Publications (108)
Histopathology WSI Encoding based on GCNs for Scalable and Efficient Retrieval of Diagnostically Relevant Regions
Yushan Zheng, Zhiguo Jiang, Haopeng Zhang +3
Content-based histopathological image retrieval (CBHIR) has become popular in recent years in the domain of histopathological image analysis. CBHIR systems provide auxiliary diagno…
Re-Visible Dual-Domain Self-Supervised Deep Unfolding Network for MRI Reconstruction
Hao Zhang, Qi Wang, Jian Sun +3
Magnetic Resonance Imaging (MRI) is widely used in clinical practice, but suffered from prolonged acquisition time. Although deep learning methods have been proposed to accelerate…
Memory-efficient Embedding for Recommendations
Xiangyu Zhao, Haochen Liu, Hui Liu +6
Practical large-scale recommender systems usually contain thousands of feature fields from users, items, contextual information, and their interactions. Most of them empirically al…
SlideGCD: Slide-based Graph Collaborative Training with Knowledge Distillation for Whole Slide Image Classification
Tong Shu, Jun Shi, Dongdong Sun +2
Existing WSI analysis methods lie on the consensus that histopathological characteristics of tumors are significant guidance for cancer diagnostics. Particularly, as the evolution…
Q-YOLO: Efficient Inference for Real-time Object Detection
Mingze Wang, Huixin Sun, Jun Shi +3
Real-time object detection plays a vital role in various computer vision applications. However, deploying real-time object detectors on resource-constrained platforms poses challen…
Weakly Supervised Lesion Detection and Diagnosis for Breast Cancers with Partially Annotated Ultrasound Images
Jian Wang, Liang Qiao, Shichong Zhou +6
Deep learning (DL) has proven highly effective for ultrasound-based computer-aided diagnosis (CAD) of breast cancers. In an automaticCAD system, lesion detection is critical for th…
H-DenseFormer: An Efficient Hybrid Densely Connected Transformer for Multimodal Tumor Segmentation
Jun Shi, Hongyu Kan, Shulan Ruan +6
Recently, deep learning methods have been widely used for tumor segmentation of multimodal medical images with promising results. However, most existing methods are limited by insu…
Reinforced Bit Allocation under Task-Driven Semantic Distortion Metrics
Jun Shi, Zhibo Chen
Rapid growing intelligent applications require optimized bit allocation in image/video coding to support specific task-driven scenarios such as detection, classification, segmentat…
DIFFUMA: High-Fidelity Spatio-Temporal Video Prediction via Dual-Path Mamba and Diffusion Enhancement
Xinyu Xie, Weifeng Cao, Jun Shi +4
Spatio-temporal video prediction plays a pivotal role in critical domains, ranging from weather forecasting to industrial automation. However, in high-precision industrial scenario…
Shadow-Background-Noise 3D Spatial Decomposition Using Sparse Low-Rank Gaussian Properties for Video-SAR Moving Target Shadow Enhancement
Xiaowo Xu, Xiaoling Zhang, Tianwen Zhang +3
Moving target shadows among video synthetic aperture radar (Video-SAR) images are always interfered by low scattering backgrounds and cluttered noises, causing poor detec-tion-trac…
All-Sky Ultra-Narrowband Spectral Imaging with the OVRO-LWA: Technosignature Constraints and Axion-Like Particle Prospects
Nikita Kosogorov, Gregg Hallinan, Greg Hellbourg +46
We present an imaging-domain search for technosignatures at decametric wavelengths with the OVRO-LWA, targeting ultra-narrowband continuous-wave signals between 50 and 86 MHz. We i…
Causal Incremental Graph Convolution for Recommender System Retraining
Sihao Ding, Fuli Feng, Xiangnan He +3
Real-world recommender system needs to be regularly retrained to keep with the new data. In this work, we consider how to efficiently retrain graph convolution network (GCN) based…
AIM 2019 Challenge on Constrained Super-Resolution: Methods and Results
Kai Zhang, Shuhang Gu, Radu Timofte +26
This paper reviews the AIM 2019 challenge on constrained example-based single image super-resolution with focus on proposed solutions and results. The challenge had 3 tracks. Takin…
LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation
Shengdong Zhang, Fan Jia, Xiang Li +4
Few-shot semantic segmentation (FSS) methods have shown great promise in handling data-scarce scenarios, particularly in medical image segmentation tasks. However, most existing FS…
