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ORCIDMeng Jiang 0001
Person information
- affiliation: University of Notre Dame, Department of Computer Science and Engineering, IN, USA
- affiliation (2015 - 2017): University of Illinois at Urbana-Champaign, Department of Computer Science, Urbana, IL, USA
- affiliation (PhD 2015): Tsinghua University, Department of Computer Science and Technology, Beijing, China
- affiliation (2012 - 2013): Carnegie Mellon University, Department of Computer Science, Pittsburgh, PA, USA
Other persons with the same name
- Meng Jiang — disambiguation page
- Meng Jiang 0002 — Rochester Institute of Technology, Department of Computer Engineering, NY, USA
- Meng Jiang 0003 — University of Electronic Science and Technology of China, School of Electronic Engineering, China
- Meng Jiang 0004 — Shandong Agricultural University, Taian, China
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2020 – today
- 2025
[c115]Annalisa Szymanski, Noah Ziems, Heather A. Eicher-Miller, Toby Jia-Jun Li, Meng Jiang, Ronald A. Metoyer:
Limitations of the LLM-as-a-Judge Approach for Evaluating LLM Outputs in Expert Knowledge Tasks. IUI 2025: 952-966- [i98]Zhaoxuan Tan, Zinan Zeng, Qingkai Zeng, Zhenyu Wu, Zheyuan Liu, Fengran Mo, Meng Jiang:
Can Large Language Models Understand Preferences in Personalized Recommendation? CoRR abs/2501.13391 (2025) - [i97]Bo Ni, Zheyuan Liu, Leyao Wang, Yongjia Lei, Yuying Zhao, Xueqi Cheng, Qingkai Zeng, Luna Dong, Yinglong Xia, Krishnaram Kenthapadi, Ryan A. Rossi, Franck Dernoncourt, Md. Mehrab Tanjim, Nesreen K. Ahmed, Xiaorui Liu, Wenqi Fan, Erik Blasch, Yu Wang, Meng Jiang, Tyler Derr:
Towards Trustworthy Retrieval Augmented Generation for Large Language Models: A Survey. CoRR abs/2502.06872 (2025) - [i96]Zhihan Zhang, Shiyang Li, Zixuan Zhang, Xin Liu, Haoming Jiang, Xianfeng Tang, Yifan Gao, Zheng Li, Haodong Wang, Zhaoxuan Tan, Yichuan Li, Qingyu Yin, Bing Yin, Meng Jiang:
IHEval: Evaluating Language Models on Following the Instruction Hierarchy. CoRR abs/2502.08745 (2025) - [i95]Hy Dang, Yuwen Lu, Jason Spicer, Tamara Kay, Di Yang, Yang Yang, Jay Brockman, Meng Jiang, Toby Jia-Jun Li:
Uncovering Disparities in Rideshare Drivers Earning and Work Patterns: A Case Study of Chicago. CoRR abs/2502.08893 (2025) - [i94]Zheyuan Liu, Guangyao Dou, Xiangchi Yuan, Chunhui Zhang, Zhaoxuan Tan, Meng Jiang:
Modality-Aware Neuron Pruning for Unlearning in Multimodal Large Language Models. CoRR abs/2502.15910 (2025) - [i93]Bang Nguyen, Tingting Du, Mengxia Yu, Lawrence Angrave, Meng Jiang:
QG-SMS: Enhancing Test Item Analysis via Student Modeling and Simulation. CoRR abs/2503.05888 (2025) - [i92]Yining Lu, Noah Ziems, Hy Dang, Meng Jiang:
Optimizing Decomposition for Optimal Claim Verification. CoRR abs/2503.15354 (2025) - [i91]Jiaxin Xu, Gang Liu, Ruilan Guo, Meng Jiang, Tengfei Luo:
POINT2: A Polymer Informatics Training and Testing Database. CoRR abs/2503.23491 (2025) - 2024
- [b1]Meng Jiang, Bill Yuchen Lin, Shuohang Wang, Yichong Xu, Wenhao Yu, Chenguang Zhu:
Knowledge-augmented Methods for Natural Language Processing. Springer Briefs in Computer Science, Springer 2024, ISBN 978-981-97-0749-2, pp. 1-95 - [j35]Xin Luna Dong, Meng Jiang, Kai Sun, Xiao Yang:
Letter from the Special Issue Editor. IEEE Data Eng. Bull. 48(4): 2 (2024) - [j34]Meng Jiang
:
Transfer Learning across Graph Convolutional Networks: Methods, Theory, and Applications. ACM Trans. Knowl. Discov. Data 18(1): 24:1-24:23 (2024) - [j33]Gang Liu, Eric Inae, Tengfei Luo, Meng Jiang:
Rationalizing Graph Neural Networks with Data Augmentation. ACM Trans. Knowl. Discov. Data 18(4): 86:1-86:23 (2024) - [j32]Bowen Jin, Gang Liu, Chi Han, Meng Jiang, Heng Ji, Jiawei Han:
Large Language Models on Graphs: A Comprehensive Survey. IEEE Trans. Knowl. Data Eng. 36(12): 8622-8642 (2024) - [c114]Zhenyu Wu, Meng Jiang, Chao Shen:
Get an A in Math: Progressive Rectification Prompting. AAAI 2024: 19288-19296 - [c113]Zheyuan Liu, Guangyao Dou, Zhaoxuan Tan, Yijun Tian, Meng Jiang:
Towards Safer Large Language Models through Machine Unlearning. ACL (Findings) 2024: 1817-1829 - [c112]Zhihan Zhang, Dong-Ho Lee, Yuwei Fang, Wenhao Yu, Mengzhao Jia, Meng Jiang, Francesco Barbieri:
PLUG: Leveraging Pivot Language in Cross-Lingual Instruction Tuning. ACL (1) 2024: 7025-7046 - [c111]Ziyi Kou, Yijun Tian, Meng Jiang, Xiangliang Zhang:
FaDE: A Face Segment Driven Identity Anonymization Framework For Fair Face Recognition. CIKM 2024: 1121-1131 - [c110]Qingkai Zeng, Yuyang Bai, Zhaoxuan Tan, Shangbin Feng, Zhenwen Liang, Zhihan Zhang, Meng Jiang:
Chain-of-Layer: Iteratively Prompting Large Language Models for Taxonomy Induction from Limited Examples. CIKM 2024: 3093-3102 - [c109]Ruiyang Qin, Jun Xia, Zhenge Jia, Meng Jiang, Ahmed Abbasi, Peipei Zhou, Jingtong Hu, Yiyu Shi:
Enabling On-Device Large Language Model Personalization with Self-Supervised Data Selection and Synthesis. DAC 2024: 29:1-29:6 - [c108]Zhaoxuan Tan, Zheyuan Liu, Meng Jiang:
Personalized Pieces: Efficient Personalized Large Language Models through Collaborative Efforts. EMNLP 2024: 6459-6475 - [c107]Zhaoxuan Tan, Qingkai Zeng, Yijun Tian, Zheyuan Liu, Bing Yin, Meng Jiang:
Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning. EMNLP 2024: 6476-6491 - [c106]Zhenyu Wu, Qingkai Zeng, Zhihan Zhang, Zhaoxuan Tan, Chao Shen, Meng Jiang:
Large Language Models Can Self-Correct with Key Condition Verification. EMNLP 2024: 12846-12867 - [c105]Bang Nguyen, Mengxia Yu, Yun Huang, Meng Jiang:
Reference-based Metrics Disprove Themselves in Question Generation. EMNLP (Findings) 2024: 13651-13666 - [c104]Noah Ziems, Zhihan Zhang, Meng Jiang:
TOWER: Tree Organized Weighting for Evaluating Complex Instructions. EMNLP (Findings) 2024: 13803-13810 - [c103]Zhihan Zhang, Tao Ge, Zhenwen Liang, Wenhao Yu, Dian Yu, Mengzhao Jia, Dong Yu, Meng Jiang:
Learn Beyond The Answer: Training Language Models with Reflection for Mathematical Reasoning. EMNLP 2024: 14720-14738 - [c102]Ziyi Kou, Shichao Pei, Meng Jiang, Xiangliang Zhang:
RAt: Injecting Implicit Bias for Text-To-Image Prompt Refinement Models. EMNLP 2024: 20561-20570 - [c101]Yue Huang, Lichao Sun, Haoran Wang, Siyuan Wu, Qihui Zhang, Yuan Li, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Hanchi Sun, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bertie Vidgen, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, Joaquin Vanschoren, John C. Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yong Chen, Yue Zhao:
Position: TrustLLM: Trustworthiness in Large Language Models. ICML 2024 - [c100]Zhenyu Wu, Chao Shen, Meng Jiang:
Instructing Large Language Models to Identify and Ignore Irrelevant Conditions. NAACL-HLT 2024: 6799-6819 - [c99]Yilun Jin, Zheng Li, Chenwei Zhang, Tianyu Cao, Yifan Gao, Pratik Jayarao, Mao Li, Xin Liu, Ritesh Sarkhel, Xianfeng Tang, Haodong Wang, Zhengyang Wang, Wenju Xu, Jingfeng Yang, Qingyu Yin, Xian Li, Priyanka Nigam, Yi Xu, Kai Chen, Qiang Yang, Meng Jiang, Bing Yin:
Shopping MMLU: A Massive Multi-Task Online Shopping Benchmark for Large Language Models. NeurIPS 2024 - [i90]Lichao Sun, Yue Huang, Haoran Wang, Siyuan Wu, Qihui Zhang, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, John C. Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yue Zhao:
TrustLLM: Trustworthiness in Large Language Models. CoRR abs/2401.05561 (2024) - [i89]Gang Liu, Jiaxin Xu, Tengfei Luo, Meng Jiang:
Inverse Molecular Design with Multi-Conditional Diffusion Guidance. CoRR abs/2401.13858 (2024) - [i88]Zhaoxuan Tan, Qingkai Zeng, Yijun Tian, Zheyuan Liu, Bing Yin, Meng Jiang:
Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning. CoRR abs/2402.04401 (2024) - [i87]Qingkai Zeng, Yuyang Bai, Zhaoxuan Tan, Shangbin Feng, Zhenwen Liang, Zhihan Zhang, Meng Jiang:
Chain-of-Layer: Iteratively Prompting Large Language Models for Taxonomy Induction from Limited Examples. CoRR abs/2402.07386 (2024) - [i86]Zheyuan Liu, Guangyao Dou, Zhaoxuan Tan, Yijun Tian, Meng Jiang:
Towards Safer Large Language Models through Machine Unlearning. CoRR abs/2402.10058 (2024) - [i85]Yuxuan Kuang, Hai Lin, Meng Jiang:
OpenFMNav: Towards Open-Set Zero-Shot Object Navigation via Vision-Language Foundation Models. CoRR abs/2402.10670 (2024) - [i84]Bang Nguyen, Mengxia Yu, Yun Huang, Meng Jiang:
Reference-based Metrics Disprove Themselves in Question Generation. CoRR abs/2403.12242 (2024) - [i83]Zhenyu Wu, Chao Shen, Meng Jiang:
Instructing Large Language Models to Identify and Ignore Irrelevant Conditions. CoRR abs/2403.12744 (2024) - [i82]Mengzhao Jia, Zhihan Zhang, Wenhao Yu, Fangkai Jiao, Meng Jiang:
Describe-then-Reason: Improving Multimodal Mathematical Reasoning through Visual Comprehension Training. CoRR abs/2404.14604 (2024) - [i81]Zhenyu Wu, Qingkai Zeng, Zhihan Zhang, Zhaoxuan Tan, Chao Shen, Meng Jiang:
Large Language Models Can Self-Correct with Minimal Effort. CoRR abs/2405.14092 (2024) - [i80]Ruiyang Qin, Dancheng Liu, Zheyu Yan, Zhaoxuan Tan, Zixuan Pan, Zhenge Jia, Meng Jiang, Ahmed Abbasi, Jinjun Xiong, Yiyu Shi:
Empirical Guidelines for Deploying LLMs onto Resource-constrained Edge Devices. CoRR abs/2406.03777 (2024) - [i79]Zhaoxuan Tan, Zheyuan Liu, Meng Jiang:
Personalized Pieces: Efficient Personalized Large Language Models through Collaborative Efforts. CoRR abs/2406.10471 (2024) - [i78]Zhihan Zhang, Zhenwen Liang, Wenhao Yu, Dian Yu, Mengzhao Jia, Dong Yu, Meng Jiang:
Learn Beyond The Answer: Training Language Models with Reflection for Mathematical Reasoning. CoRR abs/2406.12050 (2024) - [i77]Gang Liu, Srijit Seal, John Arevalo, Zhenwen Liang, Anne E. Carpenter, Meng Jiang, Shantanu Singh:
Learning Molecular Representation in a Cell. CoRR abs/2406.12056 (2024) - [i76]Yuwen Lu, Meng Chen, Qi Zhao, Victor V. Cox, Yang Yang, Meng Jiang, Jay Brockman, Tamara Kay, Toby Jia-Jun Li:
Crepe: A Mobile Screen Data Collector Using Graph Query. CoRR abs/2406.16173 (2024) - [i75]Zheyuan Liu, Guangyao Dou, Zhaoxuan Tan, Yijun Tian, Meng Jiang:
Machine Unlearning in Generative AI: A Survey. CoRR abs/2407.20516 (2024) - [i74]Qingkai Zeng, Yuyang Bai, Zhaoxuan Tan, Zhenyu Wu, Shangbin Feng, Meng Jiang:
CodeTaxo: Enhancing Taxonomy Expansion with Limited Examples via Code Language Prompts. CoRR abs/2408.09070 (2024) - [i73]Mengzhao Jia, Wenhao Yu, Kaixin Ma, Tianqing Fang, Zhihan Zhang, Siru Ouyang, Hongming Zhang, Meng Jiang, Dong Yu:
Leopard: A Vision Language Model For Text-Rich Multi-Image Tasks. CoRR abs/2410.01744 (2024) - [i72]Noah Ziems, Zhihan Zhang, Meng Jiang:
TOWER: Tree Organized Weighting for Evaluating Complex Instructions. CoRR abs/2410.06089 (2024) - [i71]Zhenyu Wu, Qingkai Zeng, Zhihan Zhang, Zhaoxuan Tan, Chao Shen, Meng Jiang:
Enhancing Mathematical Reasoning in LLMs by Stepwise Correction. CoRR abs/2410.12934 (2024) - [i70]Zifeng Zhu, Mengzhao Jia, Zhihan Zhang, Lang Li, Meng Jiang:
MultiChartQA: Benchmarking Vision-Language Models on Multi-Chart Problems. CoRR abs/2410.14179 (2024) - [i69]Annalisa Szymanski, Noah Ziems, Heather A. Eicher-Miller, Toby Jia-Jun Li, Meng Jiang, Ronald A. Metoyer:
Limitations of the LLM-as-a-Judge Approach for Evaluating LLM Outputs in Expert Knowledge Tasks. CoRR abs/2410.20266 (2024) - [i68]Yilun Jin, Zheng Li, Chenwei Zhang, Tianyu Cao, Yifan Gao, Pratik Jayarao, Mao Li, Xin Liu, Ritesh Sarkhel, Xianfeng Tang, Haodong Wang, Zhengyang Wang, Wenju Xu, Jingfeng Yang, Qingyu Yin, Xian Li, Priyanka Nigam, Yi Xu, Kai Chen, Qiang Yang, Meng Jiang, Bing Yin:
Shopping MMLU: A Massive Multi-Task Online Shopping Benchmark for Large Language Models. CoRR abs/2410.20745 (2024) - [i67]Zheyuan Liu, Guangyao Dou, Mengzhao Jia, Zhaoxuan Tan, Qingkai Zeng, Yongle Yuan, Meng Jiang:
Protecting Privacy in Multimodal Large Language Models with MLLMU-Bench. CoRR abs/2410.22108 (2024) - [i66]Tianyu Yang, Lisen Dai, Zheyuan Liu, Xiangqi Wang, Meng Jiang, Yapeng Tian, Xiangliang Zhang:
CLIPErase: Efficient Unlearning of Visual-Textual Associations in CLIP. CoRR abs/2410.23330 (2024) - 2023
- [j31]Tong Zhao, Wei Jin, Yozen Liu, Yingheng Wang, Gang Liu, Stephan Günnemann, Neil Shah, Meng Jiang:
Graph Data Augmentation for Graph Machine Learning: A Survey. IEEE Data Eng. Bull. 47(2): 140-165 (2023) - [j30]Zhaoxuan Tan, Meng Jiang:
User Modeling in the Era of Large Language Models: Current Research and Future Directions. IEEE Data Eng. Bull. 47(4): 57-96 (2023) - [j29]Zhihan Zhang, Wenhao Yu, Zheng Ning, Mingxuan Ju, Meng Jiang:
Exploring Contrast Consistency of Open-Domain Question Answering Systems on Minimally Edited Questions. Trans. Assoc. Comput. Linguistics 11: 1082-1096 (2023) - [j28]Daheng Wang, Zhihan Zhang, Yihong Ma, Tong Zhao, Tianwen Jiang, Nitesh V. Chawla, Meng Jiang:
Modeling Co-Evolution of Attributed and Structural Information in Graph Sequence. IEEE Trans. Knowl. Data Eng. 35(2): 1817-1830 (2023) - [j27]Daheng Wang, Tong Zhao, Wenhao Yu, Nitesh V. Chawla, Meng Jiang:
Deep Multimodal Complementarity Learning. IEEE Trans. Neural Networks Learn. Syst. 34(12): 10213-10224 (2023) - [c98]Noah Ziems, Wenhao Yu, Zhihan Zhang, Meng Jiang:
Large Language Models are Built-in Autoregressive Search Engines. ACL (Findings) 2023: 2666-2678 - [c97]Zhihan Zhang, Wenhao Yu, Mengxia Yu, Zhichun Guo, Meng Jiang:
A Survey of Multi-task Learning in Natural Language Processing: Regarding Task Relatedness and Training Methods. EACL 2023: 943-956 - [c96]Wenhao Yu, Meng Jiang, Peter Clark, Ashish Sabharwal:
IfQA: A Dataset for Open-domain Question Answering under Counterfactual Presuppositions. EMNLP 2023: 8276-8288 - [c95]Zhihan Zhang, Shuohang Wang, Wenhao Yu, Yichong Xu, Dan Iter, Qingkai Zeng, Yang Liu, Chenguang Zhu, Meng Jiang:
Auto-Instruct: Automatic Instruction Generation and Ranking for Black-Box Language Models. EMNLP (Findings) 2023: 9850-9867 - [c94]Mengxia Yu, Zhihan Zhang, Wenhao Yu, Meng Jiang:
Pre-training Language Models for Comparative Reasoning. EMNLP 2023: 12421-12433 - [c93]Wenhao Yu, Dan Iter, Shuohang Wang, Yichong Xu, Mingxuan Ju, Soumya Sanyal, Chenguang Zhu, Michael Zeng, Meng Jiang:
Generate rather than Retrieve: Large Language Models are Strong Context Generators. ICLR 2023 - [c92]Gang Liu, Meng Jiang:
Explaining AI-Informed Network Intrusion Detection with Counterfactuals. INFOCOM Workshops 2023: 1-2 - [c91]Yiren Liu, Mengxia Yu, Meng Jiang, Yun Huang:
Creative Research Question Generation for Human-Computer Interaction Research. IUI Workshops 2023: 58-66 - [c90]Gang Liu, Tong Zhao, Eric Inae, Tengfei Luo, Meng Jiang:
Semi-Supervised Graph Imbalanced Regression. KDD 2023: 1453-1465 - [c89]Wenhao Yu, Lingbo Tong, Weijia Shi, Nanyun Peng, Meng Jiang:
The Second Workshop on Knowledge-Augmented Methods for Natural Language Processing. KDD 2023: 5899-5900 - [c88]Chuxu Zhang, Dongkuan Xu, Mojan Javaheripi, Subhabrata Mukherjee, Lingfei Wu, Yinglong Xia, Jundong Li, Meng Jiang, Yanzhi Wang:
RelKD 2023: International Workshop on Resource-Efficient Learning for Knowledge Discovery. KDD 2023: 5901-5902 - [c87]Gang Liu, Eric Inae, Tong Zhao, Jiaxin Xu, Tengfei Luo, Meng Jiang:
Data-Centric Learning from Unlabeled Graphs with Diffusion Model. NeurIPS 2023 - [c86]Chenguang Zhu, Yichong Xu, Xiang Ren, Bill Yuchen Lin, Meng Jiang, Wenhao Yu:
Knowledge-Augmented Methods for Natural Language Processing. WSDM 2023: 1228-1231 - [i65]Gang Liu, Eric Inae, Tong Zhao, Jiaxin Xu, Tengfei Luo, Meng Jiang:
Data-Centric Learning from Unlabeled Graphs with Diffusion Model. CoRR abs/2303.10108 (2023) - [i64]Noah Ziems, Wenhao Yu, Zhihan Zhang, Meng Jiang:
Large Language Models are Built-in Autoregressive Search Engines. CoRR abs/2305.09612 (2023) - [i63]Gang Liu, Tong Zhao, Eric Inae, Tengfei Luo, Meng Jiang:
Semi-Supervised Graph Imbalanced Regression. CoRR abs/2305.12087 (2023) - [i62]Wenhao Yu, Zhihan Zhang, Zhenwen Liang, Meng Jiang, Ashish Sabharwal:
Improving Language Models via Plug-and-Play Retrieval Feedback. CoRR abs/2305.14002 (2023) - [i61]Wenhao Yu, Meng Jiang, Peter Clark, Ashish Sabharwal:
IfQA: A Dataset for Open-domain Question Answering under Counterfactual Presuppositions. CoRR abs/2305.14010 (2023) - [i60]Zhihan Zhang, Wenhao Yu, Zheng Ning, Mingxuan Ju, Meng Jiang:
Exploring Contrast Consistency of Open-Domain Question Answering Systems on Minimally Edited Questions. CoRR abs/2305.14441 (2023) - [i59]Mengxia Yu, Zhihan Zhang, Wenhao Yu, Meng Jiang:
Pre-training Language Models for Comparative Reasoning. CoRR abs/2305.14457 (2023) - [i58]Meng Jiang, Hy Dang, Lingbo Tong:
A Quantitative Review on Language Model Efficiency Research. CoRR abs/2306.01768 (2023) - [i57]Hy Dang, Bang Nguyen, Noah Ziems, Meng Jiang:
Embedding Mental Health Discourse for Community Recommendation. CoRR abs/2307.03892 (2023) - [i56]Eric Inae, Gang Liu, Meng Jiang:
Motif-aware Attribute Masking for Molecular Graph Pre-training. CoRR abs/2309.04589 (2023) - [i55]Zhihan Zhang, Shuohang Wang, Wenhao Yu, Yichong Xu, Dan Iter, Qingkai Zeng, Yang Liu, Chenguang Zhu, Meng Jiang:
Auto-Instruct: Automatic Instruction Generation and Ranking for Black-Box Language Models. CoRR abs/2310.13127 (2023) - [i54]Noah Ziems, Gang Liu, John Flanagan, Meng Jiang:
Explaining Tree Model Decisions in Natural Language for Network Intrusion Detection. CoRR abs/2310.19658 (2023) - [i53]Zhihan Zhang, Dong-Ho Lee, Yuwei Fang, Wenhao Yu, Mengzhao Jia, Meng Jiang, Francesco Barbieri:
PLUG: Leveraging Pivot Language in Cross-Lingual Instruction Tuning. CoRR abs/2311.08711 (2023) - [i52]Ruiyang Qin, Jun Xia, Zhenge Jia, Meng Jiang, Ahmed Abbasi, Peipei Zhou, Jingtong Hu, Yiyu Shi:
Enabling On-Device Large Language Model Personalization with Self-Supervised Data Selection and Synthesis. CoRR abs/2311.12275 (2023) - [i51]Bowen Jin, Gang Liu, Chi Han, Meng Jiang, Heng Ji, Jiawei Han:
Large Language Models on Graphs: A Comprehensive Survey. CoRR abs/2312.02783 (2023) - [i50]Zhenyu Wu, Meng Jiang, Chao Shen:
Get an A in Math: Progressive Rectification Prompting. CoRR abs/2312.06867 (2023) - [i49]Zhaoxuan Tan, Meng Jiang:
User Modeling in the Era of Large Language Models: Current Research and Future Directions. CoRR abs/2312.11518 (2023) - 2022
- [j26]Shawn Gu, Meng Jiang, Pietro Hiram Guzzi, Tijana Milenkovic:
Modeling multi-scale data via a network of networks. Bioinform. 38(9): 2544-2553 (2022) - [j25]Dylan Chou, Meng Jiang:
A Survey on Data-driven Network Intrusion Detection. ACM Comput. Surv. 54(9): 182:1-182:36 (2022) - [j24]Wenhao Yu, Chenguang Zhu, Zaitang Li, Zhiting Hu, Qingyun Wang, Heng Ji, Meng Jiang:
A Survey of Knowledge-enhanced Text Generation. ACM Comput. Surv. 54(11s): 227:1-227:38 (2022) - [j23]Meng Jiang, Chuxu Zhang, Xiangliang Zhang, Neil Shah:
Editorial: Computational Behavioral Modeling for Big User Data. Frontiers Big Data 5: 893216 (2022) - [j22]Mandana Saebi, Steven Kreig, Chuxu Zhang, Meng Jiang, Tomasz Kajdanowicz, Nitesh V. Chawla:
Heterogeneous relational reasoning in knowledge graphs with reinforcement learning. Inf. Fusion 88: 12-21 (2022) - [j21]Meng Jiang, Taeho Jung, Ryan Karl, Tong Zhao:
Federated Dynamic Graph Neural Networks with Secure Aggregation for Video-based Distributed Surveillance. ACM Trans. Intell. Syst. Technol. 13(4): 56:1-56:23 (2022) - [j20]Sendong Zhao, Meng Jiang, Bing Qin, Ting Liu, ChengXiang Zhai, Fei Wang:
Structural and Textual Information Fusion for Symptom and Disease Representation Learning. IEEE Trans. Knowl. Data Eng. 34(9): 4468-4483 (2022) - [j19]Tong Zhao, Tianwen Jiang, Neil Shah, Meng Jiang:
A Synergistic Approach for Graph Anomaly Detection With Pattern Mining and Feature Learning. IEEE Trans. Neural Networks Learn. Syst. 33(6): 2393-2405 (2022) - [c85]Chenguang Zhu, Yichong Xu, Xiang Ren, Bill Y. Lin, Meng Jiang, Wenhao Yu:
Knowledge-Augmented Methods for Natural Language Processing. ACL (tutorial) 2022: 12-20 - [c84]Wenhao Yu, Chenguang Zhu, Lianhui Qin, Zhihan Zhang, Tong Zhao, Meng Jiang:
Diversifying Content Generation for Commonsense Reasoning with Mixture of Knowledge Graph Experts. ACL (Findings) 2022: 1896-1906 - [c83]Wenhao Yu, Chenguang Zhu, Yuwei Fang, Donghan Yu, Shuohang Wang, Yichong Xu, Michael Zeng, Meng Jiang:
Dict-BERT: Enhancing Language Model Pre-training with Dictionary. ACL (Findings) 2022: 1907-1918 - [c82]Toby Jia-Jun Li, Yuwen Lu, Jaylexia Clark, Meng Chen, Victor V. Cox, Meng Jiang, Yang Yang, Tamara Kay, Danielle M. Wood, Jay Brockman:
A Bottom-Up End-User Intelligent Assistant Approach to Empower Gig Workers against AI Inequality. CHIWORK 2022: 9:1-9:10 - [c81]Zhihan Zhang, Wenhao Yu, Chenguang Zhu, Meng Jiang:
A Unified Encoder-Decoder Framework with Entity Memory. EMNLP 2022: 689-705 - [c80]Wenhao Yu, Chenguang Zhu, Zhihan Zhang, Shuohang Wang, Zhuosheng Zhang, Yuwei Fang, Meng Jiang:
Retrieval Augmentation for Commonsense Reasoning: A Unified Approach. EMNLP 2022: 4364-4377 - [c79]Tong Zhao, Gang Liu, Daheng Wang, Wenhao Yu, Meng Jiang:
Learning from Counterfactual Links for Link Prediction. ICML 2022: 26911-26926 - [c78]Qing Lu, Weiwen Jiang, Meng Jiang, Jingtong Hu, Yiyu Shi:
Hardware/Software Co-Exploration for Graph Neural Architectures on FPGAs. ISVLSI 2022: 358-362 - [c77]Gang Liu, Tong Zhao, Jiaxin Xu, Tengfei Luo, Meng Jiang:
Graph Rationalization with Environment-based Augmentations. KDD 2022: 1069-1078 - [c76]Xiaojie Guo, Qingkai Zeng, Meng Jiang, Yun Xiao, Bo Long, Lingfei Wu:
Automatic Controllable Product Copywriting for E-Commerce. KDD 2022: 2946-2956 - [c75]Pamela Bhattacharya, Jing Gao, Meng Jiang, Mehran Kafai, Srijan Kumar, Qi Li, Neil Shah, Sihong Xie, Philip S. Yu, Ming Zeng:
Joint International Workshop on Misinformation and Misbehavior Mining on the Web & Making a Credible Web for Tomorrow (MIS2-TrueFact). KDD 2022: 4854-4855 - [c74]Tong Zhao, Xianfeng Tang, Danqing Zhang, Haoming Jiang, Nikhil Rao, Yiwei Song, Pallav Agrawal, Karthik Subbian, Bing Yin, Meng Jiang:
AutoGDA: Automated Graph Data Augmentation for Node Classification. LoG 2022: 32 - [i48]Tong Zhao, Gang Liu, Stephan Günnemann, Meng Jiang:
Graph Data Augmentation for Graph Machine Learning: A Survey. CoRR abs/2202.08871 (2022) - [i47]Wenhao Yu, Chenguang Zhu, Lianhui Qin, Zhihan Zhang, Tong Zhao, Meng Jiang:
Diversifying Content Generation for Commonsense Reasoning with Mixture of Knowledge Graph Experts. CoRR abs/2203.07285 (2022) - [i46]Zhihan Zhang, Wenhao Yu, Mengxia Yu, Zhichun Guo, Meng Jiang:
A Survey of Multi-task Learning in Natural Language Processing: Regarding Task Relatedness and Training Methods. CoRR abs/2204.03508 (2022) - [i45]Toby Jia-Jun Li, Yuwen Lu, Jaylexia Clark, Meng Chen, Victor V. Cox, Meng Jiang, Yang Yang, Tamara Kay, Danielle M. Wood, Jay Brockman:
A Bottom-Up End-User Intelligent Assistant Approach to Empower Gig Workers against AI Inequality. CoRR abs/2204.13842 (2022) - [i44]Gang Liu, Tong Zhao, Jiaxin Xu, Tengfei Luo, Meng Jiang:
Graph Rationalization with Environment-based Augmentations. CoRR abs/2206.02886 (2022) - [i43]Xiaojie Guo, Qingkai Zeng, Meng Jiang, Yun Xiao, Bo Long, Lingfei Wu:
Automatic Controllable Product Copywriting for E-Commerce. CoRR abs/2206.10103 (2022) - [i42]Jinfeng Lin, Amrit Poudel, Wenhao Yu, Qingkai Zeng, Meng Jiang, Jane Cleland-Huang:
Enhancing Automated Software Traceability by Transfer Learning from Open-World Data. CoRR abs/2207.01084 (2022) - [i41]Gang Liu, Zhihan Zhang, Zheng Ning, Meng Jiang:
On the Relationship between Counterfactual Explainer and Recommender: A Framework and Preliminary Observations. CoRR abs/2207.04317 (2022) - [i40]Wenhao Yu, Dan Iter, Shuohang Wang, Yichong Xu, Mingxuan Ju, Soumya Sanyal, Chenguang Zhu, Michael Zeng, Meng Jiang:
Generate rather than Retrieve: Large Language Models are Strong Context Generators. CoRR abs/2209.10063 (2022) - [i39]Zhihan Zhang, Wenhao Yu, Chenguang Zhu, Meng Jiang:
A Unified Encoder-Decoder Framework with Entity Memory. CoRR abs/2210.03273 (2022) - [i38]Wenhao Yu, Chenguang Zhu, Zhihan Zhang, Shuohang Wang, Zhuosheng Zhang, Yuwei Fang, Meng Jiang:
Retrieval Augmentation for Commonsense Reasoning: A Unified Approach. CoRR abs/2210.12887 (2022) - 2021
- [j18]Munira Syed, Daheng Wang, Meng Jiang, Oliver Conway, Vishal Juneja, Sriram Subramanian, Nitesh V. Chawla:
Unified Representation of Twitter and Online News Using Graph and Entities. Frontiers Big Data 4: 699070 (2021) - [j17]Tianwen Jiang, Qingkai Zeng, Tong Zhao, Bing Qin, Ting Liu, Nitesh V. Chawla, Meng Jiang:
Biomedical Knowledge Graphs Construction From Conditional Statements. IEEE ACM Trans. Comput. Biol. Bioinform. 18(3): 823-835 (2021) - [j16]Daheng Wang, Qingkai Zeng, Nitesh V. Chawla, Meng Jiang:
Modeling Complementarity in Behavior Data with Multi-Type Itemset Embedding. ACM Trans. Intell. Syst. Technol. 12(4): 42:1-42:25 (2021) - [j15]Chuxu Zhang, Huaxiu Yao, Lu Yu, Chao Huang, Dongjin Song, Haifeng Chen, Meng Jiang, Nitesh V. Chawla:
Inductive Contextual Relation Learning for Personalization. ACM Trans. Inf. Syst. 39(3): 35:1-35:22 (2021) - [c73]Tong Zhao, Yozen Liu, Leonardo Neves, Oliver J. Woodford, Meng Jiang, Neil Shah:
Data Augmentation for Graph Neural Networks. AAAI 2021: 11015-11023 - [c72]Tong Zhao, Bo Ni, Wenhao Yu, Zhichun Guo, Neil Shah, Meng Jiang:
Action Sequence Augmentation for Early Graph-based Anomaly Detection. CIKM 2021: 2668-2678 - [c71]Xiangyu Dong, Wenhao Yu, Chenguang Zhu, Meng Jiang:
Injecting Entity Types into Entity-Guided Text Generation. EMNLP (1) 2021: 734-741 - [c70]Wenhao Yu, Chenguang Zhu, Tong Zhao, Zhichun Guo, Meng Jiang:
Sentence-Permuted Paragraph Generation. EMNLP (1) 2021: 5051-5062 - [c69]Qingkai Zeng, Mengxia Yu, Wenhao Yu, Tianwen Jiang, Meng Jiang:
Validating Label Consistency in NER Data Annotation. Eval4NLP 2021: 11-15 - [c68]Joseph Kuebler, Lingbo Tong, Meng Jiang:
Multi-Round Parsing-based Multiword Rules for Scientific Knowledge Extraction. ICBK 2021: 331-338 - [c67]Daheng Wang, Tong Zhao, Nitesh V. Chawla, Meng Jiang:
Dynamic Attributed Graph Prediction with Conditional Normalizing Flows. ICDM 2021: 1385-1390 - [c66]Jinfeng Lin, Yalin Liu, Qingkai Zeng, Meng Jiang, Jane Cleland-Huang:
Traceability Transformed: Generating more Accurate Links with Pre-Trained BERT Models. ICSE 2021: 324-335 - [c65]Meng Jiang:
Cross-Network Learning with Partially Aligned Graph Convolutional Networks. KDD 2021: 746-755 - [c64]Qingkai Zeng, Jinfeng Lin, Wenhao Yu, Jane Cleland-Huang, Meng Jiang:
Enhancing Taxonomy Completion with Concept Generation via Fusing Relational Representations. KDD 2021: 2104-2113 - [c63]Chuxu Zhang, Jundong Li, Meng Jiang:
Data Efficient Learning on Graphs. KDD 2021: 4092-4093 - [c62]Aude Hofleitner, Meng Jiang, Srijan Kumar, Neil Shah, Kai Shu:
The Second International MIS2 Workshop: Misinformation and Misbehavior Mining on the Web. KDD 2021: 4129-4130 - [c61]Wenhao Yu, Lingfei Wu, Yu Deng, Qingkai Zeng, Ruchi Mahindru, Sinem Güven, Meng Jiang:
Technical Question Answering across Tasks and Domains. NAACL-HLT (Industry Papers) 2021: 178-186 - [c60]Chenguang Zhu, William Hinthorn, Ruochen Xu, Qingkai Zeng, Michael Zeng, Xuedong Huang, Meng Jiang:
Enhancing Factual Consistency of Abstractive Summarization. NAACL-HLT 2021: 718-733 - [c59]Zhichun Guo, Chuxu Zhang, Wenhao Yu, John Herr, Olaf Wiest, Meng Jiang, Nitesh V. Chawla:
Few-Shot Graph Learning for Molecular Property Prediction. WWW 2021: 2559-2567 - [c58]Daheng Wang, Prashant Shiralkar, Colin Lockard, Binxuan Huang, Xin Luna Dong, Meng Jiang:
TCN: Table Convolutional Network for Web Table Interpretation. WWW 2021: 4020-4032 - [i37]Qingkai Zeng, Mengxia Yu, Wenhao Yu, Tianwen Jiang, Tim Weninger, Meng Jiang:
Validating Label Consistency in NER Data Annotation. CoRR abs/2101.08698 (2021) - [i36]Jinfeng Lin, Yalin Liu, Qingkai Zeng, Meng Jiang, Jane Cleland-Huang:
Traceability Transformed: Generating more Accurate Links with Pre-Trained BERT Models. CoRR abs/2102.04411 (2021) - [i35]Zhichun Guo, Chuxu Zhang, Wenhao Yu, John Herr, Olaf Wiest, Meng Jiang, Nitesh V. Chawla:
Few-Shot Graph Learning for Molecular Property Prediction. CoRR abs/2102.07916 (2021) - [i34]Daheng Wang, Prashant Shiralkar, Colin Lockard, Binxuan Huang, Xin Luna Dong, Meng Jiang:
TCN: Table Convolutional Network for Web Table Interpretation. CoRR abs/2102.09460 (2021) - [i33]Wenhao Yu, Chenguang Zhu, Tong Zhao, Zhichun Guo, Meng Jiang:
Sentence-Permuted Paragraph Generation. CoRR abs/2104.07228 (2021) - [i32]Meng Jiang:
Cross-Network Learning with Partially Aligned Graph Convolutional Networks. CoRR abs/2106.01583 (2021) - [i31]Tong Zhao, Gang Liu, Daheng Wang, Wenhao Yu, Meng Jiang:
Counterfactual Graph Learning for Link Prediction. CoRR abs/2106.02172 (2021) - [i30]Qingkai Zeng, Jinfeng Lin, Wenhao Yu, Jane Cleland-Huang, Meng Jiang:
Enhancing Taxonomy Completion with Concept Generation via Fusing Relational Representations. CoRR abs/2106.02974 (2021) - [i29]Joseph Kuebler, Lingbo Tong, Meng Jiang:
Multi-Round Parsing-based Multiword Rules for Scientific OpenIE. CoRR abs/2108.02074 (2021) - [i28]Wenhao Yu, Chenguang Zhu, Yuwei Fang, Donghan Yu, Shuohang Wang, Yichong Xu, Michael Zeng, Meng Jiang:
Dict-BERT: Enhancing Language Model Pre-training with Dictionary. CoRR abs/2110.06490 (2021) - 2020
- [j14]Xueying Wang, Meng Jiang:
Precise temporal slot filling via truth finding with data-driven commonsense. Knowl. Inf. Syst. 62(10): 4113-4139 (2020) - [j13]Jinglan Liu, Jiaxin Zhang, Yukun Ding, Xiaowei Xu, Meng Jiang, Yiyu Shi:
Binarizing Weights Wisely for Edge Intelligence: Guide for Partial Binarization of Deconvolution-Based Generators. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 39(12): 4748-4759 (2020) - [j12]Kun Kuang, Peng Cui, Bo Li, Meng Jiang, Yashen Wang, Fei Wu, Shiqiang Yang:
Treatment Effect Estimation via Differentiated Confounder Balancing and Regression. ACM Trans. Knowl. Discov. Data 14(1): 6:1-6:25 (2020) - [c57]Chuxu Zhang, Huaxiu Yao, Chao Huang, Meng Jiang, Zhenhui Li, Nitesh V. Chawla:
Few-Shot Knowledge Graph Completion. AAAI 2020: 3041-3048 - [c56]Huaxiu Yao, Chuxu Zhang, Ying Wei, Meng Jiang, Suhang Wang, Junzhou Huang, Nitesh V. Chawla, Zhenhui Li:
Graph Few-Shot Learning via Knowledge Transfer. AAAI 2020: 6656-6663 - [c55]Pingjie Tang, Meng Jiang, Bryan (Ning) Xia, Jed W. Pitera, Jeffrey Welser, Nitesh V. Chawla:
Multi-Label Patent Categorization with Non-Local Attention-Based Graph Convolutional Network. AAAI 2020: 9024-9031 - [c54]Wenhao Yu, Lingfei Wu, Qingkai Zeng, Shu Tao, Yu Deng, Meng Jiang:
Crossing Variational Autoencoders for Answer Retrieval. ACL 2020: 5635-5641 - [c53]Munira Syed, Daheng Wang, Meng Jiang, Oliver Conway, Vishal Juneja, Sriram Subramanian, Nitesh V. Chawla:
Overcoming Data Sparsity in Predicting User Characteristics from Behavior through Graph Embeddings. ASONAM 2020: 32-36 - [c52]Tianwen Jiang, Ning Zhang, Ming Liu, Meng Jiang, Ting Liu, Bing Qin:
