← Authors

Changyou Chen

92 papers · 2013–2026 · 15 conferences · across top CS/AI conferences

Achievements

πŸ—ΊοΈ Taxonomy Completionist (19) 🐝 Cross-Pollinator (5) 🧭 Keyword Pioneer πŸƒ Academic Marathon (12) 🌍 Conference Polyglot (15) 🌈 Renaissance Researcher (6) πŸŒ‰ Interdisciplinary Bridge 🐣 Hot Topic Early Bird πŸ”¬ Deep Specialist (22) πŸ‘‘ Triple Crown πŸ† Keyword Champion πŸ† Grand Slam 🌱 Topic Pioneer 🀝 Dynamic Duo (26) ❓ The Questioner πŸš€ Conference Pioneer ⚑ Prolific Year (16) πŸ”₯ Unstoppable (13) πŸ—ƒοΈ Keyword Collector (56) πŸ“ˆ Trend Setter πŸ’Ž Century Club (91)

Conferences

NIPS (13) ICLR (12) AAAI (11) ICML (11) AISTATS (9) EMNLP (9) CVPR (7) ACL (6) ICCV (3) IJCAI (3) IJCNLP (3) WACV (2) COLING (1) ECCV (1) NAACL (1)

Top co-authors

Lawrence Carin (26) Ruiyi Zhang (22) Chunyuan Li (19) Yufan Zhou (14) Rajiv Ratn Shah (9) Qinliang Su (9) Yang Zhao (9) Zhe Gan (9) Balaji Krishnamurthy (8) Dinghan Shen (7)

Research topics

Education (1)

Keywords

markov chain monte carlo (9) contrastive learning (7) bayesian inference (6) generative model (6) stochastic gradient (6) variational inference (6) stein variational gradient descent (5) distribution matching (5) generative adversarial network (5) variational autoencoder (5) stochastic gradient mcmc (5) weight uncertainty (4) large language model (4) multimodal learning (4) adversarial learning (4) style transfer (4) latent variable model (4) particle optimization (4) bayesian neural network (4) bayesian sampling (3)

