Jung, Woo Chul Shin, Rohan Bansal, Pierre Barroso, Yu Hang He, Yingyang Celine Lin, Benjamin Joffe, Shreyas Kousik, Danfei Xu
https://arxiv.org/abs/2506.11948

SAIL: Faster-than-Demonstration Execution of Imitation Learning Policies
Offline Imitation Learning (IL) methods such as Behavior Cloning are effective at acquiring complex robotic manipulation skills. However, existing IL-trained policies are confined to executing the task at the same speed as shown in demonstration data. This limits the task throughput of a robotic system, a critical requirement for applications such as industrial automation. In this paper, we introduce and formalize the novel problem of enabling faster-than-demonstration execution of visuomotor p…

This https://arxiv.org/abs/2309.05677 has been replaced.
initial toot: https://mastoxiv.page/@ar…

Optical trapping based on microring resonators with transverse slot structure
Over the past few decades, optical manipulation has emerged as a highly successful tool in various fields, such as biology, micro/nanorobotics, and physics. Among the different techniques, the transverse slot optical waveguide has shown remarkable potential in enhancing the field and significantly improving optical trapping capabilities. Additionally, microring resonators have demonstrated the ability to enhance the field at specific resonance wavelengths, enabling the manipulation and capture …

This https://arxiv.org/abs/2506.00540 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Manipulation of Photonic Spin Hall Effect via Interacting Rydberg Atom
We present a theoretical study demonstrating enhanced tunability of the photonic spin Hall effect (PSHE) using a strongly interacting Rydberg atomic medium under electromagnetically induced transparency (EIT) conditions. In contrast to conventional approaches that rely on static refractiveindex profiles or metamaterials, here the PSHE is controlled via a nonlocal third-order nonlinear susceptibility arising from long range Rydberg-Rydberg interactions. We show that this nonlocal nonlinearity en…

This https://arxiv.org/abs/2505.21652 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

PartInstruct: Part-level Instruction Following for Fine-grained Robot Manipulation
Fine-grained robot manipulation, such as lifting and rotating a bottle to display the label on the cap, requires robust reasoning about object parts and their relationships with intended tasks. Despite recent advances in training general-purpose robot manipulation policies guided by language instructions, there is a notable lack of large-scale datasets for fine-grained manipulation tasks with part-level instructions and diverse 3D object instances annotated with part-level labels. In this work,…

Orbital Hall Effect Enables Field-Free Magnetization Reversal in Ferrimagnets without Additional Conversion Layer
Zelalem Abebe Bekele, Kun Lei, Xiukai Lan, Xiangyu Liu, Hui Wen, Weihao Li, Yongcheng Deng, Wenkai Zhu, Kaiming Cai, Kaiyou Wang
https://arxiv.org/abs/2506.07608

Orbital Hall Effect Enables Field-Free Magnetization Reversal in Ferrimagnets without Additional Conversion Layer
The spin Hall effect (SHE) enables efficient electrical manipulation of magnetization through the spin Hall current \left(\mathbit{J}_{\mathbit{SHE}}\right), advancing energy-efficient spintronics. In parallel, the orbital Hall effect (OHE) offers an alternative pathway to SHE for converting charge current into an angular momentum flow. In this study, we demonstrate field-free current-induced perpendicular ferrimagnetic deterministic switching within a Mo/CoGd device without an additional orbit…

Strain-induced manipulation of non-collinear antiferromagnets
Mithuss Tharmalingam, Feodor Svetlanov Konomaev, Kjetil M. D. Hals
https://arxiv.org/abs/2505.24520

Strain-induced manipulation of non-collinear antiferromagnets
In recent years, there has been growing interest in harnessing non-collinear antiferromagnets (NCAFMs) for applications in antiferromagnetic spintronics. A key requirement for their practical use is the ability to control the spin order in a reliable and tunable manner. In this work, we investigate how the spin order in kagome antiferromagnets -- an important class of NCAFMs -- can be manipulated via strain. Starting from a microscopic spin Hamiltonian, we derive an effective action for the kag…

This https://arxiv.org/abs/2505.16512 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCV_…

