Daily Papers
- Defect Detection
- Defect Segmentation
- Anomaly Detection
- 3D Anomaly Detection
- Multimodal Anomaly Detection
- Vector Quantization
Updated on 2026.06.08
Defect Detection
| Date | Title | Authors | Code | Comments | |
|---|---|---|---|---|---|
| 2026-6-3 | Attention-Guided Autoencoder Fusion for Insulator Defect Detection Using UAV Transmission-Line Imaging | Malak Allam et.al | paper | - | - |
| 2026-6-2 | Structure-Guided Mixed Masked Pretraining and Spatial Continuity Regularization for Printed Circuit Board Defect Detection | Peitong Wang et.al | paper | - | <summary>detail</summary>Preprint |
| 2026-6-2 | Contrastive Augmented Transformer with Domain-specific Enhancement for Robust Multi-scenario Metal Surface Defect Detection | Yiyao Liu et.al | paper | - | - |
| 2026-6-1 | Improving Combined Detection and Classification of TEM Defects via Mask-Conditioned Latent Diffusion Augmentation | Ni Li et.al | paper | - | - |
| 2026-5-30 | RefDiffNet: Learning to Expose Subtle PCB Defects Before Detection | Vinay Edula et.al | paper | - | - |
| 2026-5-28 | Unsupervised Defect Detection for Surgical Instruments | Joseph Huang et.al | paper | - | - |
| 2026-5-26 | Advancing Metallic Surface Defect Detection via Anomaly-Guided Pretraining on a Large Industrial Dataset | Chuni Liu et.al | paper | code | <summary>detail</summary>Accepted for publication in Pattern Recognition |
| 2026-5-26 | UniPCB: A Generation-Assisted Detection Framework for PCB Defect Inspection | Huan Zhang et.al | paper | - | - |
| 2026-5-25 | A Universal Cliff and a Design Fingerprint: Cross-Section Defect Detection Under LLM Orchestration | Hiroki Fukui et.al | paper | - | - |
| 2026-5-23 | From Full Boards to Tiny Defects: Scale-Aware Tile Inference with Topology-Aware Merging for High-Resolution PCB Defect Detection | Mohammad Alijanpour Shalmani et.al | paper | - | - |
| 2026-5-23 | FDDet: Achieving Data-Efficient Food Defect Detection Under Real-World Scenarios | Ruihao Xu et.al | paper | - | - |
| 2026-5-20 | BioDefect: The First Dataset for Defect Detection in Bioinformatics Software | Tianxiang Xu et.al | paper | - | - |
| 2026-5-19 | Interpretable Computer Vision for Defect Detection in X-ray Tomography of Aerospace SiC/SiC Composites | Antonio Peña Corredor et.al | paper | - | - |
| 2026-5-17 | Network Knowledge Prior Guided Learning for Data-Efficient Surface Defect Detection | Hang-Cheng Dong et.al | paper | - | - |
| 2026-5-13 | Hybrid Quantum-MambaVision: A Quantum-enhanced State Space Model for Calibrated Mixed-type Wafer Defect Detection | Satwik Sai Prakash Sahoo et.al | paper | - | - |
| 2026-5-9 | Micro-Defects Expose Macro-Fakes: Detecting AI-Generated Images via Local Distributional Shifts | Boxuan Zhang et.al | paper | code | - |
| 2026-5-9 | Contour-Native Bridge Defect Detection and Compact Digital Archiving with Frequency-Supervised Fourier Contours | Jin Liu et.al | paper | - | - |
| 2026-5-3 | Application Research of a Deep Learning Model Integrating CycleGAN and YOLO in PCB Infrared Defect Detection | Chao Yang et.al | paper | - | <summary>detail</summary>Authors have conflict of interest |
| 2026-5-1 | Event-based Civil Infrastructure Visual Defect Detection: ev-CIVIL Dataset and Benchmark | Udayanga G. W. K. N. Gamage et.al | paper | - | <summary>detail</summary>Accepted version of the journal paper published in Sage Structural health monitoring journa and it is under review currently |
| 2026-4-29 | SynSur: An end-to-end generative pipeline for synthetic industrial surface defect generation and detection | Paul Julius Kühn et.al | paper | - | - |
