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Update papers from 2026-01-19 to 2026-01-26 and set config start_date for future updates
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‎README.md‎

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![paper-list](https://github.com/isLinXu/issues/assets/59380685/dbd27f25-e7d7-4a0f-bdc2-d9b06fc03a2e)![GitHub stars](https://img.shields.io/github/stars/isLinXu/paper-list)![GitHub forks](https://img.shields.io/github/forks/isLinXu/paper-list)![GitHub watchers](https://img.shields.io/github/watchers/isLinXu/paper-list)[![Build Status](https://img.shields.io/endpoint.svg?url=https%3A%2F%2Factions-badge.atrox.dev%2Fatrox%2Fsync-dotenv%2Fbadge&style=flat)](https://github.com/isLinXu/paper-list)![img](https://badgen.net/badge/icon/learning?icon=deepscan&label)![GitHub repo size](https://img.shields.io/github/repo-size/isLinXu/paper-list.svg?style=flat-square)![GitHub language count](https://img.shields.io/github/languages/count/isLinXu/paper-list)![GitHub last commit](https://img.shields.io/github/last-commit/isLinXu/paper-list)![GitHub](https://img.shields.io/github/license/isLinXu/paper-list.svg?style=flat-square)![img](https://hits.dwyl.com/isLinXu/paper-list.svg)<p align="center"><h1 align="center"><br><ins>Paper-List-DAILY</ins><br>Automatically Update Papers Daily in list</h1></p>
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## Updated on 2026.01.19
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## Updated on 2026.01.26
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![paper_list](https://github.com/isLinXu/issues/assets/59380685/0ab31126-9ef4-4c49-bf80-8dae2a3acaa8)
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‎config.yaml‎

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# TODO: add papers by configuration file
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start_date: "2026-01-05"
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start_date: "2026-01-19"
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end_date: null
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base_url: "https://arxiv.paperswithcode.com/api/v0/papers/"
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user_name: "isLinXu"

‎docs/Action_Recognition.md‎

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|Publish Date|Title|Authors|PDF|Code|
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|---|---|---|---|---|
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|**2026-01-23**|**Affinity Contrastive Learning for Skeleton-based Human Activity Understanding**|Hongda Liu et.al.|[2601.16694](https://arxiv.org/abs/2601.16694)|null|
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|**2026-01-23**|**Low-Power On-Device Gesture Recognition with Einsum Networks**|Sahar Golipoor et.al.|[2601.16662](https://arxiv.org/abs/2601.16662)|null|
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|**2026-01-22**|**Angle of Arrival Estimation for Gesture Recognition from reflective body-worn tags**|Sahar Golipoor et.al.|[2601.16303](https://arxiv.org/abs/2601.16303)|null|
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|**2026-01-22**|**Gesture Recognition from body-Worn RFID under Missing Data**|Sahar Golipoor et.al.|[2601.16301](https://arxiv.org/abs/2601.16301)|null|
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|**2026-01-22**|**GameTalk: Training LLMs for Strategic Conversation**|Victor Conchello Vendrell et.al.|[2601.16276](https://arxiv.org/abs/2601.16276)|null|
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|**2026-01-22**|**Why Can't I Open My Drawer? Mitigating Object-Driven Shortcuts in Zero-Shot Compositional Action Recognition**|Geo Ahn et.al.|[2601.16211](https://arxiv.org/abs/2601.16211)|null|
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|**2026-01-22**|**PyraTok: Language-Aligned Pyramidal Tokenizer for Video Understanding and Generation**|Onkar Susladkar et.al.|[2601.16210](https://arxiv.org/abs/2601.16210)|null|
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|**2026-01-22**|**Decoupling Return-to-Go for Efficient Decision Transformer**|Yongyi Wang et.al.|[2601.15953](https://arxiv.org/abs/2601.15953)|null|
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|**2026-01-20**|**Curriculum-Based Strategies for Efficient Cross-Domain Action Recognition**|Emily Kim et.al.|[2601.14101](https://arxiv.org/abs/2601.14101)|null|
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|**2026-01-20**|**Two-Stream temporal transformer for video action classification**|Nattapong Kurpukdee et.al.|[2601.14086](https://arxiv.org/abs/2601.14086)|null|
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|**2026-01-20**|**Unsupervised Video Class-Incremental Learning via Deep Embedded Clustering Management**|Nattapong Kurpukdee et.al.|[2601.14069](https://arxiv.org/abs/2601.14069)|null|
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|**2026-01-20**|**Variational Dual-path Attention Network for CSI-Based Gesture Recognition**|N. Zhang et.al.|[2601.13745](https://arxiv.org/abs/2601.13745)|null|
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|**2026-01-20**|**GeoDynamics: A Geometric State-Space Neural Network for Understanding Brain Dynamics on Riemannian Manifolds**|Tingting Dan et.al.|[2601.13570](https://arxiv.org/abs/2601.13570)|null|
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|**2026-01-19**|**Dynamic Hand Gesture Recognition for Robot Manipulator Tasks**|Dharmendra Sharma et.al.|[2601.12918](https://arxiv.org/abs/2601.12918)|null|
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|**2026-01-15**|**Effects of Different Attention Mechanisms Applied on 3D Models in Video Classification**|Mohammad Rasras et.al.|[2601.10854](https://arxiv.org/abs/2601.10854)|null|
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|**2026-01-15**|**Can Vision-Language Models Understand Construction Workers? An Exploratory Study**|Hieu Bui et.al.|[2601.10835](https://arxiv.org/abs/2601.10835)|null|
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|**2026-01-11**|**Explore with Long-term Memory: A Benchmark and Multimodal LLM-based Reinforcement Learning Framework for Embodied Exploration**|Sen Wang et.al.|[2601.10744](https://arxiv.org/abs/2601.10744)|null|

