← Authors

Eric P. Xing

133 papers · 2006–2026 · 16 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (19) 🧭 Keyword Pioneer 🌍 Conference Polyglot (16) πŸ—ΊοΈ Taxonomy Completionist (41) 🐣 Hot Topic Early Bird 🌈 Renaissance Researcher (11) πŸŒ‰ Interdisciplinary Bridge 🐝 Cross-Pollinator (13) 🏠 Conference Loyalist (60) 🌟 Keyword Trendsetter Combo (18) 🀝 Dynamic Duo (23) 🌱 Topic Pioneer πŸ† Keyword Champion (2) 🧬 Topic Evolution πŸ† Grand Slam πŸ‘₯ Mega-Team (71) πŸ”¬ Deep Specialist (22) πŸ“ˆ Trend Setter πŸš€ Conference Pioneer πŸ”₯ Unstoppable (20) ❓ The Questioner πŸ’Ž Century Club (132) πŸ—ƒοΈ Keyword Collector (180) ⚑ Prolific Year (13)

Conferences

NIPS (60) CVPR (22) JMLR (11) EMNLP (6) ICML (6) ICLR (5) ACL (4) ICCV (4) AAAI (3) AISTATS (3) IJCAI (2) MLHC (2) OSDI (2) COLING (1) ECCV (1) UAI (1)

Top co-authors

Eric P Xing (23) Zhiting Hu (18) Xiaodan Liang (14) Jun Zhu (10) Qirong Ho (10) Kun Zhang (9) Hao Zhang (9) Pengtao Xie (8) Ruslan Salakhutdinov (7) Haohan Wang (7)

Research topics

Deep Learning (2) Bayesian & Probabilistic (1)

Keywords

variational inference (9) multi-task learning (7) latent variable model (6) model compression (6) representation learning (6) bayesian inference (5) graphical model (5) reinforcement learning (5) generative adversarial network (5) topic model (5) large language model (5) gaussian process (5) support vector machine (4) domain adaptation (4) stochastic optimization (4) domain generalization (4) distributed learning (4) zero-shot learning (4) image classification (4) image generation (4)

