Eric P. Xing

Advancing Reasoning in Diffusion Language Models with Denoising Process Rewards ACL 2026 Decentralized Arena: Towards Democratic and Scalable Automatic Evaluation of Language Models ACL 2026 Vision-G1: Towards General Reasoning Vision-Language Models via Reinforcement Learning AAAI 2026 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 Nile-Chat: Egyptian Language Models for Arabic and Latin Scripts EMNLP 2025 Scaling Long Context Training Data by Long-Distance Referrals ICLR 2025 SmartCLIP: Modular Vision-language Alignment with Identification Guarantees CVPR 2025 Token Level Routing Inference System for Edge Devices ACL 2025 Contextualized Policy Recovery: Modeling and Interpreting Medical Decisions with Adaptive Imitation Learning ICML 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 Learning Discrete Concepts in Latent Hierarchical Models NeurIPS 2024 Position: TrustLLM: Trustworthiness in Large Language Models ICML 2024 Towards Understanding Extrapolation: a Causal Lens NeurIPS 2024 Transformers to SSMs: Distilling Quadratic Knowledge to Subquadratic Models NeurIPS 2024 Unified Generation, Reconstruction, and Representation: Generalized Diffusion with Adaptive Latent Encoding-Decoding ICML 2024 Web2Code: A Large-scale Webpage-to-Code Dataset and Evaluation Framework for Multimodal LLMs NeurIPS 2024 3D Semantic Segmentation in the Wild: Learning Generalized Models for Adverse-Condition Point Clouds CVPR 2023 Cappy: Outperforming and Boosting Large Multi-Task LMs with a Small Scorer NeurIPS 2023 Counterfactual Generation with Identifiability Guarantees NeurIPS 2023 FedNAR: Federated Optimization with Normalized Annealing Regularization NeurIPS 2023 Identification of Nonlinear Latent Hierarchical Models NeurIPS 2023 Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena NeurIPS 2023 KD-DLGAN: Data Limited Image Generation via Knowledge Distillation CVPR 2023 Making Scalable Meta Learning Practical NeurIPS 2023 Squeeze, Recover and Relabel: Dataset Condensation at ImageNet Scale From A New Perspective NeurIPS 2023 StyleRF: Zero-Shot 3D Style Transfer of Neural Radiance Fields CVPR 2023 Temporally Disentangled Representation Learning under Unknown Nonstationarity NeurIPS 2023 Understanding Masked Autoencoders via Hierarchical Latent Variable Models CVPR 2023 Weakly Supervised 3D Open-vocabulary Segmentation NeurIPS 2023 Alpa: Automating Inter- and Intra-Operator Parallelism for Distributed Deep Learning OSDI 2022 AMP: Automatically Finding Model Parallel Strategies with Heterogeneity Awareness NeurIPS 2022 Masked Generative Adversarial Networks are Data-Efficient Generation Learners NeurIPS 2022 Nonuniform-to-Uniform Quantization: Towards Accurate Quantization via Generalized Straight-Through Estimation CVPR 2022 Rare Gems: Finding Lottery Tickets at Initialization NeurIPS 2022 The Two Dimensions of Worst-Case Training and Their Integrated Effect for Out-of-Domain Generalization CVPR 2022 Toward learning human-aligned cross-domain robust models by countering misaligned features UAI 2022 Towards Principled Disentanglement for Domain Generalization CVPR 2022 Vision Transformer Slimming: Multi-Dimension Searching in Continuous Optimization Space CVPR 2022 Multi-task Learning of Order-Consistent Causal Graphs NeurIPS 2021 Pollux: Co-adaptive Cluster Scheduling for Goodput-Optimized Deep Learning OSDI 2021 AutoSync: Learning to Synchronize for Data-Parallel Distributed Deep Learning NeurIPS 2020 High-Frequency Component Helps Explain the Generalization of Convolutional Neural Networks CVPR 2020 Improving GAN Training with Probability Ratio Clipping and Sample Reweighting NeurIPS 2020 Regularizing Black-box Models for Improved Interpretability NeurIPS 2020 Self-Challenging Improves Cross-Domain Generalization ECCV 2020 Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly JMLR 2020 Knowledge-Driven Encode, Retrieve, Paraphrase for Medical Image Report Generation AAAI 2019 Learning Data Manipulation for Augmentation and Weighting NeurIPS 2019 Learning Robust Global Representations by Penalizing Local Predictive Power NeurIPS 2019 Learning Robust Representations by Projecting Superficial Statistics Out ICLR 2019 Learning Sample-Specific Models with Low-Rank Personalized Regression NeurIPS 2019 Multimodal Machine Learning for Automated ICD Coding MLHC 2019 Rethinking Knowledge Graph Propagation for Zero-Shot Learning CVPR 2019 Specific and Shared Causal Relation Modeling and Mechanism-Based Clustering NeurIPS 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 DAGs with NO TEARS: Continuous Optimization for Structure Learning NeurIPS 2018 Deep Generative Models with Learnable Knowledge Constraints NeurIPS 2018 Distributed Proximal Gradient Algorithm for Partially Asynchronous Computer Clusters JMLR 2018 Effective Use of Bidirectional Language Modeling for Transfer Learning in Biomedical Named Entity Recognition MLHC 2018 Hybrid Retrieval-Generation Reinforced Agent for Medical Image Report Generation NeurIPS 2018 Learning Pipelines with Limited Data and Domain Knowledge: A Study in Parsing Physics Problems NeurIPS 2018 Neural Architecture Search with Bayesian