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Double-Feedback: Enhancing Large Language Models Reasoning in Robotic Tasks by Knowledge Graphs

IEEE Robotics and Automation Letters 2025年第6期10卷 5951-5958页

作者： Wang, Haitao Zhang, Shaolin Wang, Shuo Jiang, Tianyu Ge, Yueguang Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Beijing100190 China University of Chinese Academy of Sciences School of Artificial Intelligence Beijing100049 China Chinese Academy of Sciences Center for Excellence in Brain Science and Intelligence Technology Shanghai200031 China

Large language models (LLMs) have demonstrated remarkable reasoning capabilities. However, in real-world robotic tasks, LLMs face grounding issues and lack precise feedback, resulting in the generated solutions deviating from the actual situation. In this letter, we propose Double-Feedback, a method that enhances LLMs reasoning by Knowledge graphs (KGs). The KGs play three key roles in Double-Feedback: prompting the LLMs to generate solutions, representing the task scenes, and verifying the solutions to provide feedback. We design structured knowledge prompts that convey the task knowledge background, example solutions, revision principles, and robotic tasks to the LLMs. We also introduce the distributed representation to quantify the task scene with interpretability. Based on the structured knowledge prompts and the distributed representation, we employ the KGs to evaluate the feasibility of each step before execution and verify the effects of the solutions after completing the tasks. The LLMs can adjust and replan the solutions based on the feedback from the KGs. Extensive experiments demonstrate that Double-Feedback outperforms prior works in the ALFRED benchmark. In addition, ablation studies show that Double-Feedback guides LLMs in generating solutions aligned with robotic tasks in the real world. © 2016 IEEE.

关键词： Knowledge graph

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GelStereo Tip: A Spherical Fingertip Visuotactile Sensor for Multi-Finger Screwing Manipulation

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IEEE Transactions on Automation science and Engineering 2025年 22卷 12012-12023页

作者： Zhang, Boyue Cui, Shaowei Zhang, Chaofan Hu, Jingyi Wang, Rui Wang, Shuo University of Chinese Academy of Sciences School of Artificial Intelligence Beijing100049 China Institute of Automation Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing100190 China Institute of Automation Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences School of Future Technology Beijing100049 China Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of Sciences Shanghai200031 China

Dexterous hands are the key element for robots to achieve human-like manipulation capabilities. An outstanding challenge is to provide fingertips of dexterous hands with precise tactile deformation sensing capabilities. In this paper, we present the GelStereo Tip, a spherical and easy-to-integrate GelStereo-type visuotactile sensor capable of sensing high-resolution 3D elastomer deformation. Previous calibration method does not take into account the impact of imaging errors caused by the sensor’s compact and high-curvature structural characteristics on the accuracy of tactile sensing. Therefore, we propose a novel self-calibration method based on the Refractive Stereo Ray Tracing model, named GTSC, and demonstrate the accuracy of less than 0.3 mm for deformation sensing. Furthermore, we also propose a Contact Retention Tactile Controller to address the issue of fingertips being unable to overcome obstructive torque during the multi-finger bottle cap screwing. After integrating GelStereo Tip into fingertips of Allegro Hand, the controller adjusts the joint positions of the given trajectory using proportional control based on the difference between the sensor’s actual deformation and the reference state for contact retention. We believe that the GelStereo Tip sensor combined with robotic dexterous hands has great application potential in the field of multi-finger fingertip manipulation. © 2004-2012 IEEE.

关键词： Proportional control systems

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Neural Network-Based Frequency Optimization for Superconducting Quantum Chips

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chinese Physics Letters 2025年第3期42卷 16-22页

作者： Bin-Han Lu Qing-Song Li Peng Wang Zhao-Yun Chen Yu-Chun Wu Guo-Ping Guo Key Laboratory of Quantum Information Chinese Academy of Sciences School of PhysicsUniversity of Science and Technology of ChinaHefei 230026China CAS Center For Excellence in Quantum Information and Quantum Physics University of Science and Technology of ChinaHefei 230026China Institute of Artificial Intelligence Hefei Comprehensive National Science CenterHefei 230026China Origin Quantum Co. Ltd.(Hefei)

Optimizing frequency configurations for qubits and gates in superconducting quantum chips presents a complex NP-complete challenge,critical for mitigating decoherence and *** paper introduces a neural network-based approach,leveraging the network as a surrogate model to predict frequency *** method employs a closed-loop Bayesian optimization framework to iteratively refine configurations,guided by the network’s knowledge of nonlinear error *** focusing on localized chip windows,the optimization identifies optimal frequency settings that minimize *** approach is validated through randomized and cross-entropy benchmarking,showing improved energy calculations when optimizing frequency configurations for a crosstalkaware hardware-efficient ansatz in variational quantum eigensolvers on superconducting quantum chips.

