| 2026 | ACL | Mem-Gallery: Benchmarking Multimodal Long-Term Conversational Memory for MLLM Agents. | Yuanchen Bei, Tianxin Wei, Xuying Ning, Yanjun Zhao, Zhining Liu, Xiao Lin, Yada Zhu, Hendrik F. Hamann, Jingrui He, Hanghang Tong |
| 2026 | ACL | RAG over Tables: Hierarchical Memory Index, Multi-Stage Retrieval, and Benchmarking. | Jiaru Zou, Dongqi Fu, Sirui Chen, Xinrui He, Zihao Li, Yada Zhu, Jiawei Han, Jingrui He |
| 2026 | EACL | UniToolBench: A Benchmark for Tool-Augmented LLMs in Cross-Domain, Universal Task Automation. | Xiaojie Guo, Yang Zhang, Bing Zhang, Ryo Kawahara, Mikio Takeuchi, Yada Zhu |
| 2025 | ACL | PLAY2PROMPT: Zero-shot Tool Instruction Optimization for LLM Agents via Tool Play. | Wei Fang, Yang Zhang, Kaizhi Qian, James R. Glass, Yada Zhu |
| 2025 | CIKM | ClimateBench-M: A Multi-Modal Climate Data Benchmark with a Simple Generative Method. | Dongqi Fu, Yada Zhu, Zhining Liu, Lecheng Zheng, Xiao Lin, Zihao Li, Liri Fang, Katherine Tieu, Onkar Bhardwaj, Kommy Weldemariam, Hanghang Tong, Hendrik F. Hamann, Jingrui He |
| 2025 | ICLR | Reasoning of Large Language Models over Knowledge Graphs with Super-Relations. | Song Wang, Junhong Lin, Xiaojie Guo, Julian Shun, Jundong Li, Yada Zhu |
| 2025 | ICML | Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting. | Zhining Liu, Ze Yang, Xiao Lin, Ruizhong Qiu, Tianxin Wei, Yada Zhu, Hendrik F. Hamann, Jingrui He, Hanghang Tong |
| 2025 | KDD | When Heterophily Meets Heterogeneity: Challenges and a New Large-Scale Graph Benchmark. | Junhong Lin, Xiaojie Guo, Shuaicheng Zhang, Yada Zhu, Julian Shun |
| 2025 | NAACL | Evaluating Large Language Models with Enterprise Benchmarks. | Bing Zhang, Mikio Takeuchi, Ryo Kawahara, Shubhi Asthana, Md. Maruf Hossain, Guang-Jie Ren, Kate Soule, Yifan Mai, Yada Zhu |
| 2024 | AAAI | Sterling: Synergistic Representation Learning on Bipartite Graphs. | Baoyu Jing, Yuchen Yan, Kaize Ding, Chanyoung Park, Yada Zhu, Huan Liu, Hanghang Tong |
| 2024 | ACL | Self-Specialization: Uncovering Latent Expertise within Large Language Models. | Junmo Kang, Hongyin Luo, Yada Zhu, Jacob A. Hansen, James R. Glass, David D. Cox, Alan Ritter, Rogrio Feris, Leonid Karlinsky |
| 2024 | ICDE | Fairgen: Towards Fair Graph Generation. | Lecheng Zheng, Dawei Zhou, Hanghang Tong, Jiejun Xu, Yada Zhu, Jingrui He |
| 2024 | ICLR | Neural Active Learning Beyond Bandits. | Yikun Ban, Ishika Agarwal, Ziwei Wu, Yada Zhu, Kommy Weldemariam, Hanghang Tong, Jingrui He |
| 2024 | ICLR | Adversarial Attacks on Fairness of Graph Neural Networks. | Binchi Zhang, Yushun Dong, Chen Chen, Yada Zhu, Minnan Luo, Jundong Li |
| 2024 | ICML | Class-Imbalanced Graph Learning without Class Rebalancing. | Zhining Liu, Ruizhong Qiu, Zhichen Zeng, Hyunsik Yoo, David Zhou, Zhe Xu, Yada Zhu, Kommy Weldemariam, Jingrui He, Hanghang Tong |
| 2024 | ICML | Learning Optimal Projection for Forecast Reconciliation of Hierarchical Time Series. | Asterios Tsiourvas, Wei Sun, Georgia Perakis, Pin-Yu Chen, Yada Zhu |
| 2024 | KDD | AIM: Attributing, Interpreting, Mitigating Data Unfairness. | Zhining Liu, Ruizhong Qiu, Zhichen Zeng, Yada Zhu, Hendrik F. Hamann, Hanghang Tong |
| 2024 | KDD | Mastering Long-Tail Complexity on Graphs: Characterization, Learning, and Generalization. | Haohui Wang, Baoyu Jing, Kaize Ding, Yada Zhu, Wei Cheng, Si Zhang, Yonghui Fan, Liqing Zhang, Dawei Zhou |