Papers

Vision-G1: Towards General Reasoning Vision-Language Models via Reinforcement Learning AAAI 2026
Token Level Routing Inference System for Edge Devices ACL 2025
Scaling Long Context Training Data by Long-Distance Referrals ICLR 2025
Causal Representation Learning from Multimodal Biomedical Observations ICLR 2025
Follow My Instruction and Spill the Beans: Scalable Data Extraction from Retrieval-Augmented Generation Systems ICLR 2025
Linear Steerability in Language Models: When It Emerges and How It Evolves EMNLP 2025
SmartCLIP: Modular Vision-language Alignment with Identification Guarantees CVPR 2025
Nile-Chat: Egyptian Language Models for Arabic and Latin Scripts EMNLP 2025
Contextualized Policy Recovery: Modeling and Interpreting Medical Decisions with Adaptive Imitation Learning ICML 2024
Towards Understanding Extrapolation: a Causal Lens NIPS 2024
Transformers to SSMs: Distilling Quadratic Knowledge to Subquadratic Models NIPS 2024
Learning Discrete Concepts in Latent Hierarchical Models NIPS 2024
Web2Code: A Large-scale Webpage-to-Code Dataset and Evaluation Framework for Multimodal LLMs NIPS 2024
Dynamic Rewarding with Prompt Optimization Enables Tuning-free Self-Alignment of Language Models EMNLP 2024
Fast Matrix Multiplications for Lookup Table-Quantized LLMs EMNLP 2024
Unified Generation, Reconstruction, and Representation: Generalized Diffusion with Adaptive Latent Encoding-Decoding ICML 2024
Position: TrustLLM: Trustworthiness in Large Language Models ICML 2024
Weakly Supervised 3D Open-vocabulary Segmentation NIPS 2023
3D Semantic Segmentation in the Wild: Learning Generalized Models for Adverse-Condition Point Clouds CVPR 2023
StyleRF: Zero-Shot 3D Style Transfer of Neural Radiance Fields CVPR 2023
Understanding Masked Autoencoders via Hierarchical Latent Variable Models CVPR 2023
FedNAR: Federated Optimization with Normalized Annealing Regularization NIPS 2023
Squeeze, Recover and Relabel: Dataset Condensation at ImageNet Scale From A New Perspective NIPS 2023
Cappy: Outperforming and Boosting Large Multi-Task LMs with a Small Scorer NIPS 2023
Counterfactual Generation with Identifiability Guarantees NIPS 2023
Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena NIPS 2023
Making Scalable Meta Learning Practical NIPS 2023
Temporally Disentangled Representation Learning under Unknown Nonstationarity NIPS 2023
Identification of Nonlinear Latent Hierarchical Models NIPS 2023
KD-DLGAN: Data Limited Image Generation via Knowledge Distillation CVPR 2023
AMP: Automatically Finding Model Parallel Strategies with Heterogeneity Awareness NIPS 2022
Nonuniform-to-Uniform Quantization: Towards Accurate Quantization via Generalized Straight-Through Estimation CVPR 2022
Towards Principled Disentanglement for Domain Generalization CVPR 2022
Toward learning human-aligned cross-domain robust models by countering misaligned features UAI 2022
The Two Dimensions of Worst-Case Training and Their Integrated Effect for Out-of-Domain Generalization CVPR 2022
Masked Generative Adversarial Networks are Data-Efficient Generation Learners NIPS 2022
Rare Gems: Finding Lottery Tickets at Initialization NIPS 2022
Vision Transformer Slimming: Multi-Dimension Searching in Continuous Optimization Space CVPR 2022
Alpa: Automating Inter- and Intra-Operator Parallelism for Distributed Deep Learning OSDI 2022
Multi-task Learning of Order-Consistent Causal Graphs NIPS 2021
Pollux: Co-adaptive Cluster Scheduling for Goodput-Optimized Deep Learning OSDI 2021
Improving GAN Training with Probability Ratio Clipping and Sample Reweighting NIPS 2020
Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly JMLR 2020
Self-Challenging Improves Cross-Domain Generalization ECCV 2020
AutoSync: Learning to Synchronize for Data-Parallel Distributed Deep Learning NIPS 2020
High-Frequency Component Helps Explain the Generalization of Convolutional Neural Networks CVPR 2020
Regularizing Black-box Models for Improved Interpretability NIPS 2020
Specific and Shared Causal Relation Modeling and Mechanism-Based Clustering NIPS 2019
Learning Data Manipulation for Augmentation and Weighting NIPS 2019
Learning Sample-Specific Models with Low-Rank Personalized Regression NIPS 2019
Learning Robust Global Representations by Penalizing Local Predictive Power NIPS 2019
Knowledge-Driven Encode, Retrieve, Paraphrase for Medical Image Report Generation AAAI 2019
What if We Simply Swap the Two Text Fragments? A Straightforward yet Effective Way to Test the Robustness of Methods to Confounding Signals in Nature Language Inference Tasks AAAI 2019
Learning Robust Representations by Projecting Superficial Statistics Out ICLR 2019
Multimodal Machine Learning for Automated ICD Coding MLHC 2019
Rethinking Knowledge Graph Propagation for Zero-Shot Learning CVPR 2019
Learning Pipelines with Limited Data and Domain Knowledge: A Study in Parsing Physics Problems NIPS 2018
The Sample Complexity of Semi-Supervised Learning with Nonparametric Mixture Models NIPS 2018
Unsupervised Text Style Transfer using Language Models as Discriminators NIPS 2018
On Unifying Deep Generative Models ICLR 2018
Effective Use of Bidirectional Language Modeling for Transfer Learning in Biomedical Named Entity Recognition MLHC 2018
