Rong Jin

Scaling Law for Multimodal Large Language Model Supervised Fine-Tuning ACL 2026 MME-RealWorld: Could Your Multimodal LLM Challenge High-Resolution Real-World Scenarios that are Difficult for Humans? ICLR 2025 MM-RLHF: The Next Step Forward in Multimodal LLM Alignment ICML 2025 CARD: Channel Aligned Robust Blend Transformer for Time Series Forecasting ICLR 2024 Structured Model Probing: Empowering Efficient Transfer Learning by Structured Regularization CVPR 2024 SumCSE: Summary as a transformation for Contrastive Learning NAACL 2024 UNICORN: A Unified Causal Video-Oriented Language-Modeling Framework for Temporal Video-Language Tasks EMNLP 2024 AdaNPC: Exploring Non-Parametric Classifier for Test-Time Adaptation ICML 2023 Beyond Appearance: A Semantic Controllable Self-Supervised Learning Framework for Human-Centric Visual Tasks CVPR 2023 FeDXL: Provable Federated Learning for Deep X-Risk Optimization ICML 2023 Free Lunch for Domain Adversarial Training: Environment Label Smoothing ICLR 2023 Making Vision Transformers Efficient From a Token Sparsification View CVPR 2023 One Fits All: Power General Time Series Analysis by Pretrained LM NeurIPS 2023 OneNet: Enhancing Time Series Forecasting Models under Concept Drift by Online Ensembling NeurIPS 2023 Progressive Backdoor Erasing via Connecting Backdoor and Adversarial Attacks CVPR 2023 A Trend-Driven Fashion Design System for Rapid Response Marketing in E-commerce AAAI 2022 CDTrans: Cross-domain Transformer for Unsupervised Domain Adaptation ICLR 2022 CHEX: CHannel EXploration for CNN Model Compression CVPR 2022 Decoupling and Recoupling Spatiotemporal Representation for RGB-D-Based Motion Recognition CVPR 2022 Effective Model Sparsification by Scheduled Grow-and-Prune Methods ICLR 2022 Entroformer: A Transformer-based Entropy Model for Learned Image Compression ICLR 2022 FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecasting ICML 2022 FiLM: Frequency improved Legendre Memory Model for Long-term Time Series Forecasting NeurIPS 2022 Grow and Merge: A Unified Framework for Continuous Categories Discovery NeurIPS 2022 Hybrid Relation Guided Set Matching for Few-Shot Action Recognition CVPR 2022 Improved Fine-Tuning by Better Leveraging Pre-Training Data NeurIPS 2022 KVT: k-NN Attention for Boosting Vision Transformers ECCV 2022 Learning From Untrimmed Videos: Self-Supervised Video Representation Learning With Hierarchical Consistency CVPR 2022 Learning to Generalize to More: Continuous Semantic Augmentation for Neural Machine Translation ACL 2022 MAE-DET: Revisiting Maximum Entropy Principle in Zero-Shot NAS for Efficient Object Detection ICML 2022 Rethinking Supervised Pre-Training for Better Downstream Transferring ICLR 2022 Robust Graph Structure Learning via Multiple Statistical Tests NeurIPS 2022 Scaled ReLU Matters for Training Vision Transformers AAAI 2022 Stability and Generalization Analysis of Gradient Methods for Shallow Neural Networks NeurIPS 2022 TransFGU: A Top-down Approach to Fine-Grained Unsupervised Semantic Segmentation ECCV 2022 Unsupervised Visual Representation Learning by Online Constrained K-Means CVPR 2022 An Online Method for A Class of Distributionally Robust Optimization with Non-convex Objectives NeurIPS 2021 Communication Efficient SGD via Gradient Sampling With Bayes Prior CVPR 2021 Dash: Semi-Supervised Learning with Dynamic Thresholding ICML 2021 Learning Accurate Entropy Model with Global Reference for Image Compression ICLR 2021 Learning Position and Target Consistency for Memory-Based Video Object Segmentation CVPR 2021 Self-Supervised Motion Learning From Static Images CVPR 2021 Self-Supervised Video Representation Learning by Context and Motion Decoupling CVPR 2021 Train a One-Million-Way Instance Classifier for Unsupervised Visual Representation Learning AAAI 2021 Weakly Supervised Representation Learning With Coarse Labels ICCV 2021 Zen-NAS: A Zero-Shot NAS for High-Performance Image Recognition ICCV 2021 DR Loss: Improving Object Detection by Distributional Ranking CVPR 2020 A Practical Semi-Parametric Contextual Bandit IJCAI 2019 Learning with Non-Convex Truncated Losses by SGD UAI 2019 Non-asymptotic Analysis of Stochastic Methods for Non-Smooth Non-Convex Regularized Problems NeurIPS 2019 On the Computation and Communication Complexity of Parallel SGD with Dynamic Batch Sizes for Stochastic Non-Convex Optimization ICML 2019 On the Convergence of (Stochastic) Gradient Descent with Extrapolation for Non-Convex Minimization IJCAI 2019 On the Linear Speedup Analysis of Communication Efficient Momentum SGD for Distributed Non-Convex Optimization ICML 2019 Relative Error Bound Analysis for Nuclear Norm Regularized Matrix Completion JMLR 2019 Robust Online Matching with User Arrival Distribution Drift AAAI 2019 Robust Optimization over Multiple Domains AAAI 2019 Semi-Parametric