Fan Zhou

Modality-Balanced Collaborative Distillation for Multi-Modal Domain Generalization AAAI 2026 Causally-Grounded Dual-Path Attention Intervention for Object Hallucination Mitigation in LVLMs AAAI 2026 Shedding the Facades, Connecting the Domains: Detecting Shifting Multimodal Hate Video with Test-Time Adaptation AAAI 2026 Beyond Graph Priors: A Co-Evolving Framework Under Uncertainty for Enterprise Resilience Assessment AAAI 2026 Learning to Curate Context: Jointly Optimizing Retrieval and Prediction for Multimodal Social Media Popularity AAAI 2026 Breach in the Shield: Unveiling the Vulnerabilities of Large Language Models EACL 2026 Enhancing Prediction Performance through Influence Measure ICLR 2025 Programming Every Example: Lifting Pre-training Data Quality Like Experts at Scale ICML 2025 Free-MoRef: Instantly Multiplexing Context Perception Capabilities of Video-MLLMs within Single Inference ICCV 2025 You Only Query Twice: Multimodal Rumor Detection via Evidential Evaluation from Dual Perspectives COLING 2025 Structure-aware Domain Knowledge Injection for Large Language Models ACL 2025 Diving into Self-Evolving Training for Multimodal Reasoning ICML 2025 Redundancy Undermines the Trustworthiness of Self-Interpretable GNNs ICML 2025 Retrieval-Augmented Dynamic Prompt Tuning for Incomplete Multimodal Learning AAAI 2025 In-context Prompt-augmented Micro-video Popularity Prediction AAAI 2025 Improving Multimodal Social Media Popularity Prediction via Selective Retrieval Knowledge Augmentation AAAI 2025 Borrowing Eyes for the Blind Spot: Overcoming Data Scarcity in Malicious Video Detection via Cross-Domain Retrieval Augmentation ICCV 2025 Natural Evolution-based Dual-Level Aggregation for Temporal Knowledge Graph Reasoning EMNLP 2024 EasyTPP: Towards Open Benchmarking Temporal Point Processes ICLR 2024 Lemur: Harmonizing Natural Language and Code for Language Agents ICLR 2024 Continuous Invariance Learning ICLR 2024 Enhancing LLM’s Cognition via Structurization NIPS 2024 OlympicArena: Benchmarking Multi-discipline Cognitive Reasoning for Superintelligent AI NIPS 2024 GMP-AR: Granularity Message Passing and Adaptive Reconciliation for Temporal Hierarchy Forecasting AAAI 2024 Generalizing across Temporal Domains with Koopman Operators AAAI 2024 Interpreting Temporal Knowledge Graph Reasoning (Student Abstract) AAAI 2024 Spatial-Temporal Augmentation for Crime Prediction (Student Abstract) AAAI 2024 Disentanglement-Guided Spatial-Temporal Graph Neural Network for Metro Flow Forecasting (Student Abstract) AAAI 2024 Shallow Diffusion for Fast Speech Enhancement (Student Abstract) AAAI 2024 Graph Anomaly Detection with Diffusion Model-Based Graph Enhancement (Student Abstract) AAAI 2024 Decoupling User Relationships Guides Information Diffusion Prediction (Student Abstract) AAAI 2024 Amplifying Diversity and Quality in Commonsense Knowledge Graph Completion (Student Abstract) AAAI 2024 Biases Mitigation and Expressiveness Preservation in Language Models: A Comprehensive Pipeline (Student Abstract) AAAI 2024 Dissecting Human and LLM Preferences ACL 2024 Enhancing Fine-Grained Urban Flow Inference via Incremental Neural Operator IJCAI 2024 Revitalizing Real Image Deraining via a Generic Paradigm towards Multiple Rainy Patterns IJCAI 2024 Two-way Deconfounder for Off-policy Evaluation in Causal Reinforcement Learning NIPS 2024 MarvelOVD: Marrying Object Recognition and Vision-Language Models for Robust Open-Vocabulary Object Detection ECCV 2024 Rethinking Out-of-Distribution Detection on Imbalanced Data Distribution NIPS 2024 Over-parameterized Deep Nonparametric Regression for Dependent Data with Its Applications to Reinforcement Learning JMLR 2023 Gap Minimization for Knowledge Sharing and Transfer JMLR 2023 Causal-Debias: Unifying Debiasing in Pretrained Language Models and Fine-tuning via Causal Invariant Learning ACL 2023 Universal Bias Reduction in Estimation of Smooth Additive Function in High Dimensions ALT 2023 Adversarial Learning of Distributional Reinforcement Learning ICML 2023 Variance Control for Distributional Reinforcement Learning ICML 2023 Somali Information Retrieval Corpus: Bridging the Gap between Query Translation and Dedicated Language Resources EMNLP 2023 Open Anomalous Trajectory Recognition via Probabilistic Metric Learning IJCAI 2023 Optimal Treatment Allocation for Efficient Policy Evaluation in