关键词： quantum optimization variational

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Multiscale Temporal-Convolution and Attention Improved Neural Network for Biased Mental State Recognition 17th

Multiscale Temporal-Convolution and Attention Improved Neur...

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17th International Conference on brain Informatics, BI 2024

作者： Zuo, Guoyu Xiao, Erjun Zhang, Tielin Beijing Key Laboratory of Computing Intelligence and Intelligent Systems Beijing University of Technology Beijing100124 China Center for Excellence in Brain Science and Intelligence Technology University of Chinese Academy of Sciences Shanghai200031 China

ISBN: (纸本)9789819632930

Accurate detection of mental state is vital for sleep assessment and anesthesia monitoring. However, challenges exist, including 1) limited data sources caused by few modalities, few channels, biased sample distribution, or large individual differences;2) multiscale dynamic feature of mental state signals, containing complex and dynamic fluctuations. In this paper, we proposed a multiscale temporal convolution and attention improved neural network (MTA-NN) to handle these two challenges, including: a preprocessing method using a clustering-first and label-generation approach for data augmentation involves filtering the production samples to mitigate the impact of noise on model performance;multiscale temporal-convolution module for detecting different scales of temporal and frequency features;an attention module for decoding key features in different spatial and temporal channels, and for setting the importance of historical dependencies;a full-connection layer is designed to recognize different sleep stage. The proposed MTA-NN is then verified in three typical sleep-state recognition tasks, including SleepEDF-20, SleepEDF-78, and ISRUC3. Compared to some state-of-the-art algorithms, the proposed MTA-NN achieves higher performance. Further ablation experiments show the necessary and importance of these designed sub modules in MTA-NN. We consider the same algorithm can also be extended to further similar mental state recognition tasks such as anesthesia monitoring. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Anesthesiology

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Dynamic alterations in bacterial and fungal microbiome and inflammatory cytokines following SRV-8 infection in cynomolgus monkeys

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Zoological Research 2025年第2期46卷 325-338页

作者： Yun-Peng Yang Li-Bing Xu Yong Lu Jing Wang Yan-Hong Nie Qiang Sun Jiangsu Co-innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonoses College of Veterinary MedicineYangzhou UniversityYangzhouJiangsu 225009China Institute of Comparative Medicine Yangzhou UniversityYangzhouJiangsu 225009China Shanghai Center for Brain Science and Brain-Inspired Technology Shanghai 201602China Institute of Neuroscience CAS Key Laboratory of Primate NeurobiologyState Key Laboratory of NeuroscienceCAS Center for Excellence in Brain Science and Intelligence TechnologyChinese Academy of SciencesShanghai 200031China Key Laboratory of Genetic Evolution&Animal Models Chinese Academy of SciencesKunmingYunnan 650201China

While viral infections can disturb the host gut microbiome,the dynamic alterations in microbial composition following infection remain poorly *** study identified SRV-8-infected monkeys and classified them into five groups based on infection progression.16S rRNA amplicon sequencing revealed significant alterations in the relative and inferred absolute abundance of bacterial genera UCG-002,Agathobacter,Coprococcus,and Holdemanella during the early stage of SRV-8 infection,coinciding with provirus *** microbial shifts were accompanied by functional modifications in bacterial communities at the same *** contrast,ITS amplicon sequencing indicated no significant differences in fungal composition between healthy wild-type and SRV-8-infected *** correlation analyses demonstrated close interactions between intestinal bacteria and fungi following SRV-8 ***,SRV-8 seropositive groups exhibited significantly elevated mRNA expression levels of pro-inflammatory(TNF-α,IFN-γ,IL-1β,and IL-6)and anti-inflammatory(IL-10)cytokine genes,highlighting close associations between inflammatory cytokines and immune ***,these findings provide a comprehensive characterization of bacterial and fungal microbiota dynamics and inflammatory cytokine responses associated with SRV-8 infection,clarifying the pathobiological mechanisms underlying SRV-8 infection from the perspective of the gut microbiome.