Beyond Face Swapping: A Diffusion-Based Digital Human Benchmark for Multimodal Deepfake Detection
In recent years, the rapid development of deepfake technology has given rise to an emerging and serious threat to public security: diffusion model-based digital human generation. Unlike traditional face manipulation methods, such models can generate highly realistic videos with consistency through multimodal control signals. Their flexibility and covertness pose severe challenges to existing detection strategies. To bridge this gap, we introduce DigiFakeAV, the first large-scale multimodal digi…

3DFlowAction: Learning Cross-Embodiment Manipulation from 3D Flow World Model
Hongyan Zhi, Peihao Chen, Siyuan Zhou, Yubo Dong, Quanxi Wu, Lei Han, Mingkui Tan
https://arxiv.org/abs/2506.06199

3DFlowAction: Learning Cross-Embodiment Manipulation from 3D Flow World Model
Manipulation has long been a challenging task for robots, while humans can effortlessly perform complex interactions with objects, such as hanging a cup on the mug rack. A key reason is the lack of a large and uniform dataset for teaching robots manipulation skills. Current robot datasets often record robot action in different action spaces within a simple scene. This hinders the robot to learn a unified and robust action representation for different robots within diverse scenes. Observing how …

TensorTouch: Calibration of Tactile Sensors for High Resolution Stress Tensor and Deformation for Dexterous Manipulation
Won Kyung Do, Matthew Strong, Aiden Swann, Boshu Lei, Monroe Kennedy III
https://arxiv.org/abs/2506.08291

TensorTouch: Calibration of Tactile Sensors for High Resolution Stress Tensor and Deformation for Dexterous Manipulation
Advanced dexterous manipulation involving multiple simultaneous contacts across different surfaces, like pinching coins from ground or manipulating intertwined objects, remains challenging for robotic systems. Such tasks exceed the capabilities of vision and proprioception alone, requiring high-resolution tactile sensing with calibrated physical metrics. Raw optical tactile sensor images, while information-rich, lack interpretability and cross-sensor transferability, limiting their real-world u…

Fast Estimation of Globally Optimal Independent Contact Regions for Robust Grasping and Manipulation
Jonathan P. King, Harnoor Ahluwalia, Michael Zhang, Nancy S. Pollard
https://arxiv.org/abs/2506.08856

Fast Estimation of Globally Optimal Independent Contact Regions for Robust Grasping and Manipulation
This work presents a fast anytime algorithm for computing globally optimal independent contact regions (ICRs). ICRs are regions such that one contact within each region enables a valid grasp. Locations of ICRs can provide guidance for grasp and manipulation planning, learning, and policy transfer. However, ICRs for modern applications have been little explored, in part due to the expense of computing them, as they have a search space exponential in the number of contacts. We present a divide an…

HiBerNAC: Hierarchical Brain-emulated Robotic Neural Agent Collective for Disentangling Complex Manipulation
Hongjun Wu, Heng Zhang, Pengsong Zhang, Jin Wang, Cong Wang
https://arxiv.org/abs/2506.08296

HiBerNAC: Hierarchical Brain-emulated Robotic Neural Agent Collective for Disentangling Complex Manipulation
Recent advances in multimodal vision-language-action (VLA) models have revolutionized traditional robot learning, enabling systems to interpret vision, language, and action in unified frameworks for complex task planning. However, mastering complex manipulation tasks remains an open challenge, constrained by limitations in persistent contextual memory, multi-agent coordination under uncertainty, and dynamic long-horizon planning across variable sequences. To address this challenge, we propose \…

This https://arxiv.org/abs/2402.05430 has been replaced.
link: https://scholar.google.com/scholar?q=a

Flipping of electronic spins in BiFeO$_3$ via chiral $d-d$ excitations
BiFeO$_3$ is a multiferroic material featuring ferroelectricity and noncollinear antiferromagnetism. Definitive and efficient control of the characteristic spin texture of BiFeO$_3$ is attractive for emerging quantum devices. In this regard, crystal-field $d\rightarrow d$ excitations localized on Fe atomic sites in BiFeO$_3$ provide an avenue for manipulation of the spin texture as they induce a complex interplay among the spin, charge, and lattice degrees of freedom. In this work, the \textit{…

