Generative Models

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Generative Models

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1,168 papers

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PersonaGest: Personalized Co-Speech Gesture Generation with Semantic-Guided Hierarchical Motion Representation
May 8, 2026Junchuan Zhao, Qifan Liang, Ye WangCo-Speech Gesture Generation Hand Gesture Recognition
On the Robustness of Distribution Support under Diffusion Guidance
May 8, 2026Ruijia Cao, Yuchen Wu, Nisha ChandramoorthyGenerative Processes
Coupling Models for One-Step Discrete Generation
May 8, 2026Fred Zhangzhi Peng, Avishek Joey Bose, Anru R. Zhang +1Generative Models Data Generation
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May 7, 2026Guyue Luo, Qiao LiuStructural Equation Models Latent Variable
Conservative Flows: A New Paradigm of Generative Models
May 7, 2026Eshed Gal, Md Shahriar Rahim Siddiqui, Moshe Eliasof +1Generative Flow Networks Generative Models
HyperTransport: Amortized Conditioning of T2I Generative Models
May 7, 2026Valentino Maiorca, Eleonora Gualdoni, Xavier Suau +3Activation Steering Stable Transport
Christoffel-DPS: Optimal sensor placement in diffusion posterior sampling for arbitrary distributions
May 7, 2026James Rowbottom, Nick Huang, Carola-Bibiane Schönlieb +1Optimal Sensor Placement Posterior Sampling
A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models
May 7, 2026Aditya Ranganath, Mukesh SinghalScore-Based Diffusion Model Generative Models
MIND: Monge Inception Distance for Generative Models Evaluation
May 7, 2026Quentin Berthet, Yu-Han Wu, Clement Crepy +3Fréchet Inception Distance Generative Models
GlazyBench: A Benchmark for Ceramic Glaze Property Prediction and Image Generation
May 7, 2026Ziyu Zhai, Siyou Li, Juexi Shao +1Image Generation Generative Models
LiVeAction: a Lightweight, Versatile, and Asymmetric Neural Codec Design for Real-time Operation
May 7, 2026Dan Jacobellis, Neeraja J. YadwadkarRate-Distortion Theory Real-Time Systems
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May 7, 2026Nafis Saami Azad, Raiyan Abdul BatenCreativity Artificial Intelligence Evaluation
Order-Agnostic Autoregressive Modelling with Missing Data
May 7, 2026Ignacio Peis, Pablo M. Olmos, Jes FrellsenMissing Data Imputation
A Flow Matching Algorithm for Many-Shot Adaptation to Unseen Distributions
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Secure Seed-Based Multi-bit Watermarking for Diffusion Models from First Principles
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Visual Fingerprints for LLM Generation Comparison
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Physical Fidelity Reconstruction via Improved Consistency-Distilled Flow Matching for Dynamical Systems
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GCCM: Enhancing Generative Graph Prediction via Contrastive Consistency Model
May 7, 2026Shaozhen Ma, Wei Huang, Hanchen Wang +2Discrete Diffusion Model Generative Models
Spherical Flows for Sampling Categorical Data
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The Pedagogy of AI Mistakes: Fostering Higher-Order Thinking
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May 6, 2026Alexander DeLise, Nick DexterSparse Recovery Generative Models
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May 6, 2026Arthur Gretton, Li Kevin Wenliang, Alexandre Galashov +3Wasserstein Gradient Flows Generative Models
Hypergraph Generation via Structured Stochastic Diffusion
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Threshold-Guided Optimization for Visual Generative Models
May 6, 2026Jinbin Bai, Yu Lei, Qingyu Shi +6Preference Alignment Training-Free Reward Alignment
Gradients with Respect to Semantics Preserving Embeddings Tell the Uncertainty of Large Language Models
May 6, 2026Mingda Li, Rundong Lv, Xinyu Li +2Large Language Model Uncertainty Large Language Model Generation
Library learning with e-graphs on jazz harmony
May 6, 2026Zeng Ren, Maddy Bowers, Xinyi Guan +1Harmonic Tones Sheet Music
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May 5, 2026Zhiqi Li, Duowen Chen, Yuchen Sun +1Flow Map Generative Models
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May 5, 2026Roberto Netti, Emily Hinds, Francesco Calvanese +3Protein Design Sequence Modeling
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May 5, 2026Bo-Wen Zhang, Jin Ye, Peng-Yu Hua +4Large Language Model Planning Large Language Model Reasoning
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May 4, 2026Thanasis Pantsios, Dimitrios Karageorgiou, Christos Koutlis +3Ai-Generated Image Detection Generative Artificial Intelligence
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May 3, 2026Phil Sidney Ostheimer, Mayank Nagda, Andriy Balinskyy +6Discrete Diffusion Model Sparsity
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May 3, 2026Srihari Unnikrishnan, Jaskaran Singh Walia, Drishti Goel +1Incident Response Cloud
Distributional Causal Mediation via Conditional Generative Modeling
May 3, 2026Jinlun Zhang, Haoneng Huang, Zishu Zhan +1Causal Mediation Analysis Conditional Distribution
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MG-Former: A Transformer-Based Framework for Music-Driven 3D Conducting Gesture Generation
May 2, 2026Ke Qiu, Yawen Qin, Tianzhi Jia +3Co-Speech Gesture Generation Audio Latent
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May 1, 2026Yuxin Lu, Jiayang Sun, Guibo Zhu +1Joint Audio-Video Generation Talk
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May 1, 2026Wenda Chu, Bingliang Zhang, Jiaqi Han +4Autoregressive Image Generation Generative Models
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May 1, 2026Fang Wu, Weihao Xuan, Heli Qi +26Protein Design Protein
Escaping Mode Collapse in LLM Generation via Geometric Regulation
May 1, 2026Xin Du, Kumiko Tanaka-IshiiLarge Language Model Generation Autoregressive Generation
Divergence is Uncertainty: A Closed-Form Posterior Covariance for Flow Matching
May 1, 2026Jiarui Xing, Song Wang, Jian WangGenerative Models Posterior
Binomial flows: Denoising and flow matching for discrete ordinal data
May 1, 2026Yair Shenfeld, Ricardo Baptista, Stefano PeluchettiDiscrete Diffusion Model Generative Models
Online Self-Calibration Against Hallucination in Vision-Language Models
May 1, 2026Minghui Chen, Chenxu Yang, Hengjie Zhu +3Large Vision Language Models Large Language Model Hallucination

