Generative Model

Generative models are artificial intelligence systems designed to create new data instances that resemble a training dataset, aiming to learn and replicate the underlying data distribution. Current research emphasizes improving efficiency and controllability, focusing on architectures like diffusion models, autoregressive models, and generative flow networks, as well as refining training algorithms and loss functions. These advancements have significant implications across diverse fields, enabling applications such as realistic image and music generation, protein design, and improved data augmentation techniques for various machine learning tasks.

Papers

November 1, 2024

Evaluation Metric for Quality Control and Generative Models in Histopathology Images
Pranav Jeevan, Neeraj Nixon, Abhijeet Patil, Amit Sethi
Generative Model Image Quality Evaluation Metric Histopathology Image Histopathology Datasets Quality Control
Diffusion Models as Network Optimizers: Explorations and Analysis
Ruihuai Liang, Bo Yang, Pengyu Chen, Xianjin Li, Yifan Xue, Zhiwen Yu, Xuelin Cao, Yan Zhang, Mérouane Debbah, H. Vincent Poor, Chau Yuen
Diffusion Model Generative Model General Analysis Environment Exploration Probabilistic Model Generative Diffusion Model Network Optimization

October 31, 2024

A Geometric Framework for Understanding Memorization in Generative Models
Brendan Leigh Ross, Hamidreza Kamkari, Tongzi Wu, Rasa Hosseinzadeh, Zhaoyan Liu, George Stein, Jesse C. Cresswell, Gabriel Loaiza-Ganem
Generative Model Full Model Generative Question Limited Memorization Memorization Effect Manifold Hypothesis Geometric Framework
Learning Visual Parkour from Generated Images
Alan Yu, Ge Yang, Ran Choi, Yajvan Ravan, John Leonard, Phillip Isola
Generative Model Simulation Study AI Generated Image Robot Dog Direct Numerical Simulation
Counterfactual MRI Data Augmentation using Conditional Denoising Diffusion Generative Models
Pedro Morão, Joao Santinha, Yasna Forghani, Nuno Loução, Pedro Gouveia, Mario A. T. Figueiredo
Generative Model Medical Imaging Denoising Diffusion Counterfactual Image Counterfactual Data Augmentation
How Do Flow Matching Models Memorize and Generalize in Sample Data Subspaces?
Weiguo Gao, Ming Li
Generative Model Data Set Flow Matching Deep Subspace Proper Orthogonal Decomposition

October 30, 2024

FlowLLM: Flow Matching for Material Generation with Large Language Models as Base Distributions
Anuroop Sriram, Benjamin Kurt Miller, Ricky T. Q. Chen, Brandon M. Wood
Generative Model Large Language Flow Matching Material Discovery Material Generation Unconventional Crystal
Diffusion Beats Autoregressive: An Evaluation of Compositional Generation in Text-to-Image Models
Arash Marioriyad, Parham Rezaei, Mahdieh Soleymani Baghshah, Mohammad Hossein Rohban
Generative Model Global Evaluation Image Generation Faithful Generation Text to Image Model Compositional Ability Diffusion Based Model Compositional Generation AutoRegressive Diffusion

October 29, 2024

AmpleGCG-Plus: A Strong Generative Model of Adversarial Suffixes to Jailbreak LLMs with Higher Success Rates in Fewer Attempts
Vishal Kumar, Zeyi Liao, Jaylen Jones, Huan Sun
Large Language Model Generative Model Adversarial Suffix Suffix Prediction
Protecting Privacy in Multimodal Large Language Models with MLLMU-Bench
Zheyuan Liu, Guangyao Dou, Mengzhao Jia, Zhaoxuan Tan, Qingkai Zeng, Yongle Yuan, Meng Jiang
Language Model Generative Model Multimodal Large Language Model Web Corpus Protecting Privacy ML Agent Bench
SimSiam Naming Game: A Unified Approach for Representation Learning and Emergent Communication
Nguyen Le Hoang, Tadahiro Taniguchi, Fang Tianwei, Akira Taniguchi
Generative Model Representation Learning Variational Inference Variational Autoencoder Unified Framework Emergent Communication Emergent Language
On the Statistical Complexity of Estimating VENDI Scores from Empirical Data
Azim Ospanov, Farzan Farnia
Generative Model Raw Data Empirical Study Statistical Complexity Truncated Linear Matrix Based Entropy Vendi Score
Generating Realistic Tabular Data with Large Language Models
Dang Nguyen, Sunil Gupta, Kien Do, Thin Nguyen, Svetha Venkatesh
Language Model Generative Model Synthetic Data Tabular Data Data Generation Synthetic Tabular Data Generation