SASL: Saliency-Adaptive Sparsity Learning for Neural Network Acceleration
Jun Shi, Jianfeng Xu, Kazuyuki Tasaka +1
Accelerating the inference speed of CNNs is critical to their deployment in real-world applications. Among all the pruning approaches, those implementing a sparsity learning framew…
A Survey of Multi-sensor Fusion Perception for Embodied AI: Background, Methods, Challenges and Prospects
Shulan Ruan, Rongwei Wang, Xuchen Shen +8
Multi-sensor fusion perception (MSFP) is a key technology for embodied AI, which can serve a variety of downstream tasks (e.g., 3D object detection and semantic segmentation) and a…
Lightweight Image Super-Resolution with Adaptive Weighted Learning Network
Chaofeng Wang, Zheng Li, Jun Shi
Deep learning has been successfully applied to the single-image super-resolution (SISR) task with great performance in recent years. However, most convolutional neural network base…
NTIRE 2025 Challenge on HR Depth from Images of Specular and Transparent Surfaces
Pierluigi Zama Ramirez, Fabio Tosi, Luigi Di Stefano +36
This paper reports on the NTIRE 2025 challenge on HR Depth From images of Specular and Transparent surfaces, held in conjunction with the New Trends in Image Restoration and Enhanc…
Large Language Model Aided Birt-Hogg-Dube Syndrome Diagnosis with Multimodal Retrieval-Augmented Generation
Haoqing Li, Jun Shi, Xianmeng Chen +5
Deep learning methods face dual challenges of limited clinical samples and low inter-class differentiation among Diffuse Cystic Lung Diseases (DCLDs) in advancing Birt-Hogg-Dube sy…
Deep Synoptic Array Science: Polarimetry of 25 New Fast Radio Bursts Provides Insights into their Origins
Myles B. Sherman, Liam Connor, Vikram Ravi +20
We report on a full-polarization analysis of the first 25 as yet non-repeating FRBs detected at 1.4 GHz by the 110-antenna Deep Synoptic Array (DSA-110) during commissioning observ…
Estimating Electron Densities in the Middle Solar Corona using White-light and Radio Observations
Surajit Mondal, Shaheda Begum Shaik, Russell A. Howard +45
The electron density of the solar corona is a fundamental parameter in many areas of solar physics. Traditionally, routine estimates of coronal density have relied exclusively on w…
Fast MRI Reconstruction via Edge Attention
Hanhui Yang, Juncheng Li, Lok Ming Lui +3
Fast and accurate MRI reconstruction is a key concern in modern clinical practice. Recently, numerous Deep-Learning methods have been proposed for MRI reconstruction, however, they…
Deep Synoptic Array science I: discovery of the host galaxy of FRB 20220912A
Vikram Ravi, Morgan Catha, Ge Chen +25
We report the detection and interferometric localization of the repeating fast radio burst (FRB) source FRB 20220912A during commissioning observations with the Deep Synoptic Array…
Radiative decay of heavy-light mesons from lattice QCD
Wen-Zheng Hou, Nan Wang, Long-Cheng Gui +4
We present the first systematic study of the radiative decays of charmed mesons using -flavor clover fermion gauge ensembles generated by the CLQCD collaboration. One of the e…
Resonances from a Neural Network-based Partial Wave Analysis on Scattering
Jun Shi, Long-Cheng Gui, Jian Liang +1
We implement a convolutional neural network to study the hyperons using experimental data of the reaction. The averaged accuracy of the NN models in resolving…
DEHRFormer: Real-time Transformer for Depth Estimation and Haze Removal from Varicolored Haze Scenes
Sixiang Chen, Tian Ye, Jun Shi +4
Varicolored haze caused by chromatic casts poses haze removal and depth estimation challenges. Recent learning-based depth estimation methods are mainly targeted at dehazing first…
Analysis of via isospin selective reaction
Dan Guo, Jun Shi, Igor Strakovsky +1
The isospin-selective reaction provides a clean probe for investigating resonances. In this work, we perform an analysis of this reaction using an…
Resonances from reactions with the center of mass energy from 1550 to 1676 MeV
Puze Gao, Jun Shi, B. S. Zou
For the study of the resonances, we analyze the differential cross sections and polarizations for the reactions and with an effective Lagr…
Spatial and Modal Optimal Transport for Fast Cross-Modal MRI Reconstruction
Qi Wang, Zhijie Wen, Jun Shi +3