RationalVLA: A Rational Vision-Language-Action Model with Dual System
Wenxuan Song, Jiayi Chen, Wenxue Li, Xu He, Han Zhao, Pengxiang Ding Shiyan Su, Feilong Tang, Xuelian Cheng, Donglin Wang, Zongyuan Ge, Xinhu Zheng, Zhe Liu, Hesheng Wang, Yunhui Liu, Haoang Li
https://arxiv.org/abs/2506.10826

RationalVLA: A Rational Vision-Language-Action Model with Dual System
A fundamental requirement for real-world robotic deployment is the ability to understand and respond to natural language instructions. Existing language-conditioned manipulation tasks typically assume that instructions are perfectly aligned with the environment. This assumption limits robustness and generalization in realistic scenarios where instructions may be ambiguous, irrelevant, or infeasible. To address this problem, we introduce RAtional MAnipulation (RAMA), a new benchmark that challen…

Chain-of-Action: Trajectory Autoregressive Modeling for Robotic Manipulation
Wenbo Zhang, Tianrun Hu, Yanyuan Qiao, Hanbo Zhang, Yuchu Qin, Yang Li, Jiajun Liu, Tao Kong, Lingqiao Liu, Xiao Ma
https://arxiv.org/abs/2506.09990

Chain-of-Action: Trajectory Autoregressive Modeling for Robotic Manipulation
We present Chain-of-Action (CoA), a novel visuo-motor policy paradigm built upon Trajectory Autoregressive Modeling. Unlike conventional approaches that predict next step action(s) forward, CoA generates an entire trajectory by explicit backward reasoning with task-specific goals through an action-level Chain-of-Thought (CoT) process. This process is unified within a single autoregressive structure: (1) the first token corresponds to a stable keyframe action that encodes the task-specific goals…

Optoelectronically Active GaAs/GeSn-MQW/Ge Heterojunctions Created via Semiconductor Grafting
Jie Zhou, Haibo Wang, Yifu Guo, Alireza Abrand, Yiran Li, Yang Liu, Jiarui Gong, Po Rei Huang, Jianping Shen, Shengqiang Xu, Daniel Vincent, Samuel Haessly, Yi Lu, Munho Kim, Shui-Qing Yu, Parsian K. Mohseni, Guo-En Chang, Zetian Mi, Kai Sun, Xiao Gong, Mikhail A Kats, Zhenqiang Ma

Optoelectronically Active GaAs/GeSn-MQW/Ge Heterojunctions Created via Semiconductor Grafting
Traditionally, advancements in semiconductor devices have been driven by lattice-matched heterojunctions with tailored band alignments through heteroepitaxy techniques. However, there is significant interest in expanding the capabilities of heterojunction devices, in particular utilizing extreme lattice mismatches. We demonstrate the manipulation of device behaviors and performance enhancement achievable through a lattice-mismatched, single-crystalline GaAs/GeSn-multi-quantum well (MQW)/Ge n-i-…

Broadband Low-loss Unidirectional Reflection On-chip with Asymmetric Dielectric Metasurface
Heijun Jeong, Zeki Hayran, Yuan Liu, Yahui Xiao, Hwaseob Lee, Zi Wang, Jonathan Klamkin, Francesco Monticone, Tingyi Gu
https://arxiv.org/abs/2506.06872

Broadband Low-loss Unidirectional Reflection On-chip with Asymmetric Dielectric Metasurface
Metasurface has emerged as a powerful platform for controlling light at subwavelength thickness, enabling new functionalities for imaging, polarization manipulation, and angular momentum conversion within a flat surface. We explored an integrated asymmetric metasurface simultaneously achieving broadband, low loss forward power transmission, and significant back reflection sup-pression in multi-mode waveguides. The tapering along the direction of light propagation leads to low loss and space-eff…

Haptic Rapidly-Exploring Random Trees: A Sampling-based Planner for Quasi-static Manipulation Tasks
Lin Yang, Huu-Thiet Nguyen, Donghan Yu, Chen Lv, Domenico Campolo
https://arxiv.org/abs/2506.00351

Haptic Rapidly-Exploring Random Trees: A Sampling-based Planner for Quasi-static Manipulation Tasks
In this work, we explore how conventional motion planning algorithms can be reapplied to contact-rich manipulation tasks. Rather than focusing solely on efficiency, we investigate how manipulation aspects can be recast in terms of conventional motion-planning algorithms. Conventional motion planners, such as Rapidly-Exploring Random Trees (RRT), typically compute collision-free paths in configuration space. However, in manipulation tasks, intentional contact is often necessary. For example, whe…

