Daily Papers
- Defect Detection
- Defect Segmentation
- Anomaly Detection
- 3D Anomaly Detection
- Multimodal Anomaly Detection
- Vector Quantization
Updated on 2026.10.09
Defect Detection
| Date | Title | Authors | Code | Comments | |
|---|---|---|---|---|---|
| 2026-10-6 | Epistemic Uncertainty-Aware Defect Detection for Quality Control in Medical Device Manufacturing | Raham A. Butt et.al | paper | - | - |
| 2026-10-5 | Feature identification for parameter extraction and defect detection using machine learning | Yan Guo et.al | paper | - | - |
| 2026-10-3 | Detecting Defects that Matter: An Application-Driven Benchmark for Anomaly Detection in Manufacturing and Retail Logistics (VAND 4.0 Challenge) | Lars Heckler-Kram et.al | paper | code | - |
| 2026-9-24 | Industrial Anomaly Detection via Defect-Grounded Reasoning in Visual Latent Space | Jaron Yeh et.al | paper | code | - |
| 2026-9-23 | TEEP-RCNN: Texture-Enhanced Edge-aware Perception for Steel Surface Defect Detection via Improved Convolutional Block Attention in Faster R-CNN | Kirtan Rajesh et.al | paper | - | - |
| 2026-9-19 | Signal-Informed Temporal Routing for Vinyl Defect Regime Detection | Yi-Hung Kan et.al | paper | - | - |
| 2026-9-18 | What Remains Normal? Clean Images Miss Useful Near-Defect Normal Patches for Anomaly Detection | Joongwon Chae et.al | paper | code | - |
| 2026-9-10 | Positional task conditioning for scalable defect detection across product families in large product catalogs | Soham Satyadharma et.al | paper | - | - |
| 2026-9-7 | Explainable Temporal Attention-based Defect Detection For Fillet Joints in Real-Time Gas Metal Arc Welding Based on Multi-modal Data | Mobina Mobaraki et.al | paper | - | - |
| 2026-9-5 | Spatial Attention Supervision for Defect Localization: Exploiting Ground-Truth Masks as Training Signal in Diffusion-Augmented Defect Detection | Sajjad Rezvani Boroujeni et.al | paper | code | - |
| 2026-9-4 | Robust Online Aero-Engine Blade Defect Detection via Dual-Alignment Test-Time Adaptation | Zhaoyang Wang et.al | paper | - | <summary>detail</summary>This manuscript is conference PRCV 2026 |
| 2026-9-3 | ISP-AD: A Large-Scale Real-World Dataset for Advancing Industrial Anomaly Detection with Synthetic and Real Defects | Paul J. Krassnig et.al | paper | code | - |
| 2026-9-2 | FuDU: A Fuzzy Dual-dimensional Uncertainty Framework for Streaming Active Learning in Industrial Defect Detection | Zhaoyang Wang et.al | paper | code | <summary>detail</summary>ECCV 2026 |
| 2026-9-1 | When Agents Implement Systems: A Case Study in Defects, Detection, and Evaluation Rigor | Phanindra Reddy Madduru et.al | paper | - | - |
| 2026-9-1 | Integrated Laser Scanning and Image-Based Topology Optimization Techniques for Detection and Quantification of Visible and Subsurface Structural Defects | Mehrdad Shafiei Dizaji et.al | paper | - | <summary>detail</summary>9 |
| 2026-8-28 | CF-YOLO: Context-Aware Feature Refinement for Camouflaged Industrial Micro-Defect Detection | Xinda Yu et.al | paper | code | - |
| 2026-8-27 | ShiftSplit-AD: Separating Domain Shift from Defects in Foundation-Feature Visual Anomaly Detection | Muhamathu Ameer Ali Aacaas Muhamath et.al | paper | - | - |
| 2026-8-25 | Lowering the Barrier to AI-Driven Inspection: A No-Code Workflow for Automated Structural Defect Detection | Michael Holm et.al | paper | code | - |
