Cover Image

Graph VQ-Transformer (GVT): Fast and Accurate Molecular Generation via High-Fidelity Discrete Latents

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zheng, Haozhuo, Wang, Cheng, Liu, Yang
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation
by: Shi, Ji, et al.
Published: (2025)

Unlocking High-Fidelity Molecular Generation from Mass Spectra via Dual-Stream Line Graph Diffusion
by: Che, Xujun, et al.
Published: (2026)

Compositional Discrete Latent Code for High Fidelity, Productive Diffusion Models
by: Lavoie, Samuel, et al.
Published: (2025)

Topic-VQ-VAE: Leveraging Latent Codebooks for Flexible Topic-Guided Document Generation
by: Yoo, YoungJoon, et al.
Published: (2023)

Fast and Accurate Probing of In-Training LLMs' Downstream Performances
by: Liu, Zhichen, et al.
Published: (2026)

FLIP: Flow-Centric Generative Planning as General-Purpose Manipulation World Model
by: Gao, Chongkai, et al.
Published: (2024)

Fast and Accurate Explanations of Distance-Based Classifiers by Uncovering Latent Explanatory Structures
by: Bley, Florian, et al.
Published: (2025)

Ultra-Fast Language Generation via Discrete Diffusion Divergence Instruct
by: Zheng, Haoyang, et al.
Published: (2025)

Deconstructing Generative Diversity: An Information Bottleneck Analysis of Discrete Latent Generative Models
by: Wu, Yudi, et al.
Published: (2025)

Fast Byte Latent Transformer
by: Kallini, Julie, et al.
Published: (2026)

Unlocking Out-of-Distribution Generalization in Transformers via Recursive Latent Space Reasoning
by: Altabaa, Awni, et al.
Published: (2025)

STAR-VAE: Latent Variable Transformers for Scalable and Controllable Molecular Generation
by: Kwon, Bum Chul, et al.
Published: (2025)

Fast Graph Generation via Spectral Diffusion
by: Luo, Tianze, et al.
Published: (2022)

Synthetic Aircraft Trajectory Generation Using Time-Based VQ-VAE
by: Murad, Abdulmajid, et al.
Published: (2025)

VQ-SAD: Vector Quantized Structure Aware Diffusion For Molecule Generation
by: Noravesh, Farshad, et al.
Published: (2026)

VQ4ALL: Efficient Neural Network Representation via a Universal Codebook
by: Deng, Juncan, et al.
Published: (2024)

Graph Diffusion Transformers are In-Context Molecular Designers
by: Liu, Gang, et al.
Published: (2025)

Sparse-VQ Transformer: An FFN-Free Framework with Vector Quantization for Enhanced Time Series Forecasting
by: Zhao, Yanjun, et al.
Published: (2024)

Discrete Diffusion Schrödinger Bridge Matching for Graph Transformation
by: Kim, Jun Hyeong, et al.
Published: (2024)

Refining Latent Representations: A Generative SSL Approach for Heterogeneous Graph Learning
by: Hu, Yulan, et al.
Published: (2023)

TASER: Temporal Adaptive Sampling for Fast and Accurate Dynamic Graph Representation Learning
by: Deng, Gangda, et al.
Published: (2024)

Graph Tokenization for Bridging Graphs and Transformers
by: Guo, Zeyuan, et al.
Published: (2026)

Latent Shadows: The Gaussian-Discrete Duality in Masked Diffusion
by: Chen, Guinan, et al.
Published: (2026)

Accurate and Scalable Graph Neural Networks via Message Invariance
by: Shi, Zhihao, et al.
Published: (2025)

FLAG: Foundation model representation with Latent diffusion Alignment via Graph for spatial gene expression prediction
by: Si, Qi, et al.
Published: (2026)

Graph Generative Pre-trained Transformer
by: Chen, Xiaohui, et al.
Published: (2025)

SEA: State-Exchange Attention for High-Fidelity Physics Based Transformers
by: Esmati, Parsa, et al.
Published: (2024)

BeamVQ: Aligning Space-Time Forecasting Model via Self-training on Physics-aware Metrics
by: Wu, Hao, et al.
Published: (2024)

Latent-Augmented Discrete Diffusion Models
by: Shariatian, Dario, et al.
Published: (2025)

Are Expressive Encoders Necessary for Discrete Graph Generation?
by: Revolinsky, Jay, et al.
Published: (2026)

High-Fidelity Synthetic ECG Generation via Mel-Spectrogram Informed Diffusion Training
by: Huang, Zhuoyi, et al.
Published: (2025)

Graph Propagation Transformer for Graph Representation Learning
by: Chen, Zhe, et al.
Published: (2023)

High-Fidelity Compression of Seismic Velocity Models via SIREN Auto-Decoders
by: Liu, Caiyun, et al.
Published: (2026)

Generative Representation Learning on Hyper-relational Knowledge Graphs via Masked Discrete Diffusion
by: Lee, Jaejun, et al.
Published: (2026)

Fine-Tuning Diffusion Models for Molecular Generation via Reinforcement Learning and Fast Sampling
by: Lin, Guang, et al.
Published: (2026)

SpecReason: Fast and Accurate Inference-Time Compute via Speculative Reasoning
by: Pan, Rui, et al.
Published: (2025)

MetaMolGen: A Neural Graph Motif Generation Model for De Novo Molecular Design
by: Yan, Zimo, et al.
Published: (2025)

Accurate and Efficient World Modeling with Masked Latent Transformers
by: Burchi, Maxime, et al.
Published: (2025)

Learning Discrete Concepts in Latent Hierarchical Models
by: Kong, Lingjing, et al.
Published: (2024)

Sparse Training of Discrete Diffusion Models for Graph Generation
by: Qin, Yiming, et al.
Published: (2023)