‎docs/Anomaly_Detection.md‎

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|Publish Date|Title|Authors|PDF|Code|
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|**2026-01-23**|**Latent Diffusion for Internet of Things Attack Data Generation in Intrusion Detection**|Estela Sánchez-Carballo et.al.|[2601.16976](https://arxiv.org/abs/2601.16976)|null|
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|**2026-01-23**|**VTFusion: A Vision-Text Multimodal Fusion Network for Few-Shot Anomaly Detection**|Yuxin Jiang et.al.|[2601.16381](https://arxiv.org/abs/2601.16381)|null|
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|**2026-01-22**|**TempoNet: Learning Realistic Communication and Timing Patterns for Network Traffic Simulation**|Kristen Moore et.al.|[2601.15663](https://arxiv.org/abs/2601.15663)|null|
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|**2026-01-22**|**Machine Failure Detection Based on Projected Quantum Models**|Larry Bowden et.al.|[2601.15641](https://arxiv.org/abs/2601.15641)|null|
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|**2026-01-21**|**DevPrompt: Deviation-Based Prompt Learning for One-Normal ShotImage Anomaly Detection**|Morteza Poudineh et.al.|[2601.15453](https://arxiv.org/abs/2601.15453)|null|
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|**2026-01-21**|**Lightweight LLMs for Network Attack Detection in IoT Networks**|Piyumi Bhagya Sudasinghe et.al.|[2601.15269](https://arxiv.org/abs/2601.15269)|null|
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|**2026-01-21**|**Dynamic Management of a Deep Learning-Based Anomaly Detection System for 5G Networks**|Lorenzo Fernández Maimó et.al.|[2601.15177](https://arxiv.org/abs/2601.15177)|null|
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|**2026-01-21**|**A Real-Time Error Prevention System for Gaze-Based Interaction in Virtual Reality Based on Anomaly Detection**|Björn R. Severitt et.al.|[2601.15146](https://arxiv.org/abs/2601.15146)|null|
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|**2026-01-21**|**Central subspace data depth**|Giacomo Francisci et.al.|[2601.14947](https://arxiv.org/abs/2601.14947)|null|
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|**2026-01-20**|**AI Agents vs. Human Investigators: Balancing Automation, Security, and Expertise in Cyber Forensic Analysis**|Sneha Sudhakaran et.al.|[2601.14544](https://arxiv.org/abs/2601.14544)|null|
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|**2026-01-20**|**Log anomaly detection via Meta Learning and Prototypical Networks for Cross domain generalization**|Krishna Sharma et.al.|[2601.14336](https://arxiv.org/abs/2601.14336)|null|
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|**2026-01-20**|**CREATE: Cross-Layer Resilience Characterization and Optimization for Efficient yet Reliable Embodied AI Systems**|Tong Xie et.al.|[2601.14140](https://arxiv.org/abs/2601.14140)|null|
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|**2026-01-20**|**AttackMate: Realistic Emulation and Automation of Cyber Attack Scenarios Across the Kill Chain**|Max Landauer et.al.|[2601.14108](https://arxiv.org/abs/2601.14108)|null|
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|**2026-01-20**|**Vision Also You Need: Navigating Out-of-Distribution Detection with Multimodal Large Language Model**|Haoran Xu et.al.|[2601.14052](https://arxiv.org/abs/2601.14052)|null|
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|**2026-01-20**|**Prospecting MeerKAT Continuum Data for Enigmatic Radio Sources with Unsupervised Vector-Quantised Variational Autoencoders**|Fernando L. Ventura et.al.|[2601.13901](https://arxiv.org/abs/2601.13901)|null|