OWMM-Agent: Open World Mobile Manipulation With Multi-modal Agentic Data Synthesis
Junting Chen, Haotian Liang, Lingxiao Du, Weiyun Wang, Mengkang Hu, Yao Mu, Wenhai Wang, Jifeng Dai, Ping Luo, Wenqi Shao, Lin Shao
https://arxiv.org/abs/2506.04217

OWMM-Agent: Open World Mobile Manipulation With Multi-modal Agentic Data Synthesis
The rapid progress of navigation, manipulation, and vision models has made mobile manipulators capable in many specialized tasks. However, the open-world mobile manipulation (OWMM) task remains a challenge due to the need for generalization to open-ended instructions and environments, as well as the systematic complexity to integrate high-level decision making with low-level robot control based on both global scene understanding and current agent state. To address this complexity, we propose a …

Scoop-and-Toss: Dynamic Object Collection for Quadrupedal Systems
Minji Kang, Chanwoo Baek, Yoonsang Lee
https://arxiv.org/abs/2506.09406 https://

Scoop-and-Toss: Dynamic Object Collection for Quadrupedal Systems
Quadruped robots have made significant advances in locomotion, extending their capabilities from controlled environments to real-world applications. Beyond movement, recent work has explored loco-manipulation using the legs to perform tasks such as pressing buttons or opening doors. While these efforts demonstrate the feasibility of leg-based manipulation, most have focused on relatively static tasks. In this work, we propose a framework that enables quadruped robots to collect objects without …

This https://arxiv.org/abs/2505.16196 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

SEM: Enhancing Spatial Understanding for Robust Robot Manipulation
A key challenge in robot manipulation lies in developing policy models with strong spatial understanding, the ability to reason about 3D geometry, object relations, and robot embodiment. Existing methods often fall short: 3D point cloud models lack semantic abstraction, while 2D image encoders struggle with spatial reasoning. To address this, we propose SEM (Spatial Enhanced Manipulation model), a novel diffusion-based policy framework that explicitly enhances spatial understanding from two com…

Efficient Manipulation-Enhanced Semantic Mapping With Uncertainty-Informed Action Selection
Nils Dengler, Jesper M\"ucke, Rohit Menon, Maren Bennewitz
https://arxiv.org/abs/2506.02286

Efficient Manipulation-Enhanced Semantic Mapping With Uncertainty-Informed Action Selection
Service robots operating in cluttered human environments such as homes, offices, and schools cannot rely on predefined object arrangements and must continuously update their semantic and spatial estimates while dealing with possible frequent rearrangements. Efficient and accurate mapping under such conditions demands selecting informative viewpoints and targeted manipulations to reduce occlusions and uncertainty. In this work, we present a manipulation-enhanced semantic mapping framework for oc…

This https://arxiv.org/abs/2501.18564 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

SAM2Act: Integrating Visual Foundation Model with A Memory Architecture for Robotic Manipulation
Robotic manipulation systems operating in diverse, dynamic environments must exhibit three critical abilities: multitask interaction, generalization to unseen scenarios, and spatial memory. While significant progress has been made in robotic manipulation, existing approaches often fall short in generalization to complex environmental variations and addressing memory-dependent tasks. To bridge this gap, we introduce SAM2Act, a multi-view robotic transformer-based policy that leverages multi-reso…

HoMeR: Learning In-the-Wild Mobile Manipulation via Hybrid Imitation and Whole-Body Control
Priya Sundaresan, Rhea Malhotra, Phillip Miao, Jingyun Yang, Jimmy Wu, Hengyuan Hu, Rika Antonova, Francis Engelmann, Dorsa Sadigh, Jeannette Bohg
https://arxiv.org/abs/2506.01185

HoMeR: Learning In-the-Wild Mobile Manipulation via Hybrid Imitation and Whole-Body Control
We introduce HoMeR, an imitation learning framework for mobile manipulation that combines whole-body control with hybrid action modes that handle both long-range and fine-grained motion, enabling effective performance on realistic in-the-wild tasks. At its core is a fast, kinematics-based whole-body controller that maps desired end-effector poses to coordinated motion across the mobile base and arm. Within this reduced end-effector action space, HoMeR learns to switch between absolute pose pred…