Distributed Proximal Gradient Algorithm for Partially Asynchronous Computer Clusters JMLR 2018
Neural Architecture Search with Bayesian Optimisation and Optimal Transport NIPS 2018
DAGs with NO TEARS: Continuous Optimization for Structure Learning NIPS 2018
Hybrid Retrieval-Generation Reinforced Agent for Medical Image Report Generation NIPS 2018
Deep Generative Models with Learnable Knowledge Constraints NIPS 2018
Symbolic Graph Reasoning Meets Convolutions NIPS 2018
Dual Motion GAN for Future-Flow Embedded Video Prediction ICCV 2017
Structured Generative Adversarial Networks NIPS 2017
Efficient Multiple Instance Metric Learning Using Weakly Supervised Data CVPR 2017
Deep Variation-Structured Reinforcement Learning for Visual Relationship and Attribute Detection CVPR 2017
Interpretable Structure-Evolving LSTM CVPR 2017
Deep Determinantal Point Process for Large-Scale Multi-Label Classification ICCV 2017
Recurrent Topic-Transition GAN for Visual Paragraph Generation ICCV 2017
Nonparametric Variational Auto-Encoders for Hierarchical Representation Learning ICCV 2017
Toward Controlled Generation of Text ICML 2017
Learning Latent Space Models with Angular Constraints ICML 2017
Uncorrelation and Evenness: a New Diversity-Promoting Regularizer ICML 2017
Learning Scalable Deep Kernels with Recurrent Structure JMLR 2017
Variance Reduction in Stochastic Gradient Langevin Dynamics NIPS 2016
They Are Not Equally Reliable: Semantic Event Search Using Differentiated Concept Classifiers CVPR 2016
Stochastic Variational Deep Kernel Learning NIPS 2016
Learning HMMs with Nonparametric Emissions via Spectral Decompositions of Continuous Matrices NIPS 2016
Deep Kernel Learning AISTATS 2016
Latent Space Inference of Internet-Scale Networks JMLR 2016
Bayesian Nonparametric Kernel-Learning AISTATS 2016
Closed-Form Training of Mahalanobis Distance for Supervised Clustering CVPR 2016
AD3: Alternating Directions Dual Decomposition for MAP Inference in Graphical Models JMLR 2015
An Active Learning Approach to Coreference Resolution IJCAI 2015
The Human Kernel NIPS 2015
Bayesian Inference with Posterior Regularization and Applications to Infinite Latent SVMs JMLR 2014
Spectral Unsupervised Parsing with Additive Tree Metrics ACL 2014
On Model Parallelization and Scheduling Strategies for Distributed Machine Learning NIPS 2014
Dependent nonparametric trees for dynamic hierarchical clustering NIPS 2014
Joint Summarization of Large-scale Collections of Web Images and Videos for Storyline Reconstruction CVPR 2014
Reconstructing Storyline Graphs for Image Recommendation from Web Community Photos CVPR 2014
Quasi Real-Time Summarization for Consumer Videos CVPR 2014
Hierarchical Feature Hashing for Fast Dimensionality Reduction CVPR 2014
Graph Estimation From Multi-Attribute Data JMLR 2014
Multi-Modal Distance Metric Learning IJCAI 2013
More Effective Distributed ML via a Stale Synchronous Parallel Parameter Server NIPS 2013
Variance Reduction for Stochastic Gradient Optimization NIPS 2013
Restricting exchangeable nonparametric distributions NIPS 2013
A Scalable Approach to Probabilistic Latent Space Inference of Large-Scale Networks NIPS 2013
Sparse Output Coding for Large-Scale Visual Recognition CVPR 2013
Jointly Aligning and Segmenting Multiple Web Photo Streams for the Inference of Collective Photo Storylines CVPR 2013
MedLDA: Maximum Margin Supervised Topic Models JMLR 2012
On Triangular versus Edge Representations --- Towards Scalable Modeling of Networks NIPS 2012
Symmetric Correspondence Topic Models for Multilingual Text Analysis NIPS 2012
Monte Carlo Methods for Maximum Margin Supervised Topic Models NIPS 2012
Discovering Sociolinguistic Associations with Structured Sparsity ACL 2011
On Time Varying Undirected Graphs AISTATS 2011
Kernel Embeddings of Latent Tree Graphical Models NIPS 2011
Large-Scale Category Structure Aware Image Categorization NIPS 2011
Infinite Latent SVM for Classification and Multi-task Learning NIPS 2011
Adaptive Multi-Task Lasso: with Application to eQTL Detection NIPS 2010
Predictive Subspace Learning for Multi-view Data: a Large Margin Approach NIPS 2010
Object Bank: A High-Level Image Representation for Scene Classification & Semantic Feature Sparsification NIPS 2010
A Latent Variable Model for Geographic Lexical Variation EMNLP 2010
Large Margin Learning of Upstream Scene Understanding Models NIPS 2010
Time-Varying Dynamic Bayesian Networks NIPS 2009
Nonextensive Information Theoretic Kernels on Measures JMLR 2009
Heterogeneous multitask learning with joint sparsity constraints NIPS 2009
Maximum Entropy Discrimination Markov Networks JMLR 2009
Sparsistent Learning of Varying-coefficient Models with Structural Changes NIPS 2009
Mixed Membership Stochastic Blockmodels NIPS 2008
Partially Observed Maximum Entropy Discrimination Markov Networks NIPS 2008
Mixed Membership Stochastic Blockmodels JMLR 2008
Stacking Dependency Parsers EMNLP 2008
HM-BiTAM: Bilingual Topic Exploration, Word Alignment, and Translation NIPS 2007
BiTAM: Bilingual Topic AdMixture Models for Word Alignment COLING 2006
Hidden Markov Dirichlet Process: Modeling Genetic Recombination in Open Ancestral Space NIPS 2006
BiTAM: Bilingual Topic AdMixture Models for Word Alignment ACL 2006