Multi-modal magnetic resonance imaging (MRI) plays a crucial role in comprehensive disease diagnosis in clinical medicine. However, acquiring certain modalities, such as T2-weighte…
Multi-scale Efficient Graph-Transformer for Whole Slide Image Classification
Saisai Ding, Juncheng Li, Jun Wang +2
The multi-scale information among the whole slide images (WSIs) is essential for cancer diagnosis. Although the existing multi-scale vision Transformer has shown its effectiveness…
A channel attention based MLP-Mixer network for motor imagery decoding with EEG
Yanbin He, Zhiyang Lu, Jun Wang +1
Convolutional neural networks (CNNs) and their variants have been successfully applied to the electroencephalogram (EEG) based motor imagery (MI) decoding task. However, these CNN-…
HASN: Hybrid Attention Separable Network for Efficient Image Super-resolution
Weifeng Cao, Xiaoyan Lei, Jun Shi +3
Recently, lightweight methods for single image super-resolution (SISR) have gained significant popularity and achieved impressive performance due to limited hardware resources. The…
Spectral Consistent Flow for One-step 3D Medical Image Translation
Haoqing Li, Jun Shi, Mingchao Li +4
We present Spectral Consistent Flow (SC-Flow), a 3D medical image translation framework with a single function evaluation (1-NFE) in the latent space. This approach reformulates me…
Single-shot Phase Retrieval from a Fractional Fourier Transform Perspective
Yixiao Yang, Ran Tao, Kaixuan Wei +1
The realm of classical phase retrieval concerns itself with the arduous task of recovering a signal from its Fourier magnitude measurements, which are fraught with inherent ambigui…
Reconstruction of Quantitative Susceptibility Maps from Phase of Susceptibility Weighted Imaging with Cross-Connected -Net
Zhiyang Lu, Jun Li, Zheng Li +2
Quantitative Susceptibility Mapping (QSM) is a new phase-based technique for quantifying magnetic susceptibility. The existing QSM reconstruction methods generally require complica…
Huizhou Hadron Spectrometer -- a Proposed High-rate Experimental Setup at the High Intensity Heavy-ion Accelerator Facility
Xurong Chen, Yunyun Fan, Shuangshi Fang +33
The High-Intensity Heavy-Ion Accelerator Facility (HIAF), currently under construction in Huizhou, Guangdong Province, China, is projected to be completed by 2025. This facility wi…
Shadow-Oriented Tracking Method for Multi-Target Tracking in Video-SAR
Xiaochuan Ni, Xiaoling Zhang, Xu Zhan +4
This work focuses on multi-target tracking in Video synthetic aperture radar. Specifically, we refer to tracking based on targets' shadows. Current methods have limited accuracy as…
Near-Field SAR Image Restoration Based On Two Dimensional Spatial-Variant Deconvolution
Wensi Zhang, Xiaoling Zhang, Xu Zhan +3
Images of near-field SAR contains spatial-variant sidelobes and clutter, subduing the image quality. Current image restoration methods are only suitable for small observation angle…
FlashOmni: A Unified Sparse Attention Engine for Diffusion Transformers
Liang Qiao, Yue Dai, Yeqi Huang +3
Multi-Modal Diffusion Transformers (DiTs) demonstrate exceptional capabilities in visual synthesis, yet their deployment remains constrained by substantial computational demands. T…
SANDFORMER: CNN and Transformer under Gated Fusion for Sand Dust Image Restoration
Jun Shi, Bingcai Wei, Gang Zhou +1
Although Convolutional Neural Networks (CNN) have made good progress in image restoration, the intrinsic equivalence and locality of convolutions still constrain further improvemen…
Patterns of CP violation from mirror symmetry breaking in the Dalitz plot
Susan Gardner, Jun Shi
A violation of mirror symmetry in the Dalitz plot has long been recognized as a signal of C and CP violation. Here we show how the isospin of the underlying C-…
SRA-LSTM: Social Relationship Attention LSTM for Human Trajectory Prediction
Yusheng Peng, Gaofeng Zhang, Jun Shi +2
Pedestrian trajectory prediction for surveillance video is one of the important research topics in the field of computer vision and a key technology of intelligent surveillance sys…
Analysis of the Crystal Ball data on reaction with center-of-mass energies of MeV
Jun Shi, Bing-Song Zou
With an effective Lagrangian approach, we analyze the reaction to study the hyperon resonances by fitting the Crystal Ball data on differential cross sectio…
EndoCIL: A Class-Incremental Learning Framework for Endoscopic Image Classification