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|**2026-01-20**|**Intelligent Distributed Optical Fiber Sensing in Transportation Infrastructures: Research Progress, Applications, and Challenges**|Xin Gui et.al.|[2601.13891](https://arxiv.org/abs/2601.13891)|null|
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|**2026-01-20**|**Enhanced Cyber Threat Intelligence by Network Forensic Analysis for Ransomware as a Service(RaaS) Malwares**|Sharmila S P et.al.|[2601.13873](https://arxiv.org/abs/2601.13873)|null|
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|**2026-01-20**|**ChauBoxplot and AdaptiveBoxplot: two R packages for boxplot-based outlier detection**|Tiejun Tong et.al.|[2601.13759](https://arxiv.org/abs/2601.13759)|null|
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|**2026-01-20**|**Towards Token-Level Text Anomaly Detection**|Yang Cao et.al.|[2601.13644](https://arxiv.org/abs/2601.13644)|null|
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|**2026-01-20**|**ChatAD: Reasoning-Enhanced Time-Series Anomaly Detection with Multi-Turn Instruction Evolution**|Hui Sun et.al.|[2601.13546](https://arxiv.org/abs/2601.13546)|null|
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|**2026-01-19**|**Analyzing VLM-Based Approaches for Anomaly Classification and Segmentation**|Mohit Kakda et.al.|[2601.13440](https://arxiv.org/abs/2601.13440)|null|
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|**2026-01-19**|**Diffusion-Driven Synthetic Tabular Data Generation for Enhanced DoS/DDoS Attack Classification**|Aravind B et.al.|[2601.13197](https://arxiv.org/abs/2601.13197)|null|
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|**2026-01-19**|**PrivFly: A Privacy-Preserving Self-Supervised Framework for Rare Attack Detection in IoFT**|Safaa Menssouri et.al.|[2601.13003](https://arxiv.org/abs/2601.13003)|null|
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|**2026-01-19**|**PDFInspect: A Unified Feature Extraction Framework for Malicious Document Detection**|Sharmila S P et.al.|[2601.12866](https://arxiv.org/abs/2601.12866)|null|
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|**2026-01-19**|**Knowledge-Integrated Representation Learning for Crypto Anomaly Detection under Extreme Label Scarcity; Relational Domain-Logic Integration with Retrieval-Grounded Context and Path-Level Explanations**|Gyuyeon Na et.al.|[2601.12839](https://arxiv.org/abs/2601.12839)|null|
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|**2026-01-19**|**A Graph Prompt Fine-Tuning Method for WSN Spatio-Temporal Correlation Anomaly Detection**|Miao Ye et.al.|[2601.12745](https://arxiv.org/abs/2601.12745)|null|
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|**2026-01-19**|**Empowering All-in-Loop Health Management of Spacecraft Power System in the Mega-Constellation Era via Human-AI Collaboration**|Yi Di et.al.|[2601.12667](https://arxiv.org/abs/2601.12667)|null|
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|**2026-01-19**|**Toward Faithful Explanations in Acoustic Anomaly Detection**|Maab Elrashid et.al.|[2601.12660](https://arxiv.org/abs/2601.12660)|null|
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|**2026-01-16**|**QUPID: A Partitioned Quantum Neural Network for Anomaly Detection in Smart Grid**|Hoang M. Ngo et.al.|[2601.11500](https://arxiv.org/abs/2601.11500)|null|
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|**2026-01-16**|**FTDMamba: Frequency-Assisted Temporal Dilation Mamba for Unmanned Aerial Vehicle Video Anomaly Detection**|Cheng-Zhuang Liu et.al.|[2601.11254](https://arxiv.org/abs/2601.11254)|null|
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|**2026-01-16**|**Assesing the Viability of Unsupervised Learning with Autoencoders for Predictive Maintenance in Helicopter Engines**|P. Sánchez et.al.|[2601.11154](https://arxiv.org/abs/2601.11154)|null|