| 2026-8-25 | When More References Hurt: Contamination-Aware DINOv2 Memory Banks for Few-Shot Steel Defect Detection | Hannaneh Kalantary et.al | paper | - | - |
| 2026-8-20 | AGIDefect-4K: A Richly Annotated Dataset for AI-Generated Image Defect Detection, Localization and Explanation | Xiangfei Sheng et.al | paper | code | - |
| 2026-8-18 | Continuity-Driven Representation Learning for Industrial Defect Detection | Minjong Kim et.al | paper | - | <summary>detail</summary>the British Machine Vision Conference (BMVC) 2026 |
| 2026-8-12 | Low Cost Two-Stage Fabric Defect Detection at the Edge | Rasel Hossen et.al | paper | - | - |
| 2026-8-9 | Keep the Needle, Prune the Haystack: Defect-Preserving Token Pruning for Efficient Zero-Shot Anomaly Detection | Yanning Hou et.al | paper | - | - |
| 2026-8-8 | Machine-Learning-Based Diagnostic Framework for Passive Ultrasonic Detection of Railway Wheel Defects | Aashish Shaju et.al | paper | - | <summary>detail</summary>Presented at the ASNT Research Symposium 2026 |
| 2026-7-30 | BladeYOLO: Wind Turbine Blade Defect Detection with Limited Annotations and Weak-Saliency Awareness | Yabin Xu et.al | paper | code | <summary>detail</summary>IEEE TGRS |
Defect Segmentation
| Date | Title | Authors | Code | Comments | |
|---|---|---|---|---|---|
| 2026-9-29 | DCM-SAM: Defect-Conditioned Mixture of LoRA Experts for NPU-Deployed AM Defect Segmentation | Md Mushfiqur Rahaman et.al | paper | code | - |
| 2026-9-18 | P$^3$-SAM: SAM with Perceptual Parallel Prompt for Few-Shot Strip Steel Surface Defect Segmentation | Qian Xu et.al | paper | - | <summary>detail</summary>Accepted by ICME 2026 |
| 2026-8-31 | SAM3-LoRA: Parameter-Efficient Adaptation of a Concept-Promptable Foundation Model for Multi-Class Structural Defect Segmentation | P. Malaisree et.al | paper | - | - |
| 2026-8-31 | SePArate: Segmenting Patterns from Defects in Wafer Manufacturing Using Weak Supervision | Dain Kwon et.al | paper | - | - |
| 2026-7-23 | SPDCN: Strip-based Deformable Convolutional Network for Steel Surface Defect Segmentation | Zhongming Liu et.al | paper | code | - |
| 2026-7-15 | XCT-SAM: Sequential Parameter-Efficient Domain Adaptation of SAM for Industrial XCT Defect Segmentation | Md Mahedi Hasan et.al | paper | code | - |
| 2026-7-2 | Defect-aware Hybrid Prompt Optimization via Progressive Tuning for Zero-Shot Multi-type Anomaly Detection and Segmentation | Nadeem Nazer et.al | paper | - | <summary>detail</summary>Journal ref:European Conference on Computer Vision (ECCV 2026) |
| 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 | - | - |
| 2026-1-22 | 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 | - | - |
Anomaly Detection
| Date | Title | Authors | Code | Comments | |
|---|---|---|---|---|---|
| 2026-10-8 | RIFT: Relative Isolation From Trees For Anomaly Detection | Mark Daniel Szalai et.al | paper | - | - |
| 2026-10-8 | Is Real-World Training Data Necessary for Generalist Graph Anomaly Detection? | Yujing Liu et.al | paper | - | - |
| 2026-10-8 | Onboard Marine Anomaly Detection on $Φ$sat-2: From Simulation-Based Development to In-Orbit Demonstration | Clotilde Szywala et.al | paper | - | - |
| 2026-10-7 | A Unified Score Matching Paradigm for Video Anomaly Detection and Anticipation | Congqi Cao et.al | paper | - | - |