Sampling for Stochastic Bandits with Many Arms AAAI 2019 SoftTriple Loss: Deep Metric Learning Without Triplet Sampling ICCV 2019 Stagewise Training Accelerates Convergence of Testing Error Over SGD NeurIPS 2019 Stochastic Optimization for DC Functions and Non-smooth Non-convex Regularizers with Non-asymptotic Convergence ICML 2019 Which Factorization Machine Modeling Is Better: A Theoretical Answer with Optimal Guarantee AAAI 2019 XNAS: Neural Architecture Search with Expert Advice NeurIPS 2019 Fast Rates of ERM and Stochastic Approximation: Adaptive to Error Bound Conditions NeurIPS 2018 First-order Stochastic Algorithms for Escaping From Saddle Points in Almost Linear Time NeurIPS 2018 Large-Scale Distance Metric Learning With Uncertainty CVPR 2018 Multinomial Logit Bandit with Linear Utility Functions IJCAI 2018 Deep Learning at Alibaba IJCAI 2017 Empirical Risk Minimization for Stochastic Convex Optimization: $O(1/n)$- and $O(1/n^2)$-type of Risk Bounds COLT 2017 Improved Dynamic Regret for Non-degenerate Functions NeurIPS 2017 Missing Modalities Imputation via Cascaded Residual Autoencoder CVPR 2017 The Opensesame NIST 2016 Speaker Recognition Evaluation System Interspeech 2017 Online Stochastic Linear Optimization under One-bit Feedback ICML 2016 Tracking Slowly Moving Clairvoyant: Optimal Dynamic Regret of Online Learning with True and Noisy Gradient ICML 2016 An Explicit Sampling Dependent Spectral Error Bound for Column Subset Selection ICML 2015 A Simple Homotopy Algorithm for Compressive Sensing AISTATS 2015 CUR Algorithm for Partially Observed Matrices ICML 2015 Fine-Grained Visual Categorization via Multi-Stage Metric Learning CVPR 2015 Lower and Upper Bounds on the Generalization of Stochastic Exponentially Concave Optimization COLT 2015 Theory of Dual-sparse Regularized Randomized Reduction ICML 2015 A Single-Pass Algorithm for Efficiently Recovering Sparse Cluster Centers of High-dimensional Data ICML 2014 Efficient Algorithms for Robust One-bit Compressive Sensing ICML 2014 Extracting Certainty from Uncertainty: Transductive Pairwise Classification from Pairwise Similarities NeurIPS 2014 Top Rank Optimization in Linear Time NeurIPS 2014 Compressed Hashing CVPR 2013 Large-Scale Image Annotation by Efficient and Robust Kernel Metric Learning ICCV 2013 Linear Convergence with Condition Number Independent Access of Full Gradients NeurIPS 2013 Mixed Optimization for Smooth Functions NeurIPS 2013 O(logT) Projections for Stochastic Optimization of Smooth and Strongly Convex Functions ICML 2013 One-Pass AUC Optimization ICML 2013 Online Kernel Learning with a Near Optimal Sparsity Bound ICML 2013 Passive Learning with Target Risk COLT 2013 Recovering the Optimal Solution by Dual Random Projection COLT 2013 Semi-supervised Clustering by Input Pattern Assisted Pairwise Similarity Matrix Completion ICML 2013 Speedup Matrix Completion with Side Information: Application to Multi-Label Learning NeurIPS 2013 Stochastic Convex Optimization with Multiple Objectives NeurIPS 2013 Nyström Method vs Random Fourier Features: A Theoretical and Empirical Comparison NeurIPS 2012 Online Optimization with Gradual Variations COLT 2012 Semi-Crowdsourced Clustering: Generalizing Crowd Labeling by Robust Distance Metric Learning NeurIPS 2012 Stochastic Gradient Descent with Only One Projection NeurIPS 2012 Trading Regret for Efficiency: Online Convex Optimization with Long Term Constraints JMLR 2012 Double Updating Online Learning JMLR 2011 Active Learning by Querying Informative and Representative Examples NeurIPS 2010 A Potential-based Framework for Online Multi-class Learning with Partial Feedback AISTATS 2010 Exclusive Lasso for Multi-task Feature Selection AISTATS 2010 Multi-label Multiple Kernel Learning by Stochastic Approximation: Application to Visual Object Recognition NeurIPS 2010 Adaptive Regularization for Transductive Support Vector Machine NeurIPS 2009 DUOL: A Double Updating Approach for Online Learning NeurIPS 2009 Learning Bregman Distance Functions and Its Application for Semi-Supervised Clustering NeurIPS 2009 Learning to Rank by Optimizing NDCG Measure NeurIPS 2009 Regularized Distance Metric Learning:Theory and Algorithm NeurIPS 2009 An Extended Level Method for Efficient Multiple Kernel Learning NeurIPS 2008 Multi-label Multiple Kernel Learning NeurIPS 2008 Semi-supervised Learning with Weakly-Related Unlabeled Data : Towards Better Text Categorization NeurIPS 2008 Automated Vocabulary Acquisition and Interpretation in Multimodal Conversational Systems ACL 2007 Efficient Convex Relaxation for Transductive Support Vector Machine NeurIPS 2007 Generalized Maximum Margin Clustering and Unsupervised Kernel Learning NeurIPS 2006 An Information Geometry Approach for Distance Metric Learning AISTATS 2005 A New Probabilistic Model for Title Generation COLING 2002