FreeTacMan: Robot-free Visuo-Tactile Data Collection System for Contact-rich Manipulation
Longyan Wu, Checheng Yu, Jieji Ren, Li Chen, Ran Huang, Guoying Gu, Hongyang Li
https://arxiv.org/abs/2506.01941

FreeTacMan: Robot-free Visuo-Tactile Data Collection System for Contact-rich Manipulation
Enabling robots with contact-rich manipulation remains a pivotal challenge in robot learning, which is substantially hindered by the data collection gap, including its inefficiency and limited sensor setup. While prior work has explored handheld paradigms, their rod-based mechanical structures remain rigid and unintuitive, providing limited tactile feedback and posing challenges for human operators. Motivated by the dexterity and force feedback of human motion, we propose FreeTacMan, a human-ce…

Fast-in-Slow: A Dual-System Foundation Model Unifying Fast Manipulation within Slow Reasoning
Hao Chen, Jiaming Liu, Chenyang Gu, Zhuoyang Liu, Renrui Zhang, Xiaoqi Li, Xiao He, Yandong Guo, Chi-Wing Fu, Shanghang Zhang, Pheng-Ann Heng
https://arxiv.org/abs/2506.01953

Fast-in-Slow: A Dual-System Foundation Model Unifying Fast Manipulation within Slow Reasoning
Generalized policy and execution efficiency constitute the two critical challenges in robotic manipulation. While recent foundation policies benefit from the common-sense reasoning capabilities of internet-scale pretrained vision-language models (VLMs), they often suffer from low execution frequency. To mitigate this dilemma, dual-system approaches, inspired by Kahneman's theory, have been proposed to leverage a VLM-based System 2 model handling high-level reasoning and a separate System 1 acti…

In-Hand Object Pose Estimation via Visual-Tactile Fusion
Felix Nonnengie{\ss}er, Alap Kshirsagar, Boris Belousov, Jan Peters
https://arxiv.org/abs/2506.10787

In-Hand Object Pose Estimation via Visual-Tactile Fusion
Accurate in-hand pose estimation is crucial for robotic object manipulation, but visual occlusion remains a major challenge for vision-based approaches. This paper presents an approach to robotic in-hand object pose estimation, combining visual and tactile information to accurately determine the position and orientation of objects grasped by a robotic hand. We address the challenge of visual occlusion by fusing visual information from a wrist-mounted RGB-D camera with tactile information from v…

This https://arxiv.org/abs/2411.18289 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Don't Let Your Robot be Harmful: Responsible Robotic Manipulation via Safety-as-Policy
Unthinking execution of human instructions in robotic manipulation can lead to severe safety risks, such as poisonings, fires, and even explosions. In this paper, we present responsible robotic manipulation, which requires robots to consider potential hazards in the real-world environment while completing instructions and performing complex operations safely and efficiently. However, such scenarios in real world are variable and risky for training. To address this challenge, we propose Safety-a…

A Novel Feedforward Youla Parameterization Method for Avoiding Local Minima in Stereo Image Based Visual Servoing Control
Rongfei Li, Francis Assadian
https://arxiv.org/abs/2506.10252

A Novel Feedforward Youla Parameterization Method for Avoiding Local Minima in Stereo Image Based Visual Servoing Control
In robot navigation and manipulation, accurately determining the camera's pose relative to the environment is crucial for effective task execution. In this paper, we systematically prove that this problem corresponds to the Perspective-3-Point (P3P) formulation, where exactly three known 3D points and their corresponding 2D image projections are used to estimate the pose of a stereo camera. In image-based visual servoing (IBVS) control, the system becomes overdetermined, as the 6 degrees of fre…

DexMachina: Functional Retargeting for Bimanual Dexterous Manipulation
Zhao Mandi, Yifan Hou, Dieter Fox, Yashraj Narang, Ajay Mandlekar, Shuran Song
https://arxiv.org/abs/2505.24853