Bingrong Liu, Jun Shi, Yushan Zheng
Class-incremental learning (CIL) for endoscopic image analysis is crucial for real-world clinical applications, where diagnostic models should continuously adapt to evolving clinic…
Topological GCN for Improving Detection of Hip Landmarks from B-Mode Ultrasound Images
Tianxiang Huang, Jing Shi, Ge Jin +4
The B-mode ultrasound based computer-aided diagnosis (CAD) has demonstrated its effectiveness for diagnosis of Developmental Dysplasia of the Hip (DDH) in infants. However, due to…
Multi-Scale Prototypical Transformer for Whole Slide Image Classification
Saisai Ding, Jun Wang, Juncheng Li +1
Whole slide image (WSI) classification is an essential task in computational pathology. Despite the recent advances in multiple instance learning (MIL) for WSI classification, accu…
Pseudo-Data based Self-Supervised Federated Learning for Classification of Histopathological Images
Jun Shi, Yuanming Zhang, Zheng Li +4
Computer-aided diagnosis (CAD) can help pathologists improve diagnostic accuracy together with consistency and repeatability for cancers. However, the CAD models trained with the h…
Study of nucleon and resonances from a systematic analysis of photoproduction
Jun Shi, Bing-Song Zou
A systematic analysis of the photoproduction off proton is performed with all the available differential cross section data. We carry out a strategy different from the p…
Review of Artificial Intelligence Techniques in Imaging Data Acquisition, Segmentation and Diagnosis for COVID-19
Feng Shi, Jun Wang, Jun Shi +6
(This paper was submitted as an invited paper to IEEE Reviews in Biomedical Engineering on April 6, 2020.) The pandemic of coronavirus disease 2019 (COVID-19) is spreading all over…
Measuring the Magnetic Field of a Coronal Mass Ejection from Low to Middle Corona
Xingyao Chen, Bin Chen, Sijie Yu +44
A major challenge in understanding the initiation and evolution of coronal mass ejections (CMEs) is measuring the magnetic field of the magnetic flux ropes (MFRs) that drive CMEs.…
Pruner: A Draft-then-Verify Exploration Mechanism to Accelerate Tensor Program Tuning
Liang Qiao, Jun Shi, Xiaoyu Hao +10
Tensor program tuning is essential for the efficient deployment of deep neural networks. Search-based approaches have demonstrated scalability and effectiveness in automatically fi…
Frequency Error-Guided Under-sampling Optimization for Multi-Contrast MRI Reconstruction
Xinming Fang, Chaoyan Huang, Juncheng Li +3
Magnetic resonance imaging (MRI) plays a vital role in clinical diagnostics, yet it remains hindered by long acquisition times and motion artifacts. Multi-contrast MRI reconstructi…
Incremental Learning for Personalized Recommender Systems
Yunbo Ouyang, Jun Shi, Haichao Wei +1
Ubiquitous personalized recommender systems are built to achieve two seemingly conflicting goals, to serve high quality content tailored to individual user's taste and to adapt qui…
Enigmatic centi-SFU and mSFU nonthermal radio transients detected in the middle corona
Surajit Mondal, Bin Chen, Sijie Yu +43
Decades of solar coronal observations have provided substantial evidence for accelerated particles in the corona. In most cases, the location of particle acceleration can be roughl…
Lesion-Aware Contrastive Representation Learning for Histopathology Whole Slide Images Analysis
Jun Li, Yushan Zheng, Kun Wu +3
Local representation learning has been a key challenge to promote the performance of the histopathological whole slide images analysis. The previous representation learning methods…
A Dataset and Benchmark for Robotic Cloth Unfolding Grasp Selection: The ICRA 2024 Cloth Competition
Victor-Louis De Gusseme, Thomas Lips, Remko Proesmans +59
Robotic cloth manipulation suffers from a lack of standardized benchmarks and shared datasets for evaluating and comparing different approaches. To address this, we created a bench…
3D Super-Resolution Imaging Method for Distributed Millimeter-wave Automotive Radar System
Yanqin Xu, Xiaoling Zhang, Shunjun Wei +3
Millimeter-wave (mmW) radar is widely applied to advanced autopilot assistance systems. However, its small antenna aperture causes a low imaging resolution. In this paper, a new di…
Solving 3D Radar Imaging Inverse Problems with a Multi-cognition Task-oriented Framework