| 2026-4-27 | Defective Task Descriptions in LLM-Based Code Generation: Detection and Analysis | Amal Akli et.al | paper | - | - |
| 2026-4-23 | Automated Annotation of Shearographic Measurements Enabling Weakly Supervised Defect Detection | Jessica Plassmann et.al | paper | - | - |
| 2026-4-21 | Feature Perturbation Pool-based Fusion Network for Unified Multi-Class Industrial Defect Detection | Yuanchan Xu et.al | paper | - | - |
| 2026-4-21 | Industrial Surface Defect Detection via Diffusion Generation and Asymmetric Student-Teacher Network | Shuo Feng et.al | paper | - | - |
| 2026-4-21 | Proactive Detection of GUI Defects in Multi-Window Scenarios via Multimodal Reasoning | Xinyao Zhang et.al | paper | - | - |
Defect Segmentation
| Date | Title | Authors | Code | Comments | |
|---|---|---|---|---|---|
| 2026-6-2 | Cesarean Scar Defect Segmentation in Transvaginal Ultrasound Images: a Dataset and Benchmark | Yuan Tian et.al | paper | - | - |
| 2026-4-20 | DeltaSeg: Tiered Attention and Deep Delta Learning for Multi-Class Structural Defect Segmentation | Enrique Hernandez Noguera et.al | paper | - | - |
| 2026-4-13 | Boxes2Pixels: Learning Defect Segmentation from Noisy SAM Masks | Camile Lendering et.al | paper | code | <summary>detail</summary>Accepted for presentation at the AI4RWC Workshop at CVPR 2026 |
| 2026-3-15 | Multi-Period Texture Contrast Enhancement for Low-Contrast Wafer Defect Detection and Segmentation | Zihan Zhang et.al | paper | - | - |
| 2026-2-11 | Defect-aware Hybrid Prompt Optimization via Progressive Tuning for Zero-Shot Multi-type Anomaly Detection and Segmentation | Nadeem Nazer et.al | paper | - | - |
| 2026-1-22 | A Segmentation-driven Editing Method for Bolt Defect Augmentation and Detection | Yangjie Xiao et.al | paper | code | - |
| 2025-11-24 | A Storage-Efficient Feature for 3D Concrete Defect Segmentation to Replace Normal Vector | Linxin Hua et.al | paper | - | - |
| 2025-11-8 | Point Cloud Segmentation of Integrated Circuits Package Substrates Surface Defects Using Causal Inference: Dataset Construction and Methodology | Bingyang Guo et.al | paper | - | - |
| 2025-11-6 | KARMA: Efficient Structural Defect Segmentation via Kolmogorov-Arnold Representation Learning | Md Meftahul Ferdaus et.al | paper | code | <summary>detail</summary>This work has been submitted to the IEEE for possible publication |
| 2025-10-15 | Sample-Centric Multi-Task Learning for Detection and Segmentation of Industrial Surface Defects | Hang-Cheng Dong et.al | paper | - | - |
| 2025-10-6 | Attention-Enhanced Prototypical Learning for Few-Shot Infrastructure Defect Segmentation | Christina Thrainer et.al | paper | - | - |
| 2025-10-1 | Defect Segmentation in OCT scans of ceramic parts for non-destructive inspection using deep learning | Andrés Laveda-Martínez et.al | paper | - | - |
| 2025-9-11 | Unsupervised Integrated-Circuit Defect Segmentation via Image-Intrinsic Normality | Botong Zhao et.al | paper | - | - |
| 2025-8-6 | MultiADS: Defect-aware Supervision for Multi-type Anomaly Detection and Segmentation in Zero-Shot Learning | Ylli Sadikaj et.al | paper | - | - |
| 2025-7-23 | Exploring Active Learning for Semiconductor Defect Segmentation | Lile Cai et.al | paper | - | <summary>detail</summary>accepted to ICIP 2022 |
| 2025-7-14 | Advancing Automatic Photovoltaic Defect Detection using Semi-Supervised Semantic Segmentation of Electroluminescence Images | Abhishek Jha et.al | paper | code | - |
| 2025-6-28 | Region-Aware CAM: High-Resolution Weakly-Supervised Defect Segmentation via Salient Region Perception | Hang-Cheng Dong et.al | paper | - | - |
