Autoregressive Model

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Period ending 2026-09-14

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Period ending 2026-09-07

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TailedTS: Benchmark Dataset for Heavy-Tailed Time Series Prediction and Periodicity Quantification
May 9, 2026Xinyu Chen, HanQin Cai, Lijun Ding +1Heavy-Tailed Noise Time Series
Non-Monotonic Latency in Apple MPS Decoding: KV Cache Interactions and Execution Regimes
May 9, 2026Willy Fitra HendriaAutoregressive Decoding Low-Latency Systems
Controlling Transient Amplification Improves Long-horizon Rollouts
May 9, 2026Adeel Pervez, Francesco LocatelloLong Rollouts Long-Horizon Forecasting
HairGPT: Strand-as-Language Autoregressive Modeling for Realistic 3D Hairstyle Synthesis
May 9, 2026Haimin Luo, Min Ouyang, Lan Xu +1Stylization Generative Models
The Power of Second Order Methods for Sequence Preconditioning
May 8, 2026Annie Marsden, Elad HazanAutoregressive Model Sequence
Exactness Matters for Physical Rule Enforcement
May 8, 2026Bum Jun KimShallow Water Equations Physics-Informed Deep Learning
Don't Retrain, Align: Adapting Autoregressive LMs to Diffusion LMs via Representation Alignment
May 7, 2026Fred Zhangzhi Peng, Alexis Fox, Anru R. Zhang +1Diffusion Language Models Autoregressive Language Models
Order-Agnostic Autoregressive Modelling with Missing Data
May 7, 2026Ignacio Peis, Pablo M. Olmos, Jes FrellsenMissingness Imputation
Learning Discrete Autoregressive Priors with Wasserstein Gradient Flow
May 7, 2026Bowen Zheng, Yihong Luo, Tianyang HuDiscrete Image Tokenizers Autoregressive Token Prediction
Autoregressive Visual Generation Needs a Prologue
May 7, 2026Bowen Zheng, Weijian Luo, Guang Yang +2Autoregressive Image Generation Autoregressive Model
Beyond Autoregressive RTG: Conditioning via Injection Outside Sequential Modeling in Decision Transformer
May 7, 2026Yongyi Wang, Hanyu Liu, Lingfeng Li +6Sequence Modeling Diffusion Transformers
Does Synthetic Data Help? Empirical Evidence from Deep Learning Time Series Forecasters
May 7, 2026Hugo Cazaux, Eyjólfur Ingi Ásgeirsson, Hlynur StefánssonSynthetic Time Series Synthetic Data
Matrix-Decoupled Concentration for Autoregressive Sequences: Dimension-Free Guarantees for Sparse Long-Context Rewards
May 7, 2026Pei-Sen LiAutoregressive Language Models Autoregressive Model
Near-Policy: Accelerating On-Policy Distillation via Asynchronous Generation and Selective Packing
May 7, 2026Miao Rang, Zhenni Bi, Hang Zhou +6On-Policy Distillation Autoregressive Model
SDFlow: Similarity-Driven Flow Matching for Time Series Generation
May 7, 2026Wei Li, Shibo Feng, Pengcheng Wu +3Contrastive Flow Matching Autoregressive Model
Towards Scalable One-Step Generative Modeling for Autoregressive Dynamical System Forecasting
May 7, 2026Tianyue Yang, Xiao XueLong-Horizon Forecasting Autoregressive Model
Contextual Memory-Enhanced Source Coding for Low-SNR Communications
May 6, 2026Ziqiong Wang, Rongpeng LiSource-Channel Coding Signal-To-Noise Ratio
Leveraging Pretrained Language Models as Energy Functions for Glauber Dynamics Text Diffusion
May 5, 2026Tarun Kathuria, Sachin KumarDiffusion Language Models Large Language Model Post-Training
ARMATA: Auto-Regressive Multi-Agent Task Assignment
May 5, 2026Yazan Youssef, Aboelmagd Noureldin, Sidney GivigiPatient-To-Room Assignment Problem Joint Optimization
Rethinking Entropy Minimization in Test-Time Adaptation for Autoregressive Models
May 5, 2026Wei-Ping Huang, Chee-En Yu, Guan-Ting Lin +1Test-Time Adaptation Autoregressive Model
When to Think, When to Speak: Learning Disclosure Policies for LLM Reasoning
May 5, 2026Jiaqi Wei, Xuehang Guo, Pengfei Yu +5LLM Reasoning Methods Token-Level Uncertainty
CARD: Coarse-to-fine Autoregressive Modeling with Radix-based Decomposition for Transferable Free Energy Estimation
May 4, 2026Ziyang Yu, Yi He, Wenbing Huang +2Free Energy Principle Molecular Dynamics
Barriers to Counterfactual Credit Attribution for Autoregressive Models
May 2, 2026Aloni Cohen, Chenhao ZhangLong-Horizon Credit Assignment Autoregressive Model
Component-Aware Self-Speculative Decoding in Hybrid Language Models
May 1, 2026Hector Borobia, Elies Seguí-Mas, Guillermina Tormo-CarbóSpeculative Decoding Hybrid
End-to-End Autoregressive Image Generation with 1D Semantic Tokenizer
May 1, 2026Wenda Chu, Bingliang Zhang, Jiaqi Han +4Autoregressive Image Generation Generative Models
Sampling two-dimensional spin systems with transformers
Apr 30, 2026Piotr Białas, Piotr Korcyl, Tomasz Stebel +2Two-Dimensional Ising Model Samplers
ABC: Any-Subset Autoregression via Non-Markovian Diffusion Bridges in Continuous Time and Space
Apr 30, 2026Gabe Guo, Thanawat Sornwanee, Lutong Hao +3Stochastic Processes Autoregressive Model
Electricity price forecasting across Norway's five bidding zones in the post-crisis era
Apr 29, 2026My Thi Diem Phan, Trung Tuyen Truong, Hoai Phuong Ha +1Energy Forecasting Electricity Markets
Probabilistic data quality assessment for structural monitoring data via outlier-resistant conditional diffusion model
Apr 29, 2026Qi Li, Yong Huang, Hui LiStructural Health Monitoring Data Quality
Breaking the Autoregressive Chain: Hyper-Parallel Decoding for Efficient LLM-Based Attribute Value Extraction
Apr 29, 2026Theodore Glavas, Nikhita Vedula, Dushyanta Dhyani +2Constrained Decoding Strategies LLM Inference Efficiency
VibeToken: Scaling 1D Image Tokenizers and Autoregressive Models for Dynamic Resolution Generations