关键词： Cynomolgus monkeys SRV-8 infection Dynamic alterations Bacterial and fungal microbes Inflammatory cytokines

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Artificial sensory neurons and their applications

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Journal of Semiconductors 2025年第1期46卷 108-128页

作者： Jiale Shao Hongwei Ying Peihong Cheng Lingxiang Hu Xianhua Wei Zongxiao Li Huanming Lu Zhizhen Ye Fei Zhuge Faculty of Electrical Engineering and Computer Science Ningbo UniversityNingbo 315211China Ningbo Institute of Materials Technology and Engineering Chinese Academy of SciencesNingbo 315201China School of Electronic and Information Engineering Ningbo University of TechnologyNingbo 315211China State Key Laboratory of Environment-friendly Energy Materials Southwest University of Science and TechnologyMianyang 621010China Institute of Wenzhou Zhejiang UniversityWenzhou 325006China State Key Laboratory of Silicon Materials School of Materials Science and EngineeringZhejiang UniversityHangzhou 310027China Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of SciencesShanghai 200072China

With the rapid development of artificial intelligence(AI)technology,the demand for high-performance and energyefficient computing is increasingly *** limitations of the traditional von Neumann computing architecture have prompted researchers to explore neuromorphic computing as a *** computing mimics the working principles of the human brain,characterized by high efficiency,low energy consumption,and strong fault tolerance,providing a hardware foundation for the development of new generation AI *** neurons and synapses are the two core components of neuromorphic computing *** perception is a crucial aspect of neuromorphic computing,where artificial sensory neurons play an irreplaceable role thus becoming a frontier and hot topic of *** work reviews recent advances in artificial sensory neurons and their ***,biological sensory neurons are briefly ***,different types of artificial neurons,such as transistor neurons and memristive neurons,are discussed in detail,focusing on their device structures and working ***,the research progress of artificial sensory neurons and their applications in artificial perception systems is systematically elaborated,covering various sensory types,including vision,touch,hearing,taste,and ***,challenges faced by artificial sensory neurons at both device and system levels are summarized.

关键词： artificial sensory neurons artificial perception systems neuromorphic computing artificial intelligence

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IsoVISoR: Towards 3D Mesoscale brain Mapping of Large Mammals at Isotropic Sub-micron Resolution

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Neuroscience Bulletin 2025年第2期41卷 344-348页

作者： Chao-Yu Yang Yan Shen Xiaoyang Qi Lufeng Ding Yanyang Xiao Qingyuan Zhu Hao Wang Cheng Xu Pak-Ming Lau Pengcheng Zhou Fang Xu Guo-Qiang Bi Division of Life Sciences and Medicine CAS Key Laboratory of Brain Function and DiseaseUniversity of Science and Technology of ChinaHefei230026China Interdisciplinary Center for Brain Information Shenzhen-Hong Kong Institute of Brain ScienceShenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen518055China Center for Integrative Imaging Hefei National Research Center for Physical Sciences at the MicroscaleUniversity of Science and Technology of ChinaHefei230027China National Engineering Laboratory for Brain-Inspired Intelligence Technology and Application MoE Key Laboratory of Brain-Inspired Intelligent Perception and CognitionSchool of Information Science and TechnologyUniversity of Science and Technology of ChinaHefei230026China Anhui Province Key Laboratory of Biomedical Imaging and Intelligent Processing Institute of Artificial IntelligenceHefei Comprehensive National Science CenterHefei230088China Faculty of Life and Health Sciences Shenzhen University of Advanced TechnologyShenzhen518107China CAS Key Laboratory of Brain Connectome and Manipulation The Brain Cognition and Brain Disease InstituteShenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen518055China

Dear Editor,The mammalian brain exhibits cross-scale complexity in neuronal morphology and connectivity,the study of which demands high-resolution morphological reconstruction of individual neurons across the entire brain[1-4].Current commonly used approaches for such mesoscale brain mapping include two main types of three-dimensional fluorescence microscopy:the block-face methods,and the lightsheet-based methods[5,6].In general,the high imaging speed and light efficiency of light-sheet microscopy make it a suitable tool for high-throughput volumetric imaging,especially when combined with tissue-clearing ***,large brain samples pose major challenges to this approach.