‎docs/Audio_Processing.md‎

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|**2026-01-22**|**TidyVoice: A Curated Multilingual Dataset for Speaker Verification Derived from Common Voice**|Aref Farhadipour et.al.|[2601.16358](https://arxiv.org/abs/2601.16358)|null|
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|**2026-01-21**|**Test-Time Adaptation for Speech Emotion Recognition**|Jiaheng Dong et.al.|[2601.16240](https://arxiv.org/abs/2601.16240)|null|
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|**2026-01-20**|**SoundBreak: A Systematic Study of Audio-Only Adversarial Attacks on Trimodal Models**|Aafiya Hussain et.al.|[2601.16231](https://arxiv.org/abs/2601.16231)|null|
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|**2026-01-22**|**Pay (Cross) Attention to the Melody: Curriculum Masking for Single-Encoder Melodic Harmonization**|Maximos Kaliakatsos-Papakostas et.al.|[2601.16150](https://arxiv.org/abs/2601.16150)|null|
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|**2026-01-22**|**Quantum Dimension Reduction of Hidden Markov Models**|Rishi Sundar et.al.|[2601.16126](https://arxiv.org/abs/2601.16126)|null|
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|**2026-01-22**|**Distillation-based Layer Dropping (DLD) Effective End-to-end Framework for Dynamic Speech Networks**|Abdul Hannan et.al.|[2601.16117](https://arxiv.org/abs/2601.16117)|null|
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|**2026-01-22**|**Timbre-Aware LLM-based Direct Speech-to-Speech Translation Extendable to Multiple Language Pairs**|Lalaram Arya et.al.|[2601.16023](https://arxiv.org/abs/2601.16023)|null|
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|**2026-01-22**|**PF-D2M: A Pose-free Diffusion Model for Universal Dance-to-Music Generation**|Jaekwon Im et.al.|[2601.15872](https://arxiv.org/abs/2601.15872)|null|
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|**2026-01-22**|**U3-xi: Pushing the Boundaries of Speaker Recognition via Incorporating Uncertainty**|Junjie Li et.al.|[2601.15719](https://arxiv.org/abs/2601.15719)|null|
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|**2026-01-22**|**DeepASMR: LLM-Based Zero-Shot ASMR Speech Generation for Anyone of Any Voice**|Leying Zhang et.al.|[2601.15596](https://arxiv.org/abs/2601.15596)|null|
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|**2026-01-20**|**Lost in Transcription: How Speech-to-Text Errors Derail Code Understanding**|Jayant Havare et.al.|[2601.15339](https://arxiv.org/abs/2601.15339)|null|
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|**2026-01-21**|**Deaf and Hard of Hearing Access to Intelligent Personal Assistants: Comparison of Voice-Based Options with an LLM-Powered Touch Interface**|Paige S. DeVries et.al.|[2601.15209](https://arxiv.org/abs/2601.15209)|null|
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|**2026-01-21**|**Training-Efficient Text-to-Music Generation with State-Space Modeling**|Wei-Jaw Lee et.al.|[2601.14786](https://arxiv.org/abs/2601.14786)|null|
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|**2026-01-21**|**Inverse-Hessian Regularization for Continual Learning in ASR**|Steven Vander Eeckt et.al.|[2601.14751](https://arxiv.org/abs/2601.14751)|null|
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|**2026-01-21**|**Triage knowledge distillation for speaker verification**|Ju-ho Kim et.al.|[2601.14699](https://arxiv.org/abs/2601.14699)|null|