| 2025-6-24 | Evolutionary computing-based image segmentation method to detect defects and features in Additive Friction Stir Deposition Process | Akshansh Mishra et.al | paper | - | - |
| 2025-6-17 | synth-dacl: Does Synthetic Defect Data Enhance Segmentation Accuracy and Robustness for Real-World Bridge Inspections? | Johannes Flotzinger et.al | paper | - | - |
| 2025-4-24 | Conformal Segmentation in Industrial Surface Defect Detection with Statistical Guarantees | Cheng Shen et.al | paper | - | <summary>detail</summary>Under Review |
| 2025-4-11 | Weakly Supervised Panoptic Segmentation for Defect-Based Grading of Fresh Produce | Manuel Knott et.al | paper | code | <summary>detail</summary>Accepted as a paper to the 6th International Workshop on Agriculture-Vision: Challenges & Opportunities for Computer Vision in Agriculture in conjunction with IEEE/CVF CVPR 2025 |
| 2025-2-11 | Exploring Few-Shot Defect Segmentation in General Industrial Scenarios with Metric Learning and Vision Foundation Models | Tongkun Liu et.al | paper | code | - |
| 2025-1-23 | Effective Defect Detection Using Instance Segmentation for NDI | Ashiqur Rahman et.al | paper | code | - |
| 2025-1-17 | Multi-Modal Attention Networks for Enhanced Segmentation and Depth Estimation of Subsurface Defects in Pulse Thermography | Mohammed Salah et.al | paper | - | <summary>detail</summary>Pulse thermography |
| 2024-10-24 | Synth4Seg – Learning Defect Data Synthesis for Defect Segmentation using Bi-level Optimization | Shancong Mou et.al | paper | - | - |
Anomaly Detection
| Date | Title | Authors | Code | Comments | |
|---|---|---|---|---|---|
| 2026-6-5 | Learnable Kernel Density Estimation for Graphs and Its Application to Graph-Level Anomaly Detection | Xudong Wang et.al | paper | - | <summary>detail</summary>Accepted in the Forty-Third International Conference on Machine Learning (ICML 2026) |
| 2026-6-4 | DAST: A VLM-LLM Framework for Cross-Interface Anomaly Detection in O-RAN | Francesco Spinelli et.al | paper | - | - |
| 2026-6-4 | Cluster-Aware Causal Mixer for Online Anomaly Detection in Multivariate Time Series | Md Mahmuddun Nabi Murad et.al | paper | - | - |
| 2026-6-4 | T-SAR-JEPA: Self-Supervised Temporal Anomaly Detection in SAR Amplitude Stacks via Latent Prediction | Kerod Woldesenbet et.al | paper | code | <summary>detail</summary>Won IEEE GRSS Data Fusion Contest 2026 |
| 2026-6-3 | Anomaly Detection for Electro-Hydrostatic Actuators using LSTM Autoencoder | Nehal Afifi et.al | paper | - | - |
| 2026-6-3 | NLLog: Lightweight, Explainable SOC Anomaly Detection via Log-to-Language Rewriting | Samuel Ndichu et.al | paper | - | - |
| 2026-6-3 | Plan First, Judge Later, Run Better: A DMAIC-Inspired Agentic System for Industrial Anomaly Detection | Yongzi Yu et.al | paper | - | - |
| 2026-6-2 | VT-3DAD: Cross-Category 3D Anomaly Detection via Visual-Text Normal Space Alignment | Zi Wang et.al | paper | - | - |
| 2026-6-2 | TPA-AD: A Two-Stage Pseudo Anomaly-Guided Method for Bearing Time-Series Anomaly Detection | Xiancheng Wang et.al | paper | - | - |
| 2026-6-1 | Trans GAN-WT: A Feature Extraction and Interactive Learning-Based Anomaly Detection Model for Wind Turbine Time Series Data | Jingzhe Kang et.al | paper | - | - |
| 2026-6-1 | Enhancing Computer Vision Model Generalization in Warehouse Facilities: A Case Study on Anomaly Detection in Vertical Material Handling Systems | Ruiliang Liu et.al | paper | - | - |
| 2026-6-1 | Normality-Preserving Continual Industrial Anomaly Detection via Orthogonal LoRA Banks | Weibai Fang et.al | paper | - | - |