Xu Zhan, Xiaoling Zhang, Mou Wang +3
This work focuses on 3D Radar imaging inverse problems. Current methods obtain undifferentiated results that suffer task-depended information retrieval loss and thus don't meet the…
Sar Ship Detection based on Swin Transformer and Feature Enhancement Feature Pyramid Network
Xiao Ke, Xiaoling Zhang, Tianwen Zhang +2
With the booming of Convolutional Neural Networks (CNNs), CNNs such as VGG-16 and ResNet-50 widely serve as backbone in SAR ship detection. However, CNN based backbone is hard to m…
Constant-Time-Delay Interferences In Near-Field SAR: Analysis And Suppression In Image Domain
Xu Zhan, Xiaoling Zhang, Jun Shi +1
Inevitable interferences exist for the SAR system, adversely affecting the imaging quality. However, current analysis and suppression methods mainly focus on the far-field situatio…
Deep Unfolding Network with Spatial Alignment for multi-modal MRI reconstruction
Hao Zhang, Qi Wang, Jun Shi +2
Multi-modal Magnetic Resonance Imaging (MRI) offers complementary diagnostic information, but some modalities are limited by the long scanning time. To accelerate the whole acquisi…
Deep Synoptic Array science: A massive elliptical host among two galaxy-cluster fast radio bursts
Kritti Sharma, Jean Somalwar, Casey Law +20
The stellar population environments associated with fast radio burst (FRB) sources provide important insights for developing their progenitor theories. We expand the diversity of k…
Searches for Prompt Low-Frequency Radio Counterparts to Gravitational Wave Event S250206dm with the OVRO-LWA Time Machine
Nikita Kosogorov, Gregg Hallinan, Casey Law +46
We report on a search for prompt, low-frequency radio emission from the gravitational-wave (GW) merger S250206dm using the Owens Valley Radio Observatory Long Wavelength Array (OVR…
Task-driven Self-supervised Bi-channel Networks for Diagnosis of Breast Cancers with Mammography
Ronglin Gong, Jun Wang, Jun Shi
Deep learning can promote the mammography-based computer-aided diagnosis (CAD) for breast cancers, but it generally suffers from the small sample size problem. Self-supervised lear…
Fast Fermion Smearing Scheme with Gaussian-like Profile
ChuanYang Li, Terrence Draper, Jun Hua +5
We propose a novel smearing scheme which gives a Gaussian-like profile and is more efficient than the traditional Gaussian smearing in terms of computer time consumption. We also c…
Relevance-Aware Anomalous Users Detection in Social Network via Graph Neural Network
Yangyang Li, Yipeng Ji, Shaoning Li +6
Anomalous users detection in social network is an imperative task for security problems. Motivated by the great power of Graph Neural Networks(GNNs), many current researches adopt…
A Commensal Radio-Only Cosmic Ray Detector at the Owens Valley Radio Observatory Long Wavelength Array
Kathryn A. Plant, Andrew Romero-Wolf, Gregg Hallinan +46
The brief (10 nanoseconds) transient radio emission from cosmic ray air showers carries key information about the energy and mass composition of high energy cosmic rays, but anthro…
Logit Attenuating Weight Normalization
Aman Gupta, Rohan Ramanath, Jun Shi +4
Over-parameterized deep networks trained using gradient-based optimizers are a popular choice for solving classification and ranking problems. Without appropriately tuned …
Promptable Representation Distribution Learning and Data Augmentation for Gigapixel Histopathology WSI Analysis
Kunming Tang, Zhiguo Jiang, Jun Shi +3
Gigapixel image analysis, particularly for whole slide images (WSIs), often relies on multiple instance learning (MIL). Under the paradigm of MIL, patch image representations are e…
Deep Synoptic Array science: Two fast radio burst sources in massive galaxy clusters
Liam Connor, Vikram Ravi, Morgan Catha +21
The hot gas that constitutes the intracluster medium (ICM) has been studied at X-ray and millimeter/sub-millimeter wavelengths (Sunyaev-Zeldovich effect) for decades. Fast radio bu…
Task-driven Semantic Coding via Reinforcement Learning
Xin Li, Jun Shi, Zhibo Chen
Task-driven semantic video/image coding has drawn considerable attention with the development of intelligent media applications, such as license plate detection, face detection, an…
and mesons from lattice QCD at the physical point using topological charge operators
Yue Su, Nan Wang, Long-cheng Gui +3