| 2024 | NAACL | Paraphrase and Solve: Exploring and Exploiting the Impact of Surface Form on Mathematical Reasoning in Large Language Models. | Yue Zhou, Yada Zhu, Diego Antognini, Yoon Kim, Yang Zhang |
| 2023 | KDD | Networked Time Series Imputation via Position-aware Graph Enhanced Variational Autoencoders. | Dingsu Wang, Yuchen Yan, Ruizhong Qiu, Yada Zhu, Kaiyu Guan, Andrew Margenot, Hanghang Tong |
| 2023 | SDM | Fairness-aware Multi-view Clustering. | Lecheng Zheng, Yada Zhu, Jingrui He |
| 2022 | KDD | Contrastive Learning with Complex Heterogeneity. | Lecheng Zheng, Jinjun Xiong, Yada Zhu, Jingrui He |
| 2022 | WWW | Adversarial Graph Contrastive Learning with Information Regularization. | Shengyu Feng, Baoyu Jing, Yada Zhu, Hanghang Tong |
| 2022 | WSDM | Structure Meets Sequences: Predicting Network of Co-evolving Sequences. | Yaojing Wang, Yuan Yao, Feng Xu, Yada Zhu, Hanghang Tong |
| 2021 | AAAI | Outlier Impact Characterization for Time Series Data. | Jianbo Li, Lecheng Zheng, Yada Zhu, Jingrui He |
| 2021 | ACL | On Sample Based Explanation Methods for NLP: Faithfulness, Efficiency and Semantic Evaluation. | Wei Zhang, Ziming Huang, Yada Zhu, Guangnan Ye, Xiaodong Cui, Fan Zhang |
| 2021 | WWW | Network of Tensor Time Series. | Baoyu Jing, Hanghang Tong, Yada Zhu |
| 2020 | AAAI | Towards Fine-Grained Temporal Network Representation via Time-Reinforced Random Walk. | Zhining Liu, Dawei Zhou, Yada Zhu, Jinjie Gu, Jingrui He |
| 2020 | AAAI | Reinforcement-Learning Based Portfolio Management with Augmented Asset Movement Prediction States. | Yunan Ye, Hengzhi Pei, Boxin Wang, Pin-Yu Chen, Yada Zhu, Ju Xiao, Bo Li |
| 2020 | IJCAI | Task-Based Learning via Task-Oriented Prediction Network with Applications in Finance. | Di Chen, Yada Zhu, Xiaodong Cui, Carla P. Gomes |
| 2020 | WWW | Domain Adaptive Multi-Modality Neural Attention Network for Financial Forecasting. | Dawei Zhou, Lecheng Zheng, Yada Zhu, Jianbo Li, Jingrui He |
| 2019 | CIKM | Robust Embedded Deep K-means Clustering. | Rui Zhang, Hanghang Tong, Yinglong Xia, Yada Zhu |
| 2018 | IJCAI | A Local Algorithm for Product Return Prediction in E-Commerce. | Yada Zhu, Jianbo Li, Jingrui He, Brian Leo Quanz, Ajay A. Deshpande |
| 2018 | KDD | E-tail Product Return Prediction via Hypergraph-based Local Graph Cut. | Jianbo Li, Jingrui He, Yada Zhu |
| 2017 | ICDM | HiMuV: Hierarchical Framework for Modeling Multi-modality Multi-resolution Data. | Jianbo Li, Jingrui He, Yada Zhu |
| 2017 | KDD | Local Algorithm for User Action Prediction Towards Display Ads. | Hongxia Yang, Yada Zhu, Jingrui He |
| 2017 | SDM | Learning from Multi-Modality Multi-Resolution Data: an Optimization Approach. | Yada Zhu, Jianbo Li, Jingrui He |
| 2015 | ICCAD | Modern Big Data Analytics for "Old-fashioned" Semiconductor Industry Applications. | Yada Zhu, Jinjun Xiong |
| 2015 | KDD | Co-Clustering based Dual Prediction for Cargo Pricing Optimization. | Yada Zhu, Hongxia Yang, Jingrui He |
| 2014 | ICDM | Co-Clustering Structural Temporal Data with Applications to Semiconductor Manufacturing. | Yada Zhu, Jingrui He |
| 2012 | AAAI | Hierarchical Modeling with Tensor Inputs. | Yada Zhu, Jingrui He, Rick Lawrence |
| 2012 | ICDM | Hierarchical Multi-task Learning with Application to Wafer Quality Prediction. | Jingrui He, Yada Zhu |