| 2026-6-1 | A Structured Benchmark for Text-Guided Anomaly Detection: When Language Stops Conditioning the Decision | Stefano Samele et.al | paper | - | - |
| 2026-6-1 | IstGPT: LLM-based Anomaly Detection for Spatial-Temporal Graph in Industrial Systems | Yuchen Zhang et.al | paper | - | - |
| 2026-5-31 | AnomSeer: Reinforcing Multimodal LLMs to Reason for Time-Series Anomaly Detection | Junru Zhang et.al | paper | - | <summary>detail</summary>ICML 2026 |
| 2026-5-31 | ChronosAD: Leveraging Time Series Foundation Models for Accurate Anomaly Detection | Uzair Khan et.al | paper | code | <summary>detail</summary>the 24th IEEE International Conference on Industrial Informatics (INDIN) 2026 |
| 2026-5-30 | MINES: Explainable Anomaly Detection through Web API Invariant Inference | Wenjie Zhang et.al | paper | - | <summary>detail</summary>Accepted by ICSE 2026 |
| 2026-5-30 | Beyond Normal References: Discriminative Few-Shot Anomaly Detection | Huan Wang et.al | paper | code | - |
| 2026-5-30 | State Machine Guided Multi-Relational Synthetic Data from Logs for Anomaly Detection | Aja Khanal et.al | paper | - | <summary>detail</summary>Journal ref:Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining V |
| 2026-5-29 | Rethinking Weak Supervision in Anomaly Detection: A Comprehensive Benchmark | Xu Yao et.al | paper | code | <summary>detail</summary>KDD 2026 Datasets and Benchmarks Track |
| 2026-5-29 | Modeling Spectral Energy Shifts in Spatio-Temporal Graph Anomaly Detection | Yilin Liu et.al | paper | - | - |
| 2026-5-29 | Conditional Attribution for Root Cause Analysis in Time-Series Anomaly Detection | Shashank Mishra et.al | paper | - | <summary>detail</summary>ECML PKDD |
| 2026-5-29 | Lightweight CNN-Based Anomaly Detection for High Voltage Converter Modulators in the Spallation Neutron Source | Alberto D. Cencillo et.al | paper | - | - |
| 2026-5-29 | Towards Foundation Models for Zero-Shot Time Series Anomaly Detection: Leveraging Synthetic Data and Relative Context Discrepancy | Tian Lan et.al | paper | - | <summary>detail</summary>This manuscript is withdrawn |
| 2026-5-29 | DEM: A Distilled Explanation Model for Interpretable Anomaly Detection in Physiological Sensor Networks | Jyotirmoy Singh et.al | paper | code | - |
3D Anomaly Detection
| Date | Title | Authors | Code | Comments | |
|---|---|---|---|---|---|
| 2026-6-2 | VT-3DAD: Cross-Category 3D Anomaly Detection via Visual-Text Normal Space Alignment | Zi Wang et.al | paper | - | - |
| 2026-5-25 | GS-CLIP: Zero-shot 3D Anomaly Detection by Geometry-Aware Prompt and Synergistic View Representation Learning | Zehao Deng et.al | paper | code | <summary>detail</summary>Accepted by CVPR 2026 |
| 2026-5-7 | Align3D-AD: Cross-Modal Feature Alignment and Dual-Prompt Learning for Zero-shot 3D Anomaly Detection | Letian Bai et.al | paper | - | - |
| 2026-5-6 | Two Steps Are All You Need: Efficient 3D Point Cloud Anomaly Detection with Consistency Models | Pranav A et.al | paper | - | <summary>detail</summary>CVPR 2026 |
| 2026-5-6 | Learning Discriminative Signed Distance Functions from Multi-scale Level-of-detail Features for 3D Anomaly Detection | Haibo Xiao et.al | paper | code | - |
| 2026-4-29 | Breaking the Rigid Prior: Towards Articulated 3D Anomaly Detection | Jinye Gan et.al | paper | - | - |
| 2026-4-6 | Synthesis4AD: Synthetic Anomalies are All You Need for 3D Anomaly Detection | Yihan Sun et.al | paper | code | - |
| 2026-4-5 | Hierarchical Point-Patch Fusion with Adaptive Patch Codebook for 3D Shape Anomaly Detection | Xueyang Kang et.al | paper | - | - |
| 2026-4-2 | Modulate-and-Map: Crossmodal Feature Mapping with Cross-View Modulation for 3D Anomaly Detection | Alex Costanzino et.al | paper | - | <summary>detail</summary>CVPR Findings 2026 |