关键词： brain mapping three dimensional fluorescence microscopy mesoscale brain mapping lightsheet based methods block face methods high throughput volumetric imaging tissue clearing techniques

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Critical biomarkers for responsive deep brain stimulation and responsive focal cortex stimulation in epilepsy field

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Fundamental Research 2025年第1期5卷 103-114页

作者： Zhikai Yu Binghao Yang Penghu Wei Hang Xu Yongzhi Shan Xiaotong Fan Huaqiang Zhang Changming Wang a d Jingjing Wang Shan Yu Guoguang Zhao Department of Neurosurgery Xuanwu HospitalCapital Medical UniversityBeijing 100053China Laboratory of Brain Atlas and Brain Inspired Intelligence Institute of AutomationChinese Academy of ScienceBeijing 100190China Clinical Research Center for Epilepsy Capital Medical UniversityBeijing 100053China Laboratory of Brain Inspired Intelligence Capital Medical UniversityBeijing 100053China School of Future Technology University of Chinese Academy of ScienceBeijing 101408China

To derive critical signal features from intracranial electroencephalograms of epileptic patients in order to design instructions for feedback-type electrical stimulation *** Detrended Fluctuation Analysis(DFA)exponent is chosen as the classification exponent,and the disparities between indicators representing distinct seizure states and the classification efficacy of rudimentary machine learning models are *** DFA exponent exhibited a statistically significant variation among the pre-ictal,ictal period,and post-ictal *** Linear Discriminant Analysis model demonstrates the highest accuracy among the three basic machine learning models,whereas the Naive Bayesian model necessitates the least amount of computational and storage *** set of DFA exponents is employed as an intermediary variable in the machine learning *** resultant model possesses the capability to function as a feedback trigger program for electrical stimulation systems of the feedback variety,specifically within the domain of neural modulation in epilepsy.

关键词： Biomarker Critical state Feedback electrical stimulation Epilepsy brain computer interface

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Efficient generation of all ESC-derived mice carrying a homozygous lethal mutation through eight-cell embryo injection

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science China Life sciences 2025年第5期68卷 1524-1527页

作者： Xidi Yin Meng Yan Yanbo Cheng Zhoujie Li Chong Cui Yingyi Wang Nan Liu Yilai Shu Jinsong Li Qing Li Key Laboratory of Multi-Cell Systems Shanghai Key Laboratory of Molecular AndrologyShanghai Institute of Biochemistry and Cell BiologyCenter for Excellence in Molecular Cell ScienceChinese Academy of Sciences School of Life Science and Technology Shanghai Tech University Animal Core Facility Shanghai Institute of Biochemistry and Cell BiologyCenter for Excellence in Molecular Cell ScienceChinese Academy of Sciences ENT Institute and Department of Otorhinolaryngology Eye & ENT HospitalState Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceFudan University Key Laboratory of Systems and Health Science of Zhejiang Province School of Life ScienceHangzhou Institute for Advanced StudyUniversity of Chinese Academy of Sciences

Dear Editor, Large-scale phenotyping efforts have shown that placental defects correlate strongly with embryonic lethal mouse mutants(Perez-Garcia et al., 2018). To rescue normal development of these mutant embryos, tetraploid complementation can be a reliable strategy, in which,tetraploid cells form extraembryonic lineages thus providing the embryo with a wild-type placenta(Nagy et al., 1990).

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A Flexible and Ultrasensitive Artificial Compound Eye Using Bionic Micro-Lens Array for Drone Vision 38

A Flexible and Ultrasensitive Artificial Compound Eye Using ...

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38th IEEE International Conference on Micro Electro Mechanical Systems, MEMS 2025

作者： Wang, Jiachuang Zhao, Fangyu Liu, Wenyuan Qin, Nan Tao, Tiger H. State Key Laboratory of Transducer Technology Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai China 2020 X-Lab Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai China School of Graduate Study University of Chinese Academy of Sciences Beijing China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of Sciences Beijing China Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of Sciences Shanghai China Jiangxi Nanchang China Guangdong Institute of Intelligence Science and Technology Zhuhai Guangdong Hengqin China Tianqiao and Chrissy Chen Institute for Translational Research Shanghai China

ISBN: (纸本)9798331508890

We report a bionic artificial compound eye based on flexible quantum dots film and micro electromechanical system (MEMS) fabrication process. The device integrates organic photodetector and micro-lens array, featuring the high-speed response, ultrathin thickness and extensive curvature radius. Our artificial eye exhibits significant discriminative detection to different targets with varying shapes and distances. The insect scale biomimetic compound eye provides a novel precision integration route for flexible optoelectronic devices and micro-optics, showing great potential applications in drone vision and bionic robot navigation. © 2025 IEEE.

关键词： Semiconductor quantum dots

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