Optimisation and Optimal Transport NeurIPS 2018 On Unifying Deep Generative Models ICLR 2018 Symbolic Graph Reasoning Meets Convolutions NeurIPS 2018 The Sample Complexity of Semi-Supervised Learning with Nonparametric Mixture Models NeurIPS 2018 Unsupervised Text Style Transfer using Language Models as Discriminators NeurIPS 2018 Deep Determinantal Point Process for Large-Scale Multi-Label Classification ICCV 2017 Deep Variation-Structured Reinforcement Learning for Visual Relationship and Attribute Detection CVPR 2017 Dual Motion GAN for Future-Flow Embedded Video Prediction ICCV 2017 Efficient Multiple Instance Metric Learning Using Weakly Supervised Data CVPR 2017 Interpretable Structure-Evolving LSTM CVPR 2017 Learning Latent Space Models with Angular Constraints ICML 2017 Learning Scalable Deep Kernels with Recurrent Structure JMLR 2017 Nonparametric Variational Auto-Encoders for Hierarchical Representation Learning ICCV 2017 Recurrent Topic-Transition GAN for Visual Paragraph Generation ICCV 2017 Structured Generative Adversarial Networks NeurIPS 2017 Toward Controlled Generation of Text ICML 2017 Uncorrelation and Evenness: a New Diversity-Promoting Regularizer ICML 2017 Bayesian Nonparametric Kernel-Learning AISTATS 2016 Closed-Form Training of Mahalanobis Distance for Supervised Clustering CVPR 2016 Deep Kernel Learning AISTATS 2016 Latent Space Inference of Internet-Scale Networks JMLR 2016 Learning HMMs with Nonparametric Emissions via Spectral Decompositions of Continuous Matrices NeurIPS 2016 Stochastic Variational Deep Kernel Learning NeurIPS 2016 They Are Not Equally Reliable: Semantic Event Search Using Differentiated Concept Classifiers CVPR 2016 Variance Reduction in Stochastic Gradient Langevin Dynamics NeurIPS 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 NeurIPS 2015 Bayesian Inference with Posterior Regularization and Applications to Infinite Latent SVMs JMLR 2014 Dependent nonparametric trees for dynamic hierarchical clustering NeurIPS 2014 Graph Estimation From Multi-Attribute Data JMLR 2014 Hierarchical Feature Hashing for Fast Dimensionality Reduction CVPR 2014 Joint Summarization of Large-scale Collections of Web Images and Videos for Storyline Reconstruction CVPR 2014 On Model Parallelization and Scheduling Strategies for Distributed Machine Learning NeurIPS 2014 Quasi Real-Time Summarization for Consumer Videos CVPR 2014 Reconstructing Storyline Graphs for Image Recommendation from Web Community Photos CVPR 2014 Spectral Unsupervised Parsing with Additive Tree Metrics ACL 2014 A Scalable Approach to Probabilistic Latent Space Inference of Large-Scale Networks NeurIPS 2013 Jointly Aligning and Segmenting Multiple Web Photo Streams for the Inference of Collective Photo Storylines CVPR 2013 More Effective Distributed ML via a Stale Synchronous Parallel Parameter Server NeurIPS 2013 Multi-Modal Distance Metric Learning IJCAI 2013 Restricting exchangeable nonparametric distributions NeurIPS 2013 Sparse Output Coding for Large-Scale Visual Recognition CVPR 2013 Variance Reduction for Stochastic Gradient Optimization NeurIPS 2013 MedLDA: Maximum Margin Supervised Topic Models JMLR 2012 Monte Carlo Methods for Maximum Margin Supervised Topic Models NeurIPS 2012 On Triangular versus Edge Representations --- Towards Scalable Modeling of Networks NeurIPS 2012 Symmetric Correspondence Topic Models for Multilingual Text Analysis NeurIPS 2012 Discovering Sociolinguistic Associations with Structured Sparsity ACL 2011 Infinite Latent SVM for Classification and Multi-task Learning NeurIPS 2011 Kernel Embeddings of Latent Tree Graphical Models NeurIPS 2011 Large-Scale Category Structure Aware Image Categorization NeurIPS 2011 On Time Varying Undirected Graphs AISTATS 2011 Adaptive Multi-Task Lasso: with Application to eQTL Detection NeurIPS 2010 A Latent Variable Model for Geographic Lexical Variation EMNLP 2010 Large Margin Learning of Upstream Scene Understanding Models NeurIPS 2010 Object Bank: A High-Level Image Representation for Scene Classification & Semantic Feature Sparsification NeurIPS 2010 Predictive Subspace Learning for Multi-view Data: a Large Margin Approach NeurIPS 2010 Heterogeneous multitask learning with joint sparsity constraints NeurIPS 2009 Maximum Entropy Discrimination Markov Networks JMLR 2009 Nonextensive Information Theoretic Kernels on Measures JMLR 2009 Sparsistent Learning of Varying-coefficient Models with Structural Changes NeurIPS 2009 Time-Varying Dynamic Bayesian Networks NeurIPS 2009 Mixed Membership Stochastic Blockmodels NeurIPS 2008 Mixed Membership Stochastic Blockmodels JMLR 2008 Partially Observed Maximum Entropy Discrimination Markov Networks NeurIPS 2008 Stacking Dependency Parsers EMNLP 2008 HM-BiTAM: Bilingual Topic Exploration, Word Alignment, and Translation NeurIPS 2007 BiTAM: Bilingual Topic AdMixture Models for Word Alignment ACL 2006 Hidden Markov Dirichlet Process: Modeling Genetic Recombination in Open Ancestral Space NeurIPS 2006 Network Completion and Survey Sampling AISTATS 2005 Seeking The Truly Correlated Topic Posterior - on tight approximate inference of logistic-normal admixture model AISTATS 1999