DexMachina: Functional Retargeting for Bimanual Dexterous Manipulation
We study the problem of functional retargeting: learning dexterous manipulation policies to track object states from human hand-object demonstrations. We focus on long-horizon, bimanual tasks with articulated objects, which is challenging due to large action space, spatiotemporal discontinuities, and embodiment gap between human and robot hands. We propose DexMachina, a novel curriculum-based algorithm: the key idea is to use virtual object controllers with decaying strength: an object is first…

Advances on Affordable Hardware Platforms for Human Demonstration Acquisition in Agricultural Applications
Alberto San-Miguel-Tello, Gennaro Scarati, Alejandro Hern\'andez, Mario Cavero-Vidal, Aakash Maroti, N\'estor Garc\'ia
https://arxiv.org/abs/2506.09494

Advances on Affordable Hardware Platforms for Human Demonstration Acquisition in Agricultural Applications
This paper presents advances on the Universal Manipulation Interface (UMI), a low-cost hand-held gripper for robot Learning from Demonstration (LfD), for complex in-the-wild scenarios found in agricultural settings. The focus is on improving the acquisition of suitable samples with minimal additional setup. Firstly, idle times and user's cognitive load are reduced through the extraction of individual samples from a continuous demonstration considering task events. Secondly, reliability on the g…

SAFE: Multitask Failure Detection for Vision-Language-Action Models
Qiao Gu, Yuanliang Ju, Shengxiang Sun, Igor Gilitschenski, Haruki Nishimura, Masha Itkina, Florian Shkurti
https://arxiv.org/abs/2506.09937

SAFE: Multitask Failure Detection for Vision-Language-Action Models
While vision-language-action models (VLAs) have shown promising robotic behaviors across a diverse set of manipulation tasks, they achieve limited success rates when deployed on novel tasks out-of-the-box. To allow these policies to safely interact with their environments, we need a failure detector that gives a timely alert such that the robot can stop, backtrack, or ask for help. However, existing failure detectors are trained and tested only on one or a few specific tasks, while VLAs require…

eFlesh: Highly customizable Magnetic Touch Sensing using Cut-Cell Microstructures
Venkatesh Pattabiraman, Zizhou Huang, Daniele Panozzo, Denis Zorin, Lerrel Pinto, Raunaq Bhirangi
https://arxiv.org/abs/2506.09994

eFlesh: Highly customizable Magnetic Touch Sensing using Cut-Cell Microstructures
If human experience is any guide, operating effectively in unstructured environments -- like homes and offices -- requires robots to sense the forces during physical interaction. Yet, the lack of a versatile, accessible, and easily customizable tactile sensor has led to fragmented, sensor-specific solutions in robotic manipulation -- and in many cases, to force-unaware, sensorless approaches. With eFlesh, we bridge this gap by introducing a magnetic tactile sensor that is low-cost, easy to fabr…

DCIRNet: Depth Completion with Iterative Refinement for Dexterous Grasping of Transparent and Reflective Objects
Guanghu Xie, Zhiduo Jiang, Yonglong Zhang, Yang Liu, Zongwu Xie, Baoshi Cao, Hong Liu
https://arxiv.org/abs/2506.09491

DCIRNet: Depth Completion with Iterative Refinement for Dexterous Grasping of Transparent and Reflective Objects
Transparent and reflective objects in everyday environments pose significant challenges for depth sensors due to their unique visual properties, such as specular reflections and light transmission. These characteristics often lead to incomplete or inaccurate depth estimation, which severely impacts downstream geometry-based vision tasks, including object recognition, scene reconstruction, and robotic manipulation. To address the issue of missing depth information in transparent and reflective o…

FreqPolicy: Efficient Flow-based Visuomotor Policy via Frequency Consistency
Yifei Su, Ning Liu, Dong Chen, Zhen Zhao, Kun Wu, Meng Li, Zhiyuan Xu, Zhengping Che, Jian Tang
https://arxiv.org/abs/2506.08822

FreqPolicy: Efficient Flow-based Visuomotor Policy via Frequency Consistency
Generative modeling-based visuomotor policies have been widely adopted in robotic manipulation attributed to their ability to model multimodal action distributions. However, the high inference cost of multi-step sampling limits their applicability in real-time robotic systems. To address this issue, existing approaches accelerate the sampling process in generative modeling-based visuomotor policies by adapting acceleration techniques originally developed for image generation. Despite this progr…