| 2026-10-7 | Adaptive Anomaly Detection in the Presence of Concept Drift: Extended Report | Jongjun Park et.al | paper | - | <summary>detail</summary>Extended version (to be updated) |
| 2026-10-7 | Efficient Patch-Based Anomaly Detection Fused with Diffusion Driven Generative Modeling for Semiconductor Wafer Bin Map Open Set Anomaly Detection | Limon Bin Hossain et.al | paper | - | - |
| 2026-10-7 | Pareto-optimal quantum kernel selection for unsupervised anomaly detection on real malware beaconing data | Boaz Micah et.al | paper | - | - |
| 2026-10-7 | A Multi-Source Ultrasound Benchmark Revealing the Limits of Contemporary Self-Supervised Anomaly Detection Methods | Marco Riedenauer et.al | paper | - | - |
| 2026-10-7 | Quasi-Binarized Autoencoders: An Architecture-Independent Information Bottleneck for Medical Image Anomaly Detection | Shouhei Hanaoka et.al | paper | code | - |
| 2026-10-7 | Quantum anomaly detection in real scarce data | Emanuele Casciaro et.al | paper | - | - |
| 2026-10-7 | Temporal transformer CAN encoder with federated lightweight heads for anomaly detection | Konstantinos Gyftodimos et.al | paper | - | <summary>detail</summary>Journal ref:Presented at ITS European Congress 2025 |
| 2026-10-7 | MORA: Modeling Observed Changes for Drift-Robust Time-Series Anomaly Detection | Xudong Mou et.al | paper | - | - |
| 2026-10-6 | GRC-Net: Global Representation Consistency Network for Unsupervised Multimodal Anomaly Detection | Seyoung Jeong et.al | paper | - | - |
| 2026-10-5 | Adapting prior-data fitted networks for tabular anomaly detection | Maximilian Bershtman et.al | paper | - | <summary>detail</summary>Submitted for a review to ICLR 2027 |
| 2026-10-5 | Detecting Nighttime Anomalies from NASA Black Marble Using a Generalized Spatio-Temporally Robust Framework of Machine Leaning Ensembles | Srija Chakraborty et.al | paper | - | - |
| 2026-10-5 | Normality Constraint Learning: Adapting Foundation Models for Time Series Anomaly Detection | Xiaohui Zhou et.al | paper | - | - |
| 2026-10-5 | Anlu: Enabling In-Context Time Series Anomaly Detection in Foundation Models via Counterfactual Supervision | Tian Lan et.al | paper | - | - |
| 2026-10-5 | OCSVM-Guided Representation Learning for Unsupervised Anomaly Detection | Nicolas Pinon et.al | paper | code | - |
| 2026-10-5 | Lightweight CNN-Based Anomaly Detection for High Voltage Converter Modulators in the Spallation Neutron Source | Alberto D. Cencillo et.al | paper | - | - |
| 2026-10-5 | Adaptive-Shot Hybrid Quantum Anomaly Detection for Tactile Internet Security: Reliability-Aware Measurement Allocation Under Resource Constraints | Mubassir Serneabat Sudipto et.al | paper | code | <summary>detail</summary>the 40th Conference on Neural Information Processing Systems (NeurIPS 2026) |
| 2026-10-5 | Protocol-Sensitive Evaluation of Log Anomaly Detection: Component Costs and Target-Access Sensitivity on HDFS and BGL | Hang Xiao et.al | paper | code | <summary>detail</summary>DASC 2026 |
| 2026-10-4 | Anchor and Adapt: Asymmetric Prompt Adaptation for Few-Shot Industrial Anomaly Detection | Mengyang Zhao et.al | paper | - | - |
| 2026-10-4 | RoMod: Temporal Routing Modulation via Mixture-of-Experts for Video Anomaly Detection | Chao Huang et.al | paper | - | - |