| 2026-4-1 | Open-Set Supervised 3D Anomaly Detection: An Industrial Dataset and a Generalisable Framework for Unknown Defects | Hanzhe Liang et.al | paper | code | <summary>detail</summary>Resources: https://github |
| 2026-3-26 | A Semantically Disentangled Unified Model for Multi-category 3D Anomaly Detection | SuYeon Kim et.al | paper | - | <summary>detail</summary>Accepted by CVPR 2026 |
| 2026-3-22 | Back to Point: Exploring Point-Language Models for Zero-Shot 3D Anomaly Detection | Kaiqiang Li et.al | paper | code | <summary>detail</summary>Accepted by CVPR 2026 |
| 2026-3-4 | Cross-Modal Mapping and Dual-Branch Reconstruction for 2D-3D Multimodal Industrial Anomaly Detection | Radia Daci et.al | paper | code | - |
| 2026-2-16 | Training-Free Zero-Shot Anomaly Detection in 3D Brain MRI with 2D Foundation Models | Tai Le-Gia et.al | paper | - | <summary>detail</summary>Accepted for MIDL 2026 |
| 2026-2-11 | DMP-3DAD: Cross-Category 3D Anomaly Detection via Realistic Depth Map Projection with Few Normal Samples | Zi Wang et.al | paper | - | - |
| 2025-12-15 | 3D Human-Human Interaction Anomaly Detection | Shun Maeda et.al | paper | - | - |
| 2025-12-14 | A Lightweight 3D Anomaly Detection Method with Rotationally Invariant Features | Hanzhe Liang et.al | paper | - | <summary>detail</summary>Preprint |
| 2025-11-23 | PointAD+: Learning Hierarchical Representations for Zero-shot 3D Anomaly Detection | Qihang Zhou et.al | paper | - | <summary>detail</summary>Submitted to TPAMI |
| 2025-11-16 | CASL: Curvature-Augmented Self-supervised Learning for 3D Anomaly Detection | Yaohua Zha et.al | paper | code | <summary>detail</summary>AAAI 2026 |
| 2025-11-5 | IEC3D-AD: A 3D Dataset of Industrial Equipment Components for Unsupervised Point Cloud Anomaly Detection | Bingyang Guo et.al | paper | - | - |
| 2025-10-19 | Registration is a Powerful Rotation-Invariance Learner for 3D Anomaly Detection | Yuyang Yu et.al | paper | - | - |
| 2025-10-14 | IterMask3D: Unsupervised Anomaly Detection and Segmentation with Test-Time Iterative Mask Refinement in 3D Brain MR | Ziyun Liang et.al | paper | code | <summary>detail</summary>Published in Medical Image Analysis |
| 2025-9-23 | 3D-ADAM: A Dataset for 3D Anomaly Detection in Additive Manufacturing | Paul McHard et.al | paper | - | - |
| 2025-9-16 | Taming Anomalies with Down-Up Sampling Networks: Group Center Preserving Reconstruction for 3D Anomaly Detection | Hanzhe Liang et.al | paper | - | <summary>detail</summary>ACM MM25 Accepted |
| 2025-9-12 | MCL-AD: Multimodal Collaboration Learning for Zero-Shot 3D Anomaly Detection | Gang Li et.al | paper | - | <summary>detail</summary>Page 14 |
Multimodal Anomaly Detection
| Date | Title | Authors | Code | Comments | |
|---|---|---|---|---|---|
| 2026-5-31 | AnomSeer: Reinforcing Multimodal LLMs to Reason for Time-Series Anomaly Detection | Junru Zhang et.al | paper | - | <summary>detail</summary>ICML 2026 |
| 2026-5-18 | Are Multimodal LLMs Ready for Surveillance? A Reality Check on Zero-Shot Anomaly Detection in the Wild | Shanle Yao et.al | paper | - | - |
| 2026-5-18 | UTOPYA: A Multimodal Deep Learning Framework for Physics-Informed Anomaly Detection and Time-Series Prediction | Robson W. S. Pessoa et.al | paper | - | - |
| 2026-5-15 | Parameter Efficient Multi-Class Intelligent Scheduling for Multimodal Online Distributed Industrial Anomaly Detection | Heqiang Wang et.al | paper | - | - |
| 2026-5-7 | EAGLE: Expert-Augmented Attention Guidance for Tuning-Free Industrial Anomaly Detection in Multimodal Large Language Models | Xiaomeng Peng et.al | paper | - | - |