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|**2026-01-21**|**Dissecting Performance Degradation in Audio Source Separation under Sampling Frequency Mismatch**|Kanami Imamura et.al.|[2601.14684](https://arxiv.org/abs/2601.14684)|null|
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|**2026-01-20**|**Prosody-Guided Harmonic Attention for Phase-Coherent Neural Vocoding in the Complex Spectrum**|Mohammed Salah Al-Radhi et.al.|[2601.14472](https://arxiv.org/abs/2601.14472)|null|
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|**2026-01-20**|**Quantifying Speaker Embedding Phonological Rule Interactions in Accented Speech Synthesis**|Thanathai Lertpetchpun et.al.|[2601.14417](https://arxiv.org/abs/2601.14417)|null|
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|**2026-01-20**|**DAME: Duration-Aware Matryoshka Embedding for Duration-Robust Speaker Verification**|Youngmoon Jung et.al.|[2601.13999](https://arxiv.org/abs/2601.13999)|null|
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|**2026-01-20**|**Stream-Voice-Anon: Enhancing Utility of Real-Time Speaker Anonymization via Neural Audio Codec and Language Models**|Nikita Kuzmin et.al.|[2601.13948](https://arxiv.org/abs/2601.13948)|null|
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|**2026-01-20**|**Habibi: Laying the Open-Source Foundation of Unified-Dialectal Arabic Speech Synthesis**|Yushen Chen et.al.|[2601.13802](https://arxiv.org/abs/2601.13802)|null|
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|**2026-01-20**|**S $^2$ Voice: Style-Aware Autoregressive Modeling with Enhanced Conditioning for Singing Style Conversion**|Ziqian Wang et.al.|[2601.13629](https://arxiv.org/abs/2601.13629)|null|
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|**2026-01-19**|**The Achilles' Heel of Angular Margins: A Chebyshev Polynomial Fix for Speaker Verification**|Yang Wang et.al.|[2601.13198](https://arxiv.org/abs/2601.13198)|null|
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|**2026-01-19**|**Typhoon ASR Real-time: FastConformer-Transducer for Thai Automatic Speech Recognition**|Warit Sirichotedumrong et.al.|[2601.13044](https://arxiv.org/abs/2601.13044)|**[link](https://github.com/scb-10x/typhoon-asr)**|
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|**2026-01-19**|**Lombard Speech Synthesis for Any Voice with Controllable Style Embeddings**|Seymanur Akti et.al.|[2601.12966](https://arxiv.org/abs/2601.12966)|null|
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|**2026-01-19**|**Supervised Learning for Game Music Segmentation**|Shangxuan Luo et.al.|[2601.12961](https://arxiv.org/abs/2601.12961)|null|
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|**2026-01-19**|**DUAP: Dual-task Universal Adversarial Perturbations Against Voice Control Systems**|Suyang Sun et.al.|[2601.12786](https://arxiv.org/abs/2601.12786)|null|
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|**2026-01-16**|**F-Actor: Controllable Conversational Behaviour in Full-Duplex Models**|Maike Züfle et.al.|[2601.11329](https://arxiv.org/abs/2601.11329)|null|
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|**2026-01-16**|**WenetSpeech-Wu: Datasets, Benchmarks, and Models for a Unified Chinese Wu Dialect Speech Processing Ecosystem**|Chengyou Wang et.al.|[2601.11027](https://arxiv.org/abs/2601.11027)|null|
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|**2026-01-15**|**Unifying Speech Recognition, Synthesis and Conversion with Autoregressive Transformers**|Runyuan Cai et.al.|[2601.10770](https://arxiv.org/abs/2601.10770)|null|

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