| 2026-10-4 | Representation–Behavior Alignment for Explainable Weakly-Supervised Video Anomaly Detection | Chao Huang et.al | paper | - | - |
| 2026-10-4 | MedAD-R1: Consistency-Reinforced Policy Optimization for Interpretable Medical Anomaly Detection | Haitao Zhang et.al | paper | code | <summary>detail</summary>Revised manuscript with an updated title |
3D Anomaly Detection
| Date | Title | Authors | Code | Comments | |
|---|---|---|---|---|---|
| 2026-9-28 | Towards Generalizable 3D Anomaly Detection via Relational Inconsistency Modeling | KunHo Heo et.al | paper | code | <summary>detail</summary>Accepted by NeurIPS 2026 |
| 2026-9-27 | Beyond Geometry: Benchmarking and Consistency Reasoning for 3D Logical Anomaly Detection | Zhiqiang Qin et.al | paper | - | - |
| 2026-9-22 | AT3D-AD: Anomaly Type-Aware 3D Anomaly Detection via Hierarchical Point-Language Alignment | Jingyu Zeng et.al | paper | - | - |
| 2026-9-13 | PC$^2$-AD: Point Cloud Upsampling to Safeguard 3D Anomaly Detection with Resolution-constrained Edge Devices | Yutong Gu et.al | paper | code | - |
| 2026-8-12 | MVFM-3DAD: Multi-view Flow Matching for 3D Anomaly Detection via Density Proxy Estimation | Liangwei Li et.al | paper | code | <summary>detail</summary>ICIG 2026 oral presentation |
| 2026-7-15 | M2P-AD: Memory-to-Prototype Learning with Boundary-aware Score Refinement for 3D Anomaly Detection | Seyoung Jeong et.al | paper | - | - |
| 2026-7-12 | Back to Point: Exploring Point-Language Models for Zero-Shot 3D Anomaly Detection | Kaiqiang Li et.al | paper | code | <summary>detail</summary>CVPR 2026 |
| 2026-7-11 | Physics-inspired Pseudo Anomaly Generation and Prototype Feature Guidance for 3D Anomaly Detection | Jian Ning et.al | paper | code | - |
| 2026-7-6 | DDStereo: Efficient Dual Decoder Transformers for Stereo 3D Road Anomaly Detection | Shiyi Mu et.al | paper | code | <summary>detail</summary>Accepted by ECCV2026 |
| 2026-6-27 | Anomaly Factory 3D: A Modular Framework for Diverse Pseudo-Anomaly Synthesis in Unsupervised 3D Anomaly Detection | Ali Balapour et.al | paper | - | - |
| 2026-6-24 | Point Cloud Diffusion with Global and Local Reconstruction for Instance-Level 3D Anomaly Detection | Linchun Wu et.al | paper | - | - |
| 2026-6-23 | CoGeoAD: Hierarchical Color-Geometric Fusion with Multi-View Attention for Zero-Shot 3D Anomaly Detection | Ke Xu et.al | paper | code | <summary>detail</summary>ICML 2026 |
| 2026-6-17 | Toward Training-Free Zero-Shot Anomaly Detection in 3D Medical Images: A Batch-Based Approach Using 2D Foundation Models | Tai Le-Gia et.al | paper | - | <summary>detail</summary>ACM Class:I |
| 2026-6-5 | Automated 3D Kinematic Monitoring for Circadian Activity and Anomaly Detection in Juvenile Fish | Chih-Wei Huang et.al | paper | - | - |
| 2026-6-2 | VT-3DAD: Cross-Category 3D Anomaly Detection via Visual-Text Normal Space Alignment | Zi Wang et.al | paper | - | - |
| 2026-5-25 | 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 |
Multimodal Anomaly Detection
| Date | Title | Authors | Code | Comments | |
|---|---|---|---|---|---|
| 2026-10-6 | GRC-Net: Global Representation Consistency Network for Unsupervised Multimodal Anomaly Detection | Seyoung Jeong et.al | paper | - | - |
| 2026-9-22 | Confidence-Guided Cross-Modal Knowledge Transfer for Multimodal Anomaly Detection in Microservice Systems | Peipeng Wang et.al | paper | - | - |