| 2026-4-24 | Text-Guided Multimodal Unified Industrial Anomaly Detection | Zewen Li et.al | paper | - | - |
| 2026-4-23 | Anomaly Detection in Smart Power Grids with Graph-Regularized MS-SVDD: a Multimodal Subspace Learning Approach | Thomas Debelle et.al | paper | - | - |
| 2026-4-20 | ZSG-IAD: A Multimodal Framework for Zero-Shot Grounded Industrial Anomaly Detection | Qiuhui Chen et.al | paper | - | - |
| 2026-4-14 | Out of Context: Reliability in Multimodal Anomaly Detection Requires Contextual Inference | Kevin Wilkinghoff et.al | paper | - | - |
| 2026-4-13 | MMR-AD: A Large-Scale Multimodal Dataset for Benchmarking General Anomaly Detection with Multimodal Large Language Models | Xincheng Yao et.al | paper | - | <summary>detail</summary>Accepted by CVPR2026 |
| 2026-4-10 | Multimodal Anomaly Detection for Human-Robot Interaction | Guilherme Ribeiro et.al | paper | - | - |
| 2026-4-7 | Reasoning-Guided Grounding: Elevating Video Anomaly Detection through Multimodal Large Language Models | Sakshi Agarwal et.al | paper | - | <summary>detail</summary>under review at conference |
| 2026-4-7 | SGANet: Semantic and Geometric Alignment for Multimodal Multi-view Anomaly Detection | Letian Bai et.al | paper | - | - |
| 2026-4-1 | VMAD: Visual-enhanced Multimodal Large Language Model for Zero-Shot Anomaly Detection | Huilin Deng et.al | paper | - | - |
| 2026-3-29 | Bidirectional Multimodal Prompt Learning with Scale-Aware Training for Few-Shot Multi-Class Anomaly Detection | Yujin Lee et.al | paper | - | <summary>detail</summary>accepted to CVPR 2026 |
| 2026-3-23 | Multimodal Industrial Anomaly Detection via Geometric Prior | Min Li et.al | paper | - | <summary>detail</summary>Accepted for publication in IEEE Transactions on Circuits and Systems for Video Technology (TCSVT) |
| 2026-3-23 | Towards Multimodal Time Series Anomaly Detection with Semantic Alignment and Condensed Interaction | Shiyan Hu et.al | paper | code | <summary>detail</summary>ICLR 2026 |
| 2026-3-23 | Exploring Multimodal Prompts For Unsupervised Continuous Anomaly Detection | Mingle Zhou et.al | paper | - | - |
| 2026-3-4 | Cross-Modal Mapping and Dual-Branch Reconstruction for 2D-3D Multimodal Industrial Anomaly Detection | Radia Daci et.al | paper | code | - |
| 2026-3-3 | Towards an Incremental Unified Multimodal Anomaly Detection: Augmenting Multimodal Denoising From an Information Bottleneck Perspective | Kaifang Long et.al | paper | - | - |
| 2026-2-26 | Leveraging Multimodal LLM Descriptions of Activity for Explainable Semi-Supervised Video Anomaly Detection | Furkan Mumcu et.al | paper | - | - |
| 2026-2-17 | Can Multimodal LLMs Perform Time Series Anomaly Detection? | Xiongxiao Xu et.al | paper | - | <summary>detail</summary>ACM Web Conference 2026 (WWW’26) |
| 2026-2-11 | Enhancing Weakly Supervised Multimodal Video Anomaly Detection through Text Guidance | Shengyang Sun et.al | paper | - | <summary>detail</summary>Accepted by IEEE Transactions on Multimedia |
| 2026-1-22 | VTFusion: A Vision-Text Multimodal Fusion Network for Few-Shot Anomaly Detection | Yuxin Jiang et.al | paper | - | - |
| 2026-1-20 | Physic-HM: Restoring Physical Generative Logic in Multimodal Anomaly Detection via Hierarchical Modulation | Xiao Liu et.al | paper | - | <summary>detail</summary>Working in progress |
Vector Quantization
| Date | Title | Authors | Code | Comments | |
|---|---|---|---|---|---|
| 2026-6-3 | RAVQ-HoloNet: Rate-Adaptive Vector-Quantized Hologram Compression | Shima Rafiei et.al | paper | - | - |
| 2026-6-1 | Channel-wise Vector Quantization | Wei Song et.al | paper | - | - |