By fitting the two-point correlation functions of topological charge density operators calculated on two -flavor gauge ensembles with physical pion mass, we determine both the…
Balance Scene Learning Mechanism for Offshore and Inshore Ship Detection in SAR Images
Tianwen Zhang, Xiaoling Zhang, Jun Shi +5
Huge imbalance of different scenes' sample numbers seriously reduces Synthetic Aperture Radar (SAR) ship detection accuracy. Thus, to solve this problem, this letter proposes a Bal…
Possible First Detection of Gyroresonance Emission from a Coronal Mass Ejection in the Middle Corona
Surajit Mondal, Bin Chen, Xingyao Chen +45
Routine measurements of the magnetic field of coronal mass ejections (CMEs) have been a key challenge in solar physics. Making such measurements is important both from a space weat…
Probing the Turbulent Corona and Heliosphere Using Radio Spectral Imaging Observation during the Solar Conjunction of Crab Nebula
Peijin Zhang, Surajit Mondal, Bin Chen +41
Measuring plasma parameters in the upper solar corona and inner heliosphere is challenging because of the region's weakly emissive nature and inaccessibility for most in situ obser…
Slide-based Graph Collaborative Training for Histopathology Whole Slide Image Analysis
Jun Shi, Tong Shu, Zhiguo Jiang +3
The development of computational pathology lies in the consensus that pathological characteristics of tumors are significant guidance for cancer diagnostics. Most existing research…
Learning to Run challenge solutions: Adapting reinforcement learning methods for neuromusculoskeletal environments
Åukasz KidziÅski, Sharada Prasanna Mohanty, Carmichael Ong +26
In the NIPS 2017 Learning to Run challenge, participants were tasked with building a controller for a musculoskeletal model to make it run as fast as possible through an obstacle c…
Traffic Image Restoration under Adverse Weather via Frequency-Aware Mamba
Liwen Pan, Longguang Wang, Guangwei Gao +3
Traffic image restoration under adverse weather conditions remains a critical challenge for intelligent transportation systems. Existing methods primarily focus on spatial-domain m…
Revisiting and Violation in Decay
Jun Shi, Jian Liang, Susan Gardner
The decay is an ideal process in which to study flavor-conserving and violation beyond the Standard Model. We deduce the - and -odd quark opera…
Investigating the Isospin Property of from its Dalitz Plot Distribution
Jun Shi, Enke Wang, Qian Wang
Recently, LHCb observed a double-charmed tetraquark candidate and claimed its isospin to be zero due to the absence of . However, the absence of the $T_{cc}…
Multi-View Attention Learning for Residual Disease Prediction of Ovarian Cancer
Xiangneng Gao, Shulan Ruan, Jun Shi +2
In the treatment of ovarian cancer, precise residual disease prediction is significant for clinical and surgical decision-making. However, traditional methods are either invasive (…
DARNet: Dual-Attention Residual Network for Automatic Diagnosis of COVID-19 via CT Images
Jun Shi, Huite Yi, Shulan Ruan +4
The ongoing global pandemic of Coronavirus Disease 2019 (COVID-19) poses a serious threat to public health and the economy. Rapid and accurate diagnosis of COVID-19 is crucial to p…
MiMo-VL Technical Report
Core Team, Zihao Yue, Zhenru Lin +71
We open-source MiMo-VL-7B-SFT and MiMo-VL-7B-RL, two powerful vision-language models delivering state-of-the-art performance in both general visual understanding and multimodal rea…
Technical Report: Towards Spatial Feature Regularization in Deep-Learning-Based Array-SAR Reconstruction
Yu Ren, Xu Zhan, Yunqiao Hu +7
Array synthetic aperture radar (Array-SAR), also known as tomographic SAR (TomoSAR), has demonstrated significant potential for high-quality 3D mapping, particularly in urban areas…
Summary of the First Year of the Space Weather Around Young Suns Program: 900 Hours of Low-frequency Radio and Optical Data Dedicated to Young, Solar-type Stars
Ivey Davis, Gregg Hallinan, Nikita Kosogorov +51
The Space Weather Around Young Suns (SWAYS) program was introduced in \citet{Davis2025} as a multi-wavelength monitoring program for studying the activity and particle environments…
MiMo: Unlocking the Reasoning Potential of Language Model -- From Pretraining to Posttraining
LLM-Core Xiaomi, :, Bingquan Xia +62