Geometric Visual Servo Via Optimal Transport
Ethan Canzini, Simon Pope, Ashutosh Tiwari
https://arxiv.org/abs/2506.02768 https://arxi…

Geometric Visual Servo Via Optimal Transport
When developing control laws for robotic systems, the principle factor when examining their performance is choosing inputs that allow smooth tracking to a reference input. In the context of robotic manipulation, this involves translating an object or end-effector from an initial pose to a target pose. Robotic manipulation control laws frequently use vision systems as an error generator to track features and produce control inputs. However, current control algorithms don't take into account the …

This https://arxiv.org/abs/2503.04280 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Towards Autonomous Reinforcement Learning for Real-World Robotic Manipulation with Large Language Models
Recent advancements in Large Language Models (LLMs) and Visual Language Models (VLMs) have significantly impacted robotics, enabling high-level semantic motion planning applications. Reinforcement Learning (RL), a complementary paradigm, enables agents to autonomously optimize complex behaviors through interaction and reward signals. However, designing effective reward functions for RL remains challenging, especially in real-world tasks where sparse rewards are insufficient and dense rewards re…

Bi-Manual Joint Camera Calibration and Scene Representation
Haozhan Tang, Tianyi Zhang, Matthew Johnson-Roberson, Weiming Zhi
https://arxiv.org/abs/2505.24819

Bi-Manual Joint Camera Calibration and Scene Representation
Robot manipulation, especially bimanual manipulation, often requires setting up multiple cameras on multiple robot manipulators. Before robot manipulators can generate motion or even build representations of their environments, the cameras rigidly mounted to the robot need to be calibrated. Camera calibration is a cumbersome process involving collecting a set of images, with each capturing a pre-determined marker. In this work, we introduce the Bi-Manual Joint Calibration and Representation Fra…

This https://arxiv.org/abs/2504.00420 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Think Small, Act Big: Primitive Prompt Learning for Lifelong Robot Manipulation
Building a lifelong robot that can effectively leverage prior knowledge for continuous skill acquisition remains significantly challenging. Despite the success of experience replay and parameter-efficient methods in alleviating catastrophic forgetting problem, naively applying these methods causes a failure to leverage the shared primitives between skills. To tackle these issues, we propose Primitive Prompt Learning (PPL), to achieve lifelong robot manipulation via reusable and extensible primi…

This https://arxiv.org/abs/2502.09180 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

A Machine Learning Approach to Sensor Substitution from Tactile Sensing to Visual Perception for Non-Prehensile Manipulation
Mobile manipulators are increasingly deployed in complex environments, requiring diverse sensors to perceive and interact with their surroundings. However, equipping every robot with every possible sensor is often impractical due to cost and physical constraints. A critical challenge arises when robots with differing sensor capabilities need to collaborate or perform similar tasks. For example, consider a scenario where a mobile manipulator equipped with high-resolution tactile skin is skilled …

This https://arxiv.org/abs/2409.03685 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

View-Invariant Policy Learning via Zero-Shot Novel View Synthesis
Large-scale visuomotor policy learning is a promising approach toward developing generalizable manipulation systems. Yet, policies that can be deployed on diverse embodiments, environments, and observational modalities remain elusive. In this work, we investigate how knowledge from large-scale visual data of the world may be used to address one axis of variation for generalizable manipulation: observational viewpoint. Specifically, we study single-image novel view synthesis models, which learn …

This https://arxiv.org/abs/2502.10090 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Manual2Skill: Learning to Read Manuals and Acquire Robotic Skills for Furniture Assembly Using Vision-Language Models
Humans possess an extraordinary ability to understand and execute complex manipulation tasks by interpreting abstract instruction manuals. For robots, however, this capability remains a substantial challenge, as they cannot interpret abstract instructions and translate them into executable actions. In this paper, we present Manual2Skill, a novel framework that enables robots to perform complex assembly tasks guided by high-level manual instructions. Our approach leverages a Vision-Language Mode…

This https://arxiv.org/abs/2503.09409 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

AI-based Framework for Robust Model-Based Connector Mating in Robotic Wire Harness Installation
Despite the widespread adoption of industrial robots in automotive assembly, wire harness installation remains a largely manual process, as it requires precise and flexible manipulation. To address this challenge, we design a novel AI-based framework that automates cable connector mating by integrating force control with deep visuotactile learning. Our system optimizes search-and-insertion strategies using first-order optimization over a multimodal transformer architecture trained on visual, ta…