| 2026-6-1 | Massive Spikes in LLMs are Bias Vectors: Mechanistic Uncovering and Spike-Free Quantization | Yung-Chin Chen et.al | paper | - | - |
| 2026-5-31 | Graph is a Natural Regularization: Revisiting Vector Quantization for Graph Representation Learning | Zian Zhai et.al | paper | - | <summary>detail</summary>ICML2026 |
| 2026-5-27 | ArcVQ-VAE: A Spherical Vector Quantization Framework with ArcCosine Additive Margin | Jaeyung Kim et.al | paper | code | <summary>detail</summary>To appear in Proceedings of the 43rd International Conference on Machine Learning (ICML 2026) |
| 2026-5-26 | DiVeQ: Differentiable Vector Quantization Using the Reparameterization Trick | Mohammad Hassan Vali et.al | paper | - | - |
| 2026-5-26 | Training-Free Vector Quantization via Gaussian VAEs | Tongda Xu et.al | paper | code | - |
| 2026-5-24 | BandVQ: Band-Wise Vector-Quantized EEG Foundation Model | Jamiyan Sukhbaatar et.al | paper | - | - |
| 2026-5-22 | EVA: Accelerating LLM Decoding via an Efficient Vector Quantization Architecture | Bowen Duan et.al | paper | code | - |
| 2026-5-22 | ProGIC: Progressive and Lightweight Generative Image Compression with Residual Vector Quantization | Hao Cao et.al | paper | - | <summary>detail</summary>Accepted by CVPR 2026 Findings |
| 2026-5-20 | Divide et Calibra: Multiclass Local Calibration via Vector Quantization | Cesare Barbera et.al | paper | - | - |
| 2026-5-20 | MGVQ: Synergizing Multi-dimensional Sensitivity-Aware and Gradient-Hessian Fusion for Vector Quantization | Zhong Wang et.al | paper | - | - |
| 2026-5-19 | Improving 3D Gaussian Splatting Compression by Scene-Adaptive Lattice Vector Quantization | Hao Xu et.al | paper | code | <summary>detail</summary>Accepted by IEEE TIP |
| 2026-5-19 | Block-Sphere Vector Quantization | Heesang Ann et.al | paper | - | - |
| 2026-5-14 | PrismQuant: Rate-Distortion-Optimal Vector Quantization for Gaussian-Mixture Sources | Bumsu Park et.al | paper | - | - |
| 2026-5-14 | Online Vector Quantized Attention | Nick Alonso et.al | paper | - | - |
| 2026-5-14 | RQ-MoE: Residual Quantization via Mixture of Experts for Efficient Input-Dependent Vector Compression | Zhengjia Zhong et.al | paper | code | <summary>detail</summary>To appear at ICML 2026 |
| 2026-5-13 | Vector-Quantized Discrete Latent Factors Meet Financial Priors: Dynamic Cross-Sectional Stock Ranking Prediction for Portfolio Construction | Namhyoung Kim et.al | paper | code | <summary>detail</summary>IJCAI 2026 Accepted Paper including Technical Appendix |
| 2026-5-11 | FibQuant: Universal Vector Quantization for Random-Access KV-Cache Compression | Namyoon Lee et.al | paper | - | - |
| 2026-5-5 | R3-VAE: Reference Vector-Guided Rating Residual Quantization VAE for Generative Recommendation | Qiang Wan et.al | paper | - | <summary>detail</summary>Tech Report |
| 2026-5-4 | Differentiable Vector Quantization for Rate-Distortion Optimization of Generative Image Compression | Shiyin Jiang et.al | paper | code | <summary>detail</summary>Accepted for publication at CVPR 2026 as an Oral presentation |
| 2026-4-30 | VQ-SAD: Vector Quantized Structure Aware Diffusion For Molecule Generation | Farshad Noravesh et.al | paper | - | - |
| 2026-4-25 | Efficient VQ-QAT and Mixed Vector/Linear quantized Neural Networks | Terry Gou et.al | paper | - | - |
| 2026-4-16 | Unsupervised Skeleton-Based Action Segmentation via Hierarchical Spatiotemporal Vector Quantization | Umer Ahmed et.al | paper | - | - |
| 2026-4-14 | SHARe-KAN: Post-Training Vector Quantization for Cache-Resident KAN Inference | Jeff Smith et.al | paper | - | - |