Mingming Gong

Scaling Beyond Context: A Survey of Multimodal Retrieval-Augmented Generation for Document Understanding ACL 2026 Optimal Transport for Time Series Imputation ICLR 2025 A Skewness-Based Criterion for Addressing Heteroscedastic Noise in Causal Discovery ICLR 2025 A Robust Method to Discover Causal or Anticausal Relation ICLR 2025 MissScore: High-Order Score Estimation in the Presence of Missing Data ICML 2025 Extracting Rare Dependence Patterns via Adaptive Sample Reweighting ICML 2025 Learning Imbalanced Data with Beneficial Label Noise ICML 2025 SnapGen: Taming High-Resolution Text-to-Image Models for Mobile Devices with Efficient Architectures and Training CVPR 2025 UNIC-Adapter: Unified Image-instruction Adapter with Multi-modal Transformer for Image Generation CVPR 2025 DIDiffGes: Decoupled Semi-Implicit Diffusion Models for Real-time Gesture Generation from Speech AAAI 2025 Semantic-guided Cross-Modal Prompt Learning for Skeleton-based Zero-shot Action Recognition CVPR 2025 Projection Pursuit Density Ratio Estimation ICML 2025 LaVin-DiT: Large Vision Diffusion Transformer CVPR 2025 Enhancing Treatment Effect Estimation via Active Learning: A Counterfactual Covering Perspective ICML 2025 A Unified Data Representation Learning for Non-parametric Two-sample Testing UAI 2025 Analytic DAG Constraints for Differentiable DAG Learning ICLR 2025 On the Identification of Temporal Causal Representation with Instantaneous Dependence ICLR 2025 Mitigating Spurious Correlations via Counterfactual Contrastive Learning EMNLP 2025 LoCA: Location-Aware Cosine Adaptation for Parameter-Efficient Fine-Tuning ICLR 2025 Causal Discovery with Mixed Linear and Nonlinear Additive Noise Models: A Scalable Approach CLEAR 2024 Physics-informed Knowledge Transfer for Underwater Monocular Depth Estimation ECCV 2024 Identifiable Latent Polynomial Causal Models through the Lens of Change ICLR 2024 Improving Non-Transferable Representation Learning by Harnessing Content and Style ICLR 2024 Learning Transferable Representations for Image Anomaly Localization Using Dense Pretraining WACV 2024 In-N-Out: Lifting 2D Diffusion Prior for 3D Object Removal via Tuning-Free Latents Alignment NIPS 2024 Identifiability Analysis of Linear ODE Systems with Hidden Confounders NIPS 2024 Neural Collapse Inspired Feature Alignment for Out-of-Distribution Generalization NIPS 2024 Discovery of the Hidden World with Large Language Models NIPS 2024 Optimal Kernel Choice for Score Function-based Causal Discovery ICML 2024 HuTuMotion: Human-Tuned Navigation of Latent Motion Diffusion Models with Minimal Feedback AAAI 2024 Grab What You Need: Rethinking Complex Table Structure Recognition with Flexible Components Deliberation AAAI 2024 On the Recoverability of Causal Relations from Temporally Aggregated I.I.D. Data ICML 2024 On Causality in Domain Adaptation and Semi-Supervised Learning: an Information-Theoretic Analysis for Parametric Models JMLR 2024 Identifiability and Asymptotics in Learning Homogeneous Linear ODE Systems from Discrete Observations JMLR 2024 Causal-learn: Causal Discovery in Python JMLR 2024 Part-aware Unified Representation of Language and Skeleton for Zero-shot Action Recognition CVPR 2024 Enhancing Visual Document Understanding with Contrastive Learning in Large Visual-Language Models CVPR 2024 Interventional Fairness on Partially Known Causal Graphs: A Constrained Optimization Approach ICLR 2024 A Variational Framework for Estimating Continuous Treatment Effects with Measurement Error ICLR 2024 Adaptive Local-Component-Aware Graph Convolutional Network for One-Shot Skeleton-Based Action Recognition WACV 2023 Combating Noisy Labels with Sample Selection by Mining High-Discrepancy Examples ICCV 2023 Multiscale Representation for Real-Time Anti-Aliasing Neural Rendering ICCV 2023 Harnessing Out-Of-Distribution Examples via Augmenting Content and Style ICLR 2023 Unpaired Image-to-Image Translation With Shortest Path Regularization CVPR 2023 Generating Dynamic Kernels via Transformers for Lane Detection ICCV 2023 Multi-domain image generation and translation with identifiability guarantees ICLR 2023 Mosaic Representation Learning for Self-supervised Visual Pre-training ICLR 2023 Semi-Implicit Denoising Diffusion Models (SIDDMs) NIPS 2023 Progressive Video Summarization via Multimodal Self-Supervised Learning WACV 2023 Which is Better for Learning with Noisy Labels: The Semi-supervised Method or Modeling Label Noise? ICML 2023 Diversity-enhancing Generative Network for Few-shot Hypothesis Adaptation ICML 2023 Generator Identification for Linear SDEs with Additive and Multiplicative Noise NIPS 2023 