| 2026-9-22 | When Point Clouds Outperform Pixels: Rethinking Zero-Shot Multimodal Anomaly Detection | Chenglin Ye et.al | paper | - | - |
| 2026-9-8 | AD-FM: Multimodal LLMs for Anomaly Detection via Multi-Stage Reasoning and Fine-Grained Reward Optimization | Jingyi Liao et.al | paper | - | - |
| 2026-8-14 | Rethinking Auxiliary Modalities in Multimodal Zero-shot Anomaly Detection: From Semantic Fusion to Conditional Modulation | Peng Wu et.al | paper | - | - |
| 2026-8-9 | Agentic Anomaly Detection with ORCA-Style Dynamic Inductive Bias Adaptation in Multimodal Wearable Time Series Data | Anushka Roy et.al | paper | - | - |
| 2026-8-9 | Modeling Normal Is All You Need: Joint Latent Clustering for Anomaly Detection in Multimodal Cyber-Physical Systems | Alexander Apartsin et.al | paper | - | - |
| 2026-8-8 | LIBAD: A Multimodal Anomaly Detection Benchmark for Li-Ion Battery Electrode Manufacturing | Wenbo Sui et.al | paper | - | - |
| 2026-8-2 | Understanding and Overcoming Cross-modal Fusion Bias in Multimodal Anomaly Detection From A Fisher Information Perspective | Kaifang Long et.al | paper | - | - |
| 2026-7-31 | ReMoE: Report-Guided Mixture-of-Experts for Multimodal OCT/OCTA Anomaly Detection | Zihan Nie et.al | paper | - | - |
| 2026-7-29 | OmniAD: Detect and Understand Industrial Anomaly via Multimodal Reasoning | Shifang Zhao et.al | paper | - | - |
| 2026-7-13 | TC-MAF: Train-Calibrated Bounded Multi-Evidence Fusion for Multimodal Industrial Anomaly Detection | Ming Deng et.al | paper | code | <summary>detail</summary>accepted by ACM MM 2026 |
| 2026-7-7 | Tuned Reverse Distillation: Enhancing Multimodal Industrial Anomaly Detection with Crossmodal Tuners | Xinyue Liu et.al | paper | code | <summary>detail</summary>Accepted by TMM |
| 2026-7-4 | Global Logic and Local Search: Dual-Stream Multimodal In-Context Learning for Verifiable Industrial Anomaly Detection | Runzhi Deng et.al | paper | - | <summary>detail</summary>Accepted by ECCV 2026 |
| 2026-7-2 | CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection | Wen Dong et.al | paper | code | - |
| 2026-6-26 | RobustMAD: Evaluating Real-World Robustness of Multimodal Small Language Models for Deployable Anomaly Detection Assistants | Anushiya Arunan et.al | paper | code | <summary>detail</summary>Accepted for publication in Transactions on Machine Learning Research (TMLR) |
| 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 | - | - |
Vector Quantization
| Date | Title | Authors | Code | Comments | |
|---|---|---|---|---|---|
| 2026-10-6 | Tree-VQ: Progressive Image Compression from Pretrained Vector Quantizers | Mingming Ma et.al | paper | - | - |
| 2026-10-1 | FedFit: Federated Fine-Tuning of LLMs via Vector-Bank Parameterization and Quantization | Hang Zou et.al | paper | - | - |
| 2026-9-30 | Spatial Strategies, Not Actions: Vector-Quantized Geodesics as Tools for LLM-Driven Agents | Gabriel Turinici et.al | paper | - | <summary>detail</summary>MSC Class:68T05 |
| 2026-9-29 | Task-Oriented Visual Feature Compression via Residual Vector Quantization for Device-Edge Multimodal Inference | Luning Pang et.al | paper | - | - |
| 2026-9-28 | Dual-Branch Vector-Quantization-Aided Satellite Digital Semantic Communication with Index Compression for High-Resolution RSI Over AFDM | Jianqiao Chen et.al | paper | - | - |
