Qingsong Wen

Assemble Your Crew: Automatic Multi-agent Communication Topology Design via Autoregressive Graph Generation AAAI 2026 AutoDebias: An Automated Framework for Detecting and Mitigating Backdoor Biases in Text-to-Image Models CVPR 2026 Backdoor Collapse: Eliminating Unknown Threats Via Known Backdoor Aggregation In Language Models ACL 2026 NeuralOM: Neural Ocean Model for Subseasonal-to-Seasonal Simulation AAAI 2026 OccamVTS: Distilling Vision Models to 1% Parameters for Time Series Forecasting AAAI 2026 SafeSieve: From Heuristics to Experience in Progressive Pruning for LLM-based Multi-Agent Communication AAAI 2026 Scaling Law for Multimodal Large Language Model Supervised Fine-Tuning ACL 2026 AI-Driven Virtual Teacher for Enhanced Educational Efficiency: Leveraging Large Pretrain Models for Autonomous Error Analysis and Correction AAAI 2025 Ask-Before-Detection: Identifying and Mitigating Conformity Bias in LLM-Powered Error Detector for Math Word Problem Solutions ACL 2025 A Survey of Mathematical Reasoning in the Era of Multimodal Large Language Model: Benchmark, Method & Challenges ACL 2025 Deep Learning for Multivariate Time Series Imputation: A Survey IJCAI 2025 DynamicNER: A Dynamic, Multilingual, and Fine-Grained Dataset for LLM-based Named Entity Recognition EMNLP 2025 Knowledge Tagging with Large Language Model Based Multi-Agent System AAAI 2025 Learning to Extrapolate and Adjust: Two-Stage Meta-Learning for Concept Drift in Online Time Series Forecasting IJCAI 2025 LLM Agents for Education: Advances and Applications EMNLP 2025 MathAgent: Leveraging a Mixture-of-Math-Agent Framework for Real-World Multimodal Mathematical Error Detection ACL 2025 MME-RealWorld: Could Your Multimodal LLM Challenge High-Resolution Real-World Scenarios that are Difficult for Humans? ICLR 2025 NetSafe: Exploring the Topological Safety of Multi-agent System ACL 2025 OneForecast: A Universal Framework for Global and Regional Weather Forecasting ICML 2025 Open-CK: A Large Multi-Physics Fields Coupling benchmarks in Combustion Kinetics ICLR 2025 Position: LLMs Can be Good Tutors in English Education EMNLP 2025 Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts ICLR 2025 Time-MQA: Time Series Multi-Task Question Answering with Context Enhancement ACL 2025 Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting ICML 2025 UniEDU: Toward Unified and Efficient Large Multimodal Models for Educational Tasks EMNLP 2025 Unlocking the Power of LSTM for Long Term Time Series Forecasting AAAI 2025 UrbanVLP: Multi-Granularity Vision-Language Pretraining for Urban Socioeconomic Indicator Prediction AAAI 2025 Attractor Memory for Long-Term Time Series Forecasting: A Chaos Perspective NeurIPS 2024 AutoSurvey: Large Language Models Can Automatically Write Surveys NeurIPS 2024 BayOTIDE: Bayesian Online Multivariate Time Series Imputation with Functional Decomposition ICML 2024 CARD: Channel Aligned Robust Blend Transformer for Time Series Forecasting ICLR 2024 CulturePark: Boosting Cross-cultural Understanding in Large Language Models NeurIPS 2024 EasyTPP: Towards Open Benchmarking Temporal Point Processes ICLR 2024 Explaining Time Series via Contrastive and Locally Sparse Perturbations ICLR 2024 Generative Semi-supervised Graph Anomaly Detection NeurIPS 2024 Online GNN Evaluation Under Test-time Graph Distribution Shifts ICLR 2024 Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting ICLR 2024 Position: What Can Large Language Models Tell Us about Time Series Analysis ICML 2024 Predicting Carpark Availability in Singapore with Cross-Domain Data: A New Dataset and A Data-Driven Approach IJCAI 2024 RAGLAB: A Modular and Research-Oriented Unified Framework for Retrieval-Augmented Generation EMNLP 2024 RobustTSF: Towards Theory and Design of Robust Time Series Forecasting with Anomalies ICLR 2024 Task-oriented Time Series Imputation Evaluation via Generalized Representers NeurIPS 2024 Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting NeurIPS 2024 Time-LLM: Time Series Forecasting by Reprogramming Large Language Models ICLR 2024 Time-MMD: Multi-Domain Multimodal Dataset for Time Series Analysis NeurIPS 2024 ADGym: Design Choices for Deep Anomaly Detection NeurIPS 2023 AHPA: Adaptive Horizontal Pod Autoscaling Systems on Alibaba Cloud Container Service for Kubernetes AAAI 2023 AirFormer: Predicting Nationwide Air Quality in China with Transformers AAAI 2023 eForecaster: Unifying Electricity Forecasting with Robust, Flexible, and Explainable Machine Learning Algorithms AAAI 2023 OneNet: Enhancing Time Series Forecasting Models under Concept Drift by Online Ensembling NeurIPS 2023 Transformers in Time Series: A Survey IJCAI 2023 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 Towards Out-of-Distribution Sequential Event Prediction: A Causal Treatment NeurIPS 2022 Time Series Data Augmentation for Deep Learning: A Survey IJCAI 2021 RobustSTL: A Robust Seasonal-Trend Decomposition Algorithm for Long Time Series AAAI 2019 RobustTrend: A Huber Loss with a Combined First and Second Order Difference Regularization for Time Series Trend Filtering IJCAI 2019