We present MiMo-7B, a large language model born for reasoning tasks, with optimization across both pre-training and post-training stages. During pre-training, we enhance the data p…
Learned Fast HEVC Intra Coding
Zhibo Chen, Jun Shi, Weiping Li
In High Efficiency Video Coding (HEVC), excellent rate-distortion (RD) performance is achieved in part by having a flexible quadtree coding unit (CU) partition and a large number o…
Clore: Interactive Pathology Image Segmentation with Click-based Local Refinement
Tiantong Wang, Minfan Zhao, Jun Shi +2
Recent advancements in deep learning-based interactive segmentation methods have significantly improved pathology image segmentation. Most existing approaches utilize user-provided…
Lifelong Histopathology Whole Slide Image Retrieval via Distance Consistency Rehearsal
Xinyu Zhu, Zhiguo Jiang, Kun Wu +2
Content-based histopathological image retrieval (CBHIR) has gained attention in recent years, offering the capability to return histopathology images that are content-wise similar…
Deep Synoptic Array Science: Implications of Faraday Rotation Measures of Localized Fast Radio Bursts
Myles B. Sherman, Liam Connor, Vikram Ravi +20
Faraday rotation measures (RMs) of fast radio bursts (FRBs) offer the prospect of directly measuring extragalactic magnetic fields. We present an analysis of the RMs of ten as yet…
Implementation of a Near-Realtime Recording and Reporting System of Solar Radio Bursts
Peijin Zhang, Anastasia Kuske, Bin Chen +48
Strong solar activity is often accompanied by a variety of radio bursts. These bursts are valuable diagnostics of coronal and heliospheric processes and also have potential applica…
RobotGPT: Robot Manipulation Learning from ChatGPT
Yixiang Jin, Dingzhe Li, Yong A +5
We present RobotGPT, an innovative decision framework for robotic manipulation that prioritizes stability and safety. The execution code generated by ChatGPT cannot guarantee the s…
Deciphering the Impact of Pretraining Data on Large Language Models through Machine Unlearning
Yang Zhao, Li Du, Xiao Ding +5
Through pretraining on a corpus with various sources, Large Language Models (LLMs) have gained impressive performance. However, the impact of each component of the pretraining corp…
Mamba-Based Modality Disentanglement Network for Multi-Contrast MRI Reconstruction
Weiyi Lyu, Xinming Fang, Jun Wang +3
Magnetic resonance imaging (MRI) is a cornerstone of modern clinical diagnosis, offering unparalleled soft-tissue contrast without ionizing radiation. However, prolonged scan times…
Sparse Sampling Transformer with Uncertainty-Driven Ranking for Unified Removal of Raindrops and Rain Streaks
Sixiang Chen, Tian Ye, Jinbin Bai +3
In the real world, image degradations caused by rain often exhibit a combination of rain streaks and raindrops, thereby increasing the challenges of recovering the underlying clean…
ASGrasp: Generalizable Transparent Object Reconstruction and 6-DoF Grasp Detection from RGB-D Active Stereo Camera
Jun Shi, Yong A, Yixiang Jin +4
In this paper, we tackle the problem of grasping transparent and specular objects. This issue holds importance, yet it remains unsolved within the field of robotics due to failure…
Pan-cancer Histopathology WSI Pre-training with Position-aware Masked Autoencoder
Kun Wu, Zhiguo Jiang, Kunming Tang +5
Large-scale pre-training models have promoted the development of histopathology image analysis. However, existing self-supervised methods for histopathology images primarily focus…
Predictive Accuracy-Based Active Learning for Medical Image Segmentation
Jun Shi, Shulan Ruan, Ziqi Zhu +4
Active learning is considered a viable solution to alleviate the contradiction between the high dependency of deep learning-based segmentation methods on annotated data and the exp…
Deep Synoptic Array science: a 50 Mpc fast radio burst constrains the mass of the Milky Way circumgalactic medium
Vikram Ravi, Morgan Catha, Ge Chen +21
We present the Deep Synoptic Array (DSA-110) discovery and interferometric localization of the so far non-repeating FRB 20220319D. The FRB originates in a young, rapidly star-formi…
MiMo-V2-Flash Technical Report
Core Team, Bangjun Xiao, Bingquan Xia +123
We present MiMo-V2-Flash, a Mixture-of-Experts (MoE) model with 309B total parameters and 15B active parameters, designed for fast, strong reasoning and agentic capabilities. MiMo-…