Mingming Gong

Beyond DAGs: A Latent Partial Causal Model for Multimodal Learning

Causal Discovery in the Wild: A Voting-Theoretic Ensemble Approach

Agent-Centric Personalized Multiple Clustering with Multi-Modal LLMs

I Predict Therefore I Am: Is Next Token Prediction Enough to Learn Human-Interpretable Concepts from Data?

Treatment Responder Classification with Abstention

FedReLa: Imbalanced Federated Learning via Re-Labeling

AdLift: Lifting Adversarial Perturbations to Safeguard 3D Gaussian Splatting Assets Against Instruction-Driven Editing

TimeLAVA: Learning-Agnostic Valuation for Time Series Data

Unifying Counterfactual Data Augmentation and Architectural Inductive Biases in Offline Reinforcement Learning

A Kernel Distribution Closeness Testing

Towards Identifiable Latent Additive Noise Models

Editing by Reconstruction: Background Preservation for Instruction-based Autoregressive Image Editing

Estimating the Effects of Sample Training Orders for Large Language Models without Retraining

Mitigating Hidden Confounding by Progressive Confounder Imputation via Large Language Models

On the Identification of Temporal Causal Representation with Instantaneous Dependence

Optimal Transport for Time Series Imputation

Analytic DAG Constraints for Differentiable DAG Learning

Practical Kernel Selection for Kernel-based Conditional Independence Test

Counterfactual Implicit Feedback Modeling

Detecting Generated Images by Fitting Natural Image Distributions

Towards Accurate Time Series Forecasting via Implicit Decoding

A Robust Method to Discover Causal or Anticausal Relation

Learning Imbalanced Data with Beneficial Label Noise

A Skewness-Based Criterion for Addressing Heteroscedastic Noise in Causal Discovery

MLLM-For3D: Adapting Multimodal Large Language Model for 3D Reasoning Segmentation

Decentralized Dynamic Cooperation of Personalized Models for Federated Continual Learning

MissScore: High-Order Score Estimation in the Presence of Missing Data

Enhancing Treatment Effect Estimation via Active Learning: A Counterfactual Covering Perspective

Extracting Rare Dependence Patterns via Adaptive Sample Reweighting

LoCA: Location-Aware Cosine Adaptation for Parameter-Efficient Fine-Tuning

Beyond DAGs: A Latent Partial Causal Model for Multimodal Learning

Projection Pursuit Density Ratio Estimation

Learning Imbalanced Data with Beneficial Label Noise

Turning Challenges into Opportunities: How Distribution Shifts Enhance Identifiability in Causal Representation Learning

EM-DARTS: Preventing Performance Collapse in Differentiable Architecture Search with The Edge Mutation Mechanism

Revisit Non-parametric Two-sample Testing as a Semi-supervised Learning Problem

Counterfactual Delayed Feedback Learning

Practical Kernel Learning for Kernel-based Conditional Independent Test

MMA: Benchmarking Multi-Modal Large Language Model in Ambiguity Contexts

MissScore: High-Order Score Estimation in the Presence of Missing Data

Sampling Process Brings Additional Bias for Debiased Recommendation

Consistency Verification for Detecting AI-Generated Images