BiAssemble: Learning Collaborative Affordance for Bimanual Geometric Assembly
Yan Shen, Ruihai Wu, Yubin Ke, Xinyuan Song, Zeyi Li, Xiaoqi Li, Hongwei Fan, Haoran Lu, Hao dong
https://arxiv.org/abs/2506.06221

BiAssemble: Learning Collaborative Affordance for Bimanual Geometric Assembly
Shape assembly, the process of combining parts into a complete whole, is a crucial robotic skill with broad real-world applications. Among various assembly tasks, geometric assembly--where broken parts are reassembled into their original form (e.g., reconstructing a shattered bowl)--is particularly challenging. This requires the robot to recognize geometric cues for grasping, assembly, and subsequent bimanual collaborative manipulation on varied fragments. In this paper, we exploit the geometri…

This https://arxiv.org/abs/2506.03896 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

FLIP: Flowability-Informed Powder Weighing
Autonomous manipulation of powders remains a significant challenge for robotic automation in scientific laboratories. The inherent variability and complex physical interactions of powders in flow, coupled with variability in laboratory conditions necessitates adaptive automation. This work introduces FLIP, a flowability-informed powder weighing framework designed to enhance robotic policy learning for granular material handling. Our key contribution lies in using material flowability, quantifie…

This https://arxiv.org/abs/2505.24305 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

SR3D: Unleashing Single-view 3D Reconstruction for Transparent and Specular Object Grasping
Recent advancements in 3D robotic manipulation have improved grasping of everyday objects, but transparent and specular materials remain challenging due to depth sensing limitations. While several 3D reconstruction and depth completion approaches address these challenges, they suffer from setup complexity or limited observation information utilization. To address this, leveraging the power of single view 3D object reconstruction approaches, we propose a training free framework SR3D that enables…

FLIP: Flowability-Informed Powder Weighing
Nikola Radulov (Department of Computer Science University of Liverpool UK), Alex Wright (Department of Computer Science University of Liverpool UK), Thomas little (Department of Computer Science University of Liverpool UK), Andrew I. Cooper (Department of Chemistry university of Liverpool UK), Gabriella Pizzuto (Department of Computer Science University of Liverpool UK, Department of Chemistry university of Liverpool UK)

FLIP: Flowability-Informed Powder Weighing
Autonomous manipulation of powders remains a significant challenge for robotic automation in scientific laboratories. The inherent variability and complex physical interactions of powders in flow, coupled with variability in laboratory conditions necessitates adaptive automation. This work introduces FLIP, a flowability-informed powder weighing framework designed to enhance robotic policy learning for granular material handling. Our key contribution lies in using material flowability, quantifie…

This https://arxiv.org/abs/2503.05231 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Kaiwu: A Multimodal Manipulation Dataset and Framework for Robot Learning and Human-Robot Interaction
Cutting-edge robot learning techniques including foundation models and imitation learning from humans all pose huge demands on large-scale and high-quality datasets which constitute one of the bottleneck in the general intelligent robot fields. This paper presents the Kaiwu multimodal dataset to address the missing real-world synchronized multimodal data problems in the sophisticated assembling scenario,especially with dynamics information and its fine-grained labelling. The dataset first provi…

STAR: Learning Diverse Robot Skill Abstractions through Rotation-Augmented Vector Quantization
Hao Li, Qi Lv, Rui Shao, Xiang Deng, Yinchuan Li, Jianye Hao, Liqiang Nie
https://arxiv.org/abs/2506.03863

STAR: Learning Diverse Robot Skill Abstractions through Rotation-Augmented Vector Quantization
Transforming complex actions into discrete skill abstractions has demonstrated strong potential for robotic manipulation. Existing approaches mainly leverage latent variable models, e.g., VQ-VAE, to learn skill abstractions through learned vectors (codebooks), while they suffer from codebook collapse and modeling the causal relationship between learned skills. To address these limitations, we present \textbf{S}kill \textbf{T}raining with \textbf{A}ugmented \textbf{R}otation (\textbf{STAR}), a f…