| 2026-9-28 | SSTQ:Privacy-Preserving Vector Quantization via Subsampled Stochastic TurboQuant | Adel Javanmard et.al | paper | - | - |
| 2026-9-27 | Pushing Toward the Simplex Vertices: A Simple Remedy for Code Collapse in Smoothed Vector Quantization | Takashi Morita et.al | paper | - | - |
| 2026-9-24 | VQ-LIC: Shared Vector-Quantized Learned Image Compression on a Resource-Constrained FPGA | Muhammad Fahd Ibrahim Bhatti et.al | paper | - | - |
| 2026-9-22 | StableVQ: Practical Guidelines for Stable Vector-Quantized Tokenizer Training | Bao Tang et.al | paper | code | <summary>detail</summary>Project page: https://tt-day |
| 2026-9-17 | VQ-Logits: Compressing the Output Bottleneck of Large Language Models via Vector Quantized Logits | Jintian Shao et.al | paper | - | <summary>detail</summary>Lack of sufficient experiments and detailed format alignment |
| 2026-9-15 | Prior-Aided Masked Vector Quantization CSI Feedback for FDD Massive MIMO Systems | Yi Song et.al | paper | - | - |
| 2026-9-10 | LC-QAT: Data-Efficient 2-Bit QAT for LLMs via Linear-Constrained Vector Quantization | Haoyu Wang et.al | paper | code | <summary>detail</summary>Accepted by ICML 2026 |
| 2026-9-9 | When Does Low-Bit Quantization Preserve the Decisions of Vector Search? | Wenxuan Xiao et.al | paper | - | <summary>detail</summary>JMLR-style preprint with theoretical and experimental appendices |
| 2026-9-4 | SeRV: Semantic-Aligned Residual Vector Quantization for American Sign Language Generation | Hongyu Wu et.al | paper | - | - |
| 2026-9-3 | PACodec: A Low-bitrate Neural Speech Codec with Parallel Additive Vector Quantization | Fei Liu et.al | paper | - | <summary>detail</summary>Accepted by APSIPA 2026 |
| 2026-9-2 | A Unified Rate-Distortion Perspective on Vector, Product, and Scalar Quantization | Xianghong Fang et.al | paper | - | - |
| 2026-8-31 | RSLM: Training-Free Vector Quantization for Approximate Nearest Neighbor Search | Rastislav Lenhardt et.al | paper | - | <summary>detail</summary>14 Pages |
| 2026-8-24 | ASH: Asymmetric Scalar Hashing With Learned Dimensionality Reduction for High-Fidelity Vector Quantization | Mariano Tepper et.al | paper | - | <summary>detail</summary>CIKM 2026 |
| 2026-8-11 | Bandwidth-Efficient Multi-Agent Communication through Information Bottleneck and Vector Quantization | Ahmad Farooq et.al | paper | - | <summary>detail</summary>IEEE ICRA 2026 |
| 2026-8-11 | GranQ: Efficient Channel-wise Quantization via Vectorized Pre-Scaling for Zero-Shot QAT | Inpyo Hong et.al | paper | - | <summary>detail</summary>ACM SAC 2026 |
| 2026-8-5 | VQ-VAD: Vector-quantized Motion Representation Learning for Human-centric Video Anomaly Detection | Narges Rashvand et.al | paper | code | - |
| 2026-8-4 | Spend Bits Where Queries Look: KV Cache Vector Quantization with Attention-Preserving Transforms | Samuel Fernández-Menduiña et.al | paper | - | - |
| 2026-7-31 | Distributional Matching for Vector Quantization: A Unified Theoretical and Empirical Framework | Xianghong Fang et.al | paper | - | - |
| 2026-7-31 | VQ-bench: A Composable Vector Quantization Framework | Ashwin Padaki et.al | paper | - | <summary>detail</summary>Results available on www |
| 2026-7-30 | FairDiffuseVQVAE: Sampling-Time Fairness in Tabular Diffusion via Conditional Refinement of Vector-Quantized Latents | Nitish Nagesh et.al | paper | - | - |