Papers

ALPHA: Action-Based Learning for Pluralistic Human Alignment in Large Language Models AAAI 2026
Teaching Human Behavior Improves Content Understanding Abilities Of VLMs ICLR 2025
Measuring And Improving Engagement of Text-to-Image Generation Models ICLR 2025
Multimodal LLMs as Customized Reward Models for Text-to-Image Generation ICCV 2025
Multi-Modal Multi-Task Unified Embedding Model (M3T-UEM): A Task-Adaptive Representation Learning Framework ICCV 2025
SV-RAG: LoRA-Contextualizing Adaptation of MLLMs for Long Document Understanding ICLR 2025
A High-Quality Text-Rich Image Instruction Tuning Dataset via Hybrid Instruction Generation COLING 2025
Long-Term Ad Memorability: Understanding & Generating Memorable Ads WACV 2025
Cross-Modal Feature Alignment and MMD Improve Robustness of Prompt Tuning WACV 2025
TextLap: Customizing Language Models for Text-to-Layout Planning EMNLP 2024
Large Content And Behavior Models To Understand, Simulate, And Optimize Content And Behavior ICLR 2024
AUC-CL: A Batchsize-Robust Framework for Self-Supervised Contrastive Representation Learning ICLR 2024
Diffusion Models for Multi-Task Generative Modeling ICLR 2024
Towards Aligned Layout Generation via Diffusion Model with Aesthetic Constraints ICLR 2024
A probability contrastive learning framework for 3D molecular representation learning NIPS 2024
TRINS: Towards Multimodal Language Models that Can Read CVPR 2024
AUC Maximization for Low-Resource Named Entity Recognition AAAI 2023
Label-Retrieval-Augmented Diffusion Models for Learning from Noisy Labels NIPS 2023
Persuasion Strategies in Advertisements AAAI 2023
ReAugKD: Retrieval-Augmented Knowledge Distillation For Pre-trained Language Models ACL 2023
Understanding and Constructing Latent Modality Structures in Multi-Modal Representation Learning CVPR 2023
Shifted Diffusion for Text-to-Image Generation CVPR 2023
A Video Is Worth 4096 Tokens: Verbalize Videos To Understand Them In Zero Shot EMNLP 2023
ALCAP: Alignment-Augmented Music Captioner EMNLP 2023
Learning Unnormalized Statistical Models via Compositional Optimization ICML 2023
Fed-CBS: A Heterogeneity-Aware Client Sampling Mechanism for Federated Learning via Class-Imbalance Reduction ICML 2023
MINIMAL: Mining Models for Universal Adversarial Triggers AAAI 2022
Using Sampling to Estimate and Improve Performance of Automated Scoring Systems with Guarantees AAAI 2022
Rethinking Deep Face Restoration CVPR 2022
Hardness-guided domain adaptation to recognise biomedical named entities under low-resource scenarios EMNLP 2022
Why do We Need Large Batchsizes in Contrastive Learning? A Gradient-Bias Perspective NIPS 2022
TiGAN: Text-Based Interactive Image Generation and Manipulation AAAI 2022
Towards Language-Free Training for Text-to-Image Generation CVPR 2022
Rethinking Sentiment Style Transfer EMNLP 2021
Unsupervised Hashing with Contrastive Information Bottleneck IJCAI 2021
Integrating Semantics and Neighborhood Information with Graph-Driven Generative Models for Document Retrieval IJCNLP 2021
MixKD: Towards Efficient Distillation of Large-scale Language Models ICLR 2021
Unpaired Image-to-Image Translation via Latent Energy Transport CVPR 2021
Meta-Learning with Neural Tangent Kernels ICLR 2021
Integrating Semantics and Neighborhood Information with Graph-Driven Generative Models for Document Retrieval ACL 2021
Towards Faithful Neural Table-to-Text Generation with Content-Matching Constraints ACL 2020
Nested-Wasserstein Self-Imitation Learning for Sequence Generation AISTATS 2020
Generative Semantic Hashing Enhanced via Boltzmann Machines ACL 2020
Stochastic Particle-Optimization Sampling and the Non-Asymptotic Convergence Theory AISTATS 2020
Learning Diverse Stochastic Human-Action Generators by Learning Smooth Latent Transitions AAAI 2020
Bayesian Meta Sampling for Fast Uncertainty Adaptation ICLR 2020
Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning ICLR 2020
Bayesian Multi-type Mean Field Multi-agent Imitation Learning NIPS 2020
Learning Manifold Implicitly via Explicit Heat-Kernel Learning NIPS 2020
Improving Adversarial Text Generation by Modeling the Distant Future ACL 2020
Feature Quantization Improves GAN Training ICML 2020
Variance Reduction in Stochastic Particle-Optimization Sampling ICML 2020
Variational Adversarial Kernel Learned Imitation Learning AAAI 2020
Structure-Aware Human-Action Generation ECCV 2020
Repulsive Attention: Rethinking Multi-head Attention as Bayesian Inference EMNLP 2020
Semantic Matching for Sequence-to-Sequence Learning EMNLP 2020
Bayesian Uncertainty Matching for Unsupervised Domain Adaptation IJCAI 2019
Implicit Deep Latent Variable Models for Text Generation IJCNLP 2019
Scalable Thompson Sampling via Optimal Transport AISTATS 2019
On Connecting Stochastic Gradient MCMC and Differential Privacy AISTATS 2019
Adversarial Learning of a Sampler Based on an Unnormalized Distribution AISTATS 2019
Document Hashing with Mixture-Prior Generative Models IJCNLP 2019
Implicit Deep Latent Variable Models for Text Generation EMNLP 2019
Document Hashing with Mixture-Prior Generative Models EMNLP 2019
Topic-Guided Variational Auto-Encoder for Text Generation NAACL 2019
Self-Adversarially Learned Bayesian Sampling AAAI 2019
PointCloud Saliency Maps ICCV 2019
Communication-Efficient Stochastic Gradient MCMC for Neural Networks AAAI 2019
Distributionally Adversarial Attack AAAI 2019
Improving Sequence-to-Sequence Learning via Optimal Transport ICLR 2019
Text-Based Interactive Recommendation via Constraint-Augmented Reinforcement Learning NIPS 2019
Certified Adversarial Robustness with Additive Noise NIPS 2019
Differentially Private Empirical Risk Minimization with Non-convex Loss Functions ICML 2019
Deep Metric Learning: The Generalization Analysis and an Adaptive Algorithm IJCAI 2019
Symmetric Variational Autoencoder and Connections to Adversarial Learning AISTATS 2018
Learning Structural Weight Uncertainty for Sequential Decision-Making AISTATS 2018
Policy Optimization as Wasserstein Gradient Flows ICML 2018
Continuous-Time Flows for Efficient Inference and Density Estimation ICML 2018
Stochastic Gradient Monomial Gamma Sampler ICML 2017
Learning Structured Weight Uncertainty in Bayesian Neural Networks AISTATS 2017
ALICE: Towards Understanding Adversarial Learning for Joint Distribution Matching NIPS 2017
Scalable Bayesian Learning of Recurrent Neural Networks for Language Modeling ACL 2017
Learning Weight Uncertainty With Stochastic Gradient MCMC for Shape Classification CVPR 2016
Stochastic Gradient MCMC with Stale Gradients NIPS 2016
Bridging the Gap between Stochastic Gradient MCMC and Stochastic Optimization AISTATS 2016
Towards Unifying Hamiltonian Monte Carlo and Slice Sampling NIPS 2016
Nonlinear Statistical Learning with Truncated Gaussian Graphical Models ICML 2016
On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators NIPS 2015
Scalable Deep Poisson Factor Analysis for Topic Modeling ICML 2015
Robust Bayesian Max-Margin Clustering NIPS 2014
Bayesian Sampling Using Stochastic Gradient Thermostats NIPS 2014
Dependent Normalized Random Measures ICML 2013