October 28, 2024

CaloChallenge 2022: A Community Challenge for Fast Calorimeter Simulation
Claudius Krause, Michele Faucci Giannelli, Gregor Kasieczka, Benjamin Nachman, Dalila Salamani, David Shih, Anna Zaborowska, Oz Amram, Kerstin Borras, Matthew R. Buckley, Erik Buhmann, Thorsten Buss, Renato Paulo Da Costa Cardoso, Anthony L. Caterini, Nadezda Chernyavskaya, Federico A.G. Corchia, Jesse C. Cresswell, Sascha Diefenbacher, Etienne Dreyer, Vijay Ekambaram, Engin Eren, Florian Ernst, Luigi Favaro, Matteo Franchini, Frank Gaede, Eilam Gross, Shih-Chieh Hsu, Kristina Jaruskova, Benno Käch, Jayant Kalagnanam, Raghav Kansal, Taewoo Kim, Dmitrii Kobylianskii, Anatolii Korol, William Korcari, Dirk Krücker, Katja Krüger, Marco Letizia, Shu Li, Qibin Liu, Xiulong Liu, Gabriel Loaiza-Ganem, Thandikire Madula, Peter McKeown, Isabell-A. Melzer-Pellmann, Vinicius Mikuni, Nam Nguyen, Ayodele Ore, Sofia Palacios Schweitzer, Ian Pang, Kevin Pedro, Tilman Plehn, Witold Pokorski, Huilin Qu, Piyush Raikwar, John A. Raine, Humberto Reyes-Gonzalez, Lorenzo Rinaldi, Brendan Leigh Ross, Moritz A.W. Scham, Simon Schnake, Chase Shimmin, Eli Shlizerman, Nathalie Soybelman, Mudhakar Srivatsa, Kalliopi Tsolaki, Sofia Vallecorsa, Kyongmin Yeo, Rui Zhang et al. (22 additional authors not shown) You must enabled JavaScript to view entire author list.
Generative Model Simulation Study State of the Art Generative Calorimeter Simulation Calorimeter Shower Core Challenge
Accelerated, Robust Lower-Field Neonatal MRI with Generative Models
Yamin Arefeen, Brett Levac, Jonathan I. Tamir
Generative Model Robust Version Magnetic Resonance Imaging Low Rate ACCELERATION Fetal Brain Diffusion Based Generative Fetal MRI
LARP: Tokenizing Videos with a Learned Autoregressive Generative Prior
Hanyu Wang, Saksham Suri, Yixuan Ren, Hao Chen, Abhinav Shrivastava
Generative Model Video Generation Gameplay Video Autoregressive Generative Model Role Play Semantic Patch
Diff-Instruct*: Towards Human-Preferred One-step Text-to-image Generative Models
Weijian Luo, Colin Zhang, Debing Zhang, Zhengyang Geng
Generative Model Text to Image
Scaling-based Data Augmentation for Generative Models and its Theoretical Extension
Yoshitaka Koike, Takumi Nakagawa, Hiroki Waida, Takafumi Kanamori
Generative Model Data Augmentation GAN Model Stable Learning Diffusion GAN Natural Extension

October 27, 2024

Symbotunes: unified hub for symbolic music generative models
Paweł Skierś, Maksymilian Łazarski, Michał Kopeć, Mateusz Modrzejewski
Generative Model Symbolic Music Generate Quick Unified Library
Idempotent Unsupervised Representation Learning for Skeleton-Based Action Recognition
Lilang Lin, Lehong Wu, Jiahang Zhang, Jiaying Liu
Generative Model Action Recognition Generative Modeling Unsupervised Representation Learning Pre Trained Generative Model Skeleton Based Action

Generative Model

Papers

Evaluation Metric for Quality Control and Generative Models in Histopathology Images

Diffusion Models as Network Optimizers: Explorations and Analysis

A Geometric Framework for Understanding Memorization in Generative Models

Learning Visual Parkour from Generated Images

Counterfactual MRI Data Augmentation using Conditional Denoising Diffusion Generative Models

How Do Flow Matching Models Memorize and Generalize in Sample Data Subspaces?

FlowLLM: Flow Matching for Material Generation with Large Language Models as Base Distributions

Diffusion Beats Autoregressive: An Evaluation of Compositional Generation in Text-to-Image Models

AmpleGCG-Plus: A Strong Generative Model of Adversarial Suffixes to Jailbreak LLMs with Higher Success Rates in Fewer Attempts

Protecting Privacy in Multimodal Large Language Models with MLLMU-Bench

SimSiam Naming Game: A Unified Approach for Representation Learning and Emergent Communication

On the Statistical Complexity of Estimating VENDI Scores from Empirical Data

Generating Realistic Tabular Data with Large Language Models

CaloChallenge 2022: A Community Challenge for Fast Calorimeter Simulation

Accelerated, Robust Lower-Field Neonatal MRI with Generative Models

LARP: Tokenizing Videos with a Learned Autoregressive Generative Prior

Diff-Instruct*: Towards Human-Preferred One-step Text-to-image Generative Models

Scaling-based Data Augmentation for Generative Models and its Theoretical Extension

Symbotunes: unified hub for symbolic music generative models

Idempotent Unsupervised Representation Learning for Skeleton-Based Action Recognition