Sequential Decision Making NIPS 2023 Enhancing Knowledge Transfer for Task Incremental Learning with Data-free Subnetwork NIPS 2023 DOSE: Diffusion Dropout with Adaptive Prior for Speech Enhancement NIPS 2023 De-biased Teacher: Rethinking IoU Matching for Semi-supervised Object Detection AAAI 2023 Overcoming Forgetting in Fine-Grained Urban Flow Inference via Adaptive Knowledge Replay AAAI 2023 Foresee What You Will Learn: Data Augmentation for Domain Generalization in Non-stationary Environment AAAI 2023 SLOTH: Structured Learning and Task-Based Optimization for Time Series Forecasting on Hierarchies AAAI 2023 Revisiting Denoising Diffusion Probabilistic Models for Speech Enhancement: Condition Collapse, Efficiency and Refinement AAAI 2023 CasODE: Modeling Irregular Information Cascade via Neural Ordinary Differential Equations (Student Abstract) AAAI 2023 Exploring Hypergraph of Earnings Call for Risk Prediction (Student Abstract) AAAI 2023 Mobility Prediction via Sequential Trajectory Disentanglement (Student Abstract) AAAI 2023 Debiasing Intrinsic Bias and Application Bias Jointly via Invariant Risk Minimization (Student Abstract) AAAI 2023 A Probabilistic Graph Diffusion Model for Source Localization (Student Abstract) AAAI 2023 Learning Dynamic Temporal Relations with Continuous Graph for Multivariate Time Series Forecasting (Student Abstract) AAAI 2023 DyCVAE: Learning Dynamic Causal Factors for Non-stationary Series Domain Generalization (Student Abstract) AAAI 2023 Directional diffusion models for graph representation learning NIPS 2023 Language Models Can Improve Event Prediction by Few-Shot Abductive Reasoning NIPS 2023 Table Pre-training: A Survey on Model Architectures, Pre-training Objectives, and Downstream Tasks IJCAI 2022 Learning Latent Seasonal-Trend Representations for Time Series Forecasting NIPS 2022 Dynamic Manifold Learning for Land Deformation Forecasting AAAI 2022 PrEF: Probabilistic Electricity Forecasting via Copula-Augmented State Space Model AAAI 2022 Learning Contrastive Multi-View Graphs for Recommendation (Student Abstract) AAAI 2022 A Probabilistic Framework for Land Deformation Prediction (Student Abstract) AAAI 2022 Conditional Collaborative Filtering Process for Top-K Recommender System (Student Abstract) AAAI 2022 Large-Scale IP Usage Identification via Deep Ensemble Learning (Student Abstract) AAAI 2022 Fine-Grained Urban Flow Inference via Normalizing Flow (Student Abstract) AAAI 2022 Linking Transformer to Hawkes Process for Information Cascade Prediction (Student Abstract) AAAI 2022 Exploring Image Regions Not Well Encoded by an INN AISTATS 2022 TaCube: Pre-computing Data Cubes for Answering Numerical-Reasoning Questions over Tabular Data EMNLP 2022 Quantification and Analysis of Layer-wise and Pixel-wise Information Discarding ICML 2022 Double-Check Soft Teacher for Semi-Supervised Object Detection IJCAI 2022 Principal Subspace Estimation Under Information Diffusion AISTATS 2021 Multi-task Learning by Leveraging the Semantic Information AAAI 2021 Forecasting Reservoir Inflow via Recurrent Neural ODEs AAAI 2021 Non-decreasing Quantile Function Network with Efficient Exploration for Distributional Reinforcement Learning IJCAI 2021 Rate-Optimal Subspace Estimation on Random Graphs NIPS 2021 Land Deformation Prediction via Slope-Aware Graph Neural Networks AAAI 2021 Overcoming Catastrophic Forgetting in Graph Neural Networks with Experience Replay AAAI 2021 Optimal Estimation of High Dimensional Smooth Additive Function Based on Noisy Observations ICML 2021 Deep Active Learning: Unified and Principled Method for Query and Training AISTATS 2020 Enhancing Urban Flow Maps via Neural ODEs IJCAI 2020 Non-Crossing Quantile Regression for Distributional Reinforcement Learning NIPS 2020 Relational State-Space Model for Stochastic Multi-Object Systems ICLR 2020 Interpreting Twitter User Geolocation ACL 2020 Interpretable Operational Risk Classification with Semi-Supervised Variational Autoencoder ACL 2020 The Sup-norm Perturbation of HOSVD and Low Rank Tensor Denoising JMLR 2019 Graph-Based Semi-Supervised Learning with Non-ignorable Non-response NIPS 2019 On the Convergence Properties of a K-step Averaging Stochastic Gradient Descent Algorithm for Nonconvex Optimization IJCAI 2018 Trajectory-User Linking via Variational AutoEncoder IJCAI 2018 Identifying Human Mobility via Trajectory Embeddings IJCAI 2017