Apr 27, 2026Maitreya Patel, Jingtao Li, Weiming Zhuang +2Autoregressive Image Generation Discrete Image Tokenizers
DepthKV: Layer-Dependent KV Cache Pruning for Long-Context LLM Inference
Apr 27, 2026Zahra Dehghanighobadi, Asja FischerKey-Value Cache Eviction LLM Inference Efficiency
Autocorrelation Reintroduces Spectral Bias in KANs for Time Series Forecasting
Apr 26, 2026Chen Zeng, Jiahui Wang, Qiao WangKolmogorov-Arnold Networks Time Series Forecasting
Explanation of Dynamic Physical Field Predictions using WassersteinGrad: Application to Autoregressive Weather Forecasting
Apr 24, 2026Younes Essafouri, Laure Raynaud, Luciano Drozda +1Artificial Intelligence Weather Models Neural Fields
A Hybridizable Neural Time Integrator for Stable Autoregressive Forecasting
Apr 22, 2026Brooks Kinch, Xiaozhe Hu, Yilong Huang +6Autoregressive Transformers Autoregressive Model
X-Cache: Cross-Chunk Block Caching for Few-Step Autoregressive World Models Inference
Apr 22, 2026Yixiao Zeng, Jianlei Zheng, Chaoda Zheng +10Cache Video Diffusion Models
Trajectory-Aware Reliability Modeling of Democratic Systems
Apr 22, 2026Dmitry Zaytsev, Valentina Kuskova, Michael CoppedgeEarly Failure Prediction Reliability
StarTSE: Towards Streaming Target Speaker Extraction via Chunk-wise Interleaved Splicing of Autoregressive Language Model
Apr 21, 2026Shuhai Peng, Hui Lu, Jinjiang Liu +8Target Speaker Extraction Autoregressive Text-To-Speech
Handling and Interpreting Missing Modalities in Patient Clinical Trajectories via Autoregressive Sequence Modeling
Apr 20, 2026Andrew Wang, Ellie Pavlick, Ritambhara SinghMultimodal Clinical Data Missing Modalities
FlowRefiner: Flow Matching-Based Iterative Refinement for 3D Turbulent Flow Simulation
Apr 18, 2026Yilong Dai, Yiming Sun, Yiheng Chen +3Turbulence Neural Partial Differential Equation Solvers
Extraction of informative statistical features in the problem of forecasting time series generated by It{ô}-type processes
Apr 18, 2026Victor Korolev, Mikhail Ivanov, Tatiana Kukanova +4Time Series Forecasting Time Series
Reward Weighted Classifier-Free Guidance as Policy Improvement in Autoregressive Models
Apr 16, 2026Alexander Peysakhovich, William BermanReward Gradients Classifier-Free Guidance
The Illusion of Equivalence: Systematic FP16 Divergence in KV-Cached Autoregressive Inference
Apr 16, 2026Ranjith Chodavarapu, Lei XuSystematic Fp16 Divergence Key-Value Cache Quantization
BARD: Bridging AutoRegressive and Diffusion Vision-Language Models Via Highly Efficient Progressive Block Merging and Stage-Wise Distillation
Apr 15, 2026Baoyou Chen, Hanchen Xia, Peng Tu +5Diffusion Language Models Recent Vision-Language Models
Sliding-Window Reordering with Overlap Averaging: A Simple Time-Domain Augmentation for Multivariate Forecasting
Apr 10, 2026Jafar Bakhshaliyev, Johannes Burchert, Niels Landwehr +1Time Series Forecasting Data Augmentation
HAFM: Hierarchical Autoregressive Foundation Model for Music Accompaniment Generation
Apr 10, 2026Jian Zhu, Jianwei Cui, Yunlong Xue +4Piano Cover Generation Musical Structure
Drift-AR: Single-Step Visual Autoregressive Generation via Anti-Symmetric Drifting
Mar 30, 2026Zhen Zou, Xiaoxiao Ma, Mingde Yao +3Autoregressive Diffusion Autoregressive Image Generation
Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers
Mar 24, 2026Jakob Kienegger, Timo GerkmannTarget Speaker Extraction Multi-Object Tracking
Revisiting Autoregressive Models for Generative Image Classification
Mar 19, 2026Ilia Sudakov, Artem Babenko, Dmitry BaranchukAutoregressive Image Generation Generative Models
Not All Retrievals are Useful: Cross-Attention for Input-Aware RAG in Time Series Forecasting
Mar 16, 2026Seunghan Lee, Jaehoon Lee, Jun Seo +7Zero-Shot Forecasting Time Series Forecasting
SEA-TS: Self-Evolving Agent for Autonomous Code Generation of Time Series Forecasting Algorithms
Mar 5, 2026Longkun Xu, Xiaochun Zhang, Qiantu Tuo +1Time Series Forecasting Autoregressive Model
Chain-of-Goals Hierarchical Policy for Long-Horizon Offline Goal-Conditioned RL
Feb 3, 2026Jinwoo Choi, Sang-Hyun Lee, Seung-Woo SeoGoal-Conditioned Reinforcement Learning Long-Horizon
GryphOne: Symbol-Aware Masked Diffusion for Structural Refinement in Offline Handwritten Mathematical Expression Recognition
Feb 3, 2026Takaya Kawakatsu, Ryo IshiyamaHandwriting Word Error Rate
Mechanism Shift During Post-training from Autoregressive to Masked Diffusion Language Models
Jan 21, 2026Injin Kong, Hyoungjoon Lee, Yohan JoMasked Diffusion Language Models Diffusion Language Models
Spanning Tree Autoregressive Visual Generation
Nov 21, 2025Sangkyu Lee, Changho Lee, Janghoon Han +6Autoregressive Image Generation Visual Generation
UniSE: A Unified Framework for Decoder-Only Autoregressive LM-Based Speech Enhancement
Oct 23, 2025Haoyin Yan, Chengwei Liu, Shaofei Xue +4Speech Enhancement Autoregressive Decoding
CRPS-LAM: Probabilistic Regional Weather Forecasting with Continuous Ranked Probability Score
Oct 10, 2025Erik Larsson, Joel Oskarsson, Tomas Landelius +1Artificial Intelligence Weather Models Autoregressive Model
HunyuanImage 3.0 Technical Report
Sep 28, 2025Tencent Hunyuan Foundation Model TeamHigh-Performance Image Generation Models Generative Models
Evidence Recomposition and Predictive Context Residualization for Visual Attribution in Multimodal Large Language Models
Sep 26, 2025Jiawei Liang, Jianjie Huang, Ruoyu Chen +4Large Multimodal Models Token-Level Uncertainty
Temporal horizons in forecasting: a performance-learnability trade-off
Jun 4, 2025Pau Vilimelis Aceituno, Jack William Miller, Noah Marti +2Long-Horizon Forecasting Autoregressive Model