CS-Isolate: Extracting Hard Confident Examples by Content and Style Isolation NIPS 2023 Learning World Models with Identifiable Factorization NIPS 2023 ConDaFormer: Disassembled Transformer with Local Structure Enhancement for 3D Point Cloud Understanding NIPS 2023 Rethinking Class-Prior Estimation for Positive-Unlabeled Learning ICLR 2022 Counterfactual Fairness with Partially Known Causal Graph NIPS 2022 MissDAG: Causal Discovery in the Presence of Missing Data with Continuous Additive Noise Models NIPS 2022 Truncated Matrix Power Iteration for Differentiable DAG Learning NIPS 2022 Fair Classification with Instance-dependent Label Noise CLEAR 2022 CRIS: CLIP-Driven Referring Image Segmentation CVPR 2022 Alleviating Semantics Distortion in Unsupervised Low-Level Image-to-Image Translation via Structure Consistency Constraint CVPR 2022 Few-Shot Font Generation by Learning Fine-Grained Local Styles CVPR 2022 Maximum Spatial Perturbation Consistency for Unpaired Image-to-Image Translation CVPR 2022 Exploring Set Similarity for Dense Self-Supervised Representation Learning CVPR 2022 Uncertainty Quantification in Depth Estimation via Constrained Ordinal Regression ECCV 2022 Digging into Radiance Grid for Real-Time View Synthesis with Detail Preservation ECCV 2022 Sample Selection with Uncertainty of Losses for Learning with Noisy Labels ICLR 2022 Adversarial Robustness Through the Lens of Causality ICLR 2022 A Relational Intervention Approach for Unsupervised Dynamics Generalization in Model-Based Reinforcement Learning ICLR 2022 Understanding Robust Overfitting of Adversarial Training and Beyond ICML 2022 Robust Weight Perturbation for Adversarial Training IJCAI 2022 Not All Operations Contribute Equally: Hierarchical Operation-Adaptive Predictor for Neural Architecture Search ICCV 2021 Class2Simi: A Noise Reduction Perspective on Learning with Noisy Labels ICML 2021 Learning with Group Noise AAAI 2021 Domain Adaptation with Invariant Representation Learning: What Transformations to Learn? NIPS 2021 Instance-dependent Label-noise Learning under a Structural Causal Model NIPS 2021 Unaligned Image-to-Image Translation by Learning to Reweight ICCV 2021 Bridging Causality and Learning: How Do They Benefit from Each Other? IJCAI 2020 LTF: A Label Transformation Framework for Correcting Label Shift ICML 2020 Label-Noise Robust Domain Adaptation ICML 2020 Dual T: Reducing Estimation Error for Transition Matrix in Label-noise Learning NIPS 2020 Domain Adaptation as a Problem of Inference on Graphical Models NIPS 2020 Causal Discovery from Multiple Data Sets with Non-Identical Variable Sets AAAI 2020 Generative-Discriminative Complementary Learning AAAI 2020 Compressed Self-Attention for Deep Metric Learning AAAI 2020 Compressed Self-Attention for Deep Metric Learning with Low-Rank Approximation IJCAI 2020 Domain Generalization via Entropy Regularization NIPS 2020 Hard Example Generation by Texture Synthesis for Cross-domain Shape Similarity Learning NIPS 2020 Short-Term and Long-Term Context Aggregation Network for Video Inpainting ECCV 2020 Sub-center ArcFace: Boosting Face Recognition by Large-scale Noisy Web Faces ECCV 2020 Part-dependent Label Noise: Towards Instance-dependent Label Noise NIPS 2020 Likelihood-Free Overcomplete ICA and Applications In Causal Discovery NIPS 2019 Specific and Shared Causal Relation Modeling and Mechanism-Based Clustering NIPS 2019 Geometry-Aware Symmetric Domain Adaptation for Monocular Depth Estimation CVPR 2019 Twin Auxilary Classifiers GAN NIPS 2019 Geometry-Consistent Generative Adversarial Networks for One-Sided Unsupervised Domain Mapping CVPR 2019 Data-Driven Approach to Multiple-Source Domain Adaptation AISTATS 2019 Causal Discovery and Forecasting in Nonstationary Environments with State-Space Models ICML 2019 Low-Dimensional Density Ratio Estimation for Covariate Shift Correction AISTATS 2019 Learning with Biased Complementary Labels ECCV 2018 An Efficient and Provable Approach for Mixture Proportion Estimation Using Linear Independence Assumption CVPR 2018 Deep Ordinal Regression Network for Monocular Depth Estimation CVPR 2018 Modeling Dynamic Missingness of Implicit Feedback for Recommendation NIPS 2018 Deep Domain Generalization via Conditional Invariant Adversarial Networks ECCV 2018 Correcting the Triplet Selection Bias for Triplet Loss ECCV 2018 A Coarse-Fine Network for Keypoint Localization ICCV 2017 Domain Adaptation with Conditional Transferable Components ICML 2016 Causal Inference by Identification of Vector Autoregressive Processes with Hidden Components ICML 2015 Discovering Temporal Causal Relations from Subsampled Data ICML 2015