May 8, 2026 · cs.GRJ/K move · Enter open · S save

PersonaGest: Personalized Co-Speech Gesture Generation with Semantic-Guided Hierarchical Motion Representation

Junchuan Zhao, Qifan Liang, Ye Wang

School of Computing, National University of Singapore

Co-speech gesture generation aims to synthesize realistic body movements that are semantically coherent with speech and faithful to a user-specified gestural style. Existing VQ-VAE based co-speech gesture generation methods improve generation quality but fail to encode semantic structure into the motion representation or explicitly disentangle content from style, limiting both semantic coherence and personalization fidelity. We present PersonaGest, a two-stage framework addressing both limitations. In the first stage, a semantic-guided RVQ-VAE disentangles motion content and gestural style within the residual quantization structure, where a Semantic-Aware Motion Codebook (SMoC) organizes the content codebook by gesture semantics and contrastive learning further enforces content-style separation. In the second stage, a Masked Generative Transformer generates content tokens via a semantic-aware re-masking strategy, followed by a cascade of Style Residual Transformers conditioned on a reference motion prompt for style control. Extensive experiments demonstrate state-of-the-art performance on objective metrics and perceptual user studies, with strong style consistency to the reference prompt. Our project page with demo videos is available at https://danny-nus.github.io/PersonaGest/

Co-Speech Gesture Generation Hand Gesture Recognition Generative Framework Persona

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