May 9, 2026 · cs.LGJ/K move · Enter open · S save

TailedTS: Benchmark Dataset for Heavy-Tailed Time Series Prediction and Periodicity Quantification

Xinyu Chen, HanQin Cai, Lijun Ding, Jinhua Zhao

We present TailedTS, a large-scale benchmark dataset derived from Wikipedia hourly page view observations throughout 2024, specifically designed to test time series forecasting models under heavy-tailed, zero-inflated, and non-Gaussian conditions. The dataset comprises approximately 24.69 billion data points spanning roughly 3 million unique Wikipedia pages per month, stored in high-efficiency Apache Parquet format. Wikipedia traffic follows a pronounced power-law distribution where roughly 5% of pages account for over 70% of total page views, creating a natural and rigorous testbed for model robustness against extreme volatility that are absent from or underrepresented in existing benchmarks such as M4, M5, and UCI electricity datasets. TailedTS enables several research tasks. First, we introduce a periodicity quantification framework based on sparse autoregression with sparsity and non-negativity constraints, revealing that frequently-viewed pages exhibit significantly weaker periodic structure than their less-viewed counterparts, showing direct implications for server allocation and traffic forecasting on large digital platforms. Second, we provide standardized prediction benchmarks evaluated under a suite of non-Gaussian loss functions, including

\ell_1

-norm, Huber, quantile, and

\ell_p

-norm losses, demonstrating that standard Gaussian-based estimators degrade substantially on high-volume page categories, while robust alternatives provide consistent gains across all traffic scales. TailedTS is publicly available at https://doi.org/10.5281/zenodo.17070469.

Heavy-Tailed Noise Time Series Periodic Domains Benchmark Datasets Power-Law Distribution Autoregressive Model

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