Use of "Internal Knowledge": Biomedical Literature Search Liberated From External Resources. BIBM 2020: 275-280 - [c51]Jennifer J. Schnur, Ryan Karl, Angélica García-Martínez, Meng Jiang, Nitesh V. Chawla:
Imputing Growth Snapshot Similarity in Early Childhood Development: A Tensor Decomposition Approach. BIBM 2020: 729-734 - [c50]Alvin Alaphat, Meng Jiang:
SmartFund: Predicting Research Outcomes with Machine Learning and Natural Language Processing. IEEE BigData 2020: 2857-2865 - [c49]Zhichun Guo, Wenhao Yu, Chuxu Zhang, Meng Jiang, Nitesh V. Chawla:
GraSeq: Graph and Sequence Fusion Learning for Molecular Property Prediction. CIKM 2020: 435-443 - [c48]Tong Zhao, Chuchen Deng, Kaifeng Yu, Tianwen Jiang, Daheng Wang, Meng Jiang:
Error-Bounded Graph Anomaly Loss for GNNs. CIKM 2020: 1873-1882 - [c47]Wenhao Yu, Lingfei Wu, Yu Deng, Ruchi Mahindru, Qingkai Zeng, Sinem Güven, Meng Jiang:
A Technical Question Answering System with Transfer Learning. EMNLP (Demos) 2020: 92-99 - [c46]Chuxu Zhang, Lu Yu, Mandana Saebi, Meng Jiang, Nitesh V. Chawla:
Few-Shot Multi-Hop Relation Reasoning over Knowledge Bases. EMNLP (Findings) 2020: 580-585 - [c45]Qingkai Zeng, Wenhao Yu, Mengxia Yu, Tianwen Jiang, Tim Weninger, Meng Jiang:
Tri-Train: Automatic Pre-Fine Tuning between Pre-Training and Fine-Tuning for SciNER. EMNLP (Findings) 2020: 4778-4787 - [c44]Daheng Wang, Meng Jiang, Munira Syed, Oliver Conway, Vishal Juneja, Sriram Subramanian, Nitesh V. Chawla:
Calendar Graph Neural Networks for Modeling Time Structures in Spatiotemporal User Behaviors. KDD 2020: 2581-2589 - [c43]Meng Jiang, Jingbo Shang:
Scientific Text Mining and Knowledge Graphs. KDD 2020: 3537-3538 - [c42]Chuxu Zhang, Meng Jiang, Xiangliang Zhang, Yanfang Ye, Nitesh V. Chawla:
Multi-modal Network Representation Learning. KDD 2020: 3557-3558 - [c41]Yalin Liu, Jinfeng Lin, Qingkai Zeng, Meng Jiang, Jane Cleland-Huang:
Towards Semantically Guided Traceability. RE 2020: 328-333 - [c40]Wenhao Yu, Wei Peng, Yu Shu, Qingkai Zeng, Meng Jiang:
Experimental Evidence Extraction System in Data Science with Hybrid Table Features and Ensemble Learning. WWW 2020: 951-961 - [c39]Wenhao Yu, Mengxia Yu, Tong Zhao, Meng Jiang:
Identifying Referential Intention with Heterogeneous Contexts. WWW 2020: 962-972 - [i27]Zhiyu Liu, Meng Jiang, Hai Lin:
A graph-based spatial temporal logic for knowledge representation and automated reasoning in cognitive robots. CoRR abs/2001.07205 (2020) - [i26]Bo Ni, Zhichun Guo, Jianing Li, Meng Jiang:
Improving Generalizability of Fake News Detection Methods using Propensity Score Matching. CoRR abs/2002.00838 (2020) - [i25]Mandana Saebi, Steven J. Krieg, Chuxu Zhang, Meng Jiang, Nitesh V. Chawla:
Heterogeneous Relational Reasoning in Knowledge Graphs with Reinforcement Learning. CoRR abs/2003.06050 (2020) - [i24]Chenguang Zhu, William Hinthorn, Ruochen Xu, Qingkai Zeng, Michael Zeng, Xuedong Huang, Meng Jiang:
Boosting Factual Correctness of Abstractive Summarization with Knowledge Graph. CoRR abs/2003.08612 (2020) - [i23]Wenhao Yu, Lingfei Wu, Qingkai Zeng, Yu Deng, Shu Tao, Meng Jiang:
Crossing Variational Autoencoders for Answer Retrieval. CoRR abs/2005.02557 (2020) - [i22]Yang Zhou, Tong Zhao, Meng Jiang:
A Probabilistic Model with Commonsense Constraints for Pattern-based Temporal Fact Extraction. CoRR abs/2006.06436 (2020) - [i21]Daheng Wang, Meng Jiang, Munira Syed, Oliver Conway, Vishal Juneja, Sriram Subramanian, Nitesh V. Chawla:
Calendar Graph Neural Networks for Modeling Time Structures in Spatiotemporal User Behaviors. CoRR abs/2006.06820 (2020) - [i20]Tong Zhao, Yozen Liu, Leonardo Neves, Oliver J. Woodford, Meng Jiang, Neil Shah:
Data Augmentation for Graph Neural Networks. CoRR abs/2006.06830 (2020) - [i19]Tianwen Jiang, Tong Zhao, Bing Qin, Ting Liu, Nitesh V. Chawla, Meng Jiang:
Canonicalizing Open Knowledge Bases with Multi-Layered Meta-Graph Neural Network. CoRR abs/2006.09610 (2020) - [i18]Zhiyu Liu, Meng Jiang, Hai Lin:
Specification mining and automated task planning for autonomous robots based on a graph-based spatial temporal logic. CoRR abs/2007.08451 (2020) - [i17]Daheng Wang, Zhihan Zhang, Yihong Ma, Tong Zhao, Tianwen Jiang, Nitesh V. Chawla, Meng Jiang:
Learning Attribute-Structure Co-Evolutions in Dynamic Graphs. CoRR abs/2007.13004 (2020) - [i16]Meng Jiang, Taeho Jung, Ryan Karl, Tong Zhao:
Federated Dynamic GNN with Secure Aggregation. CoRR abs/2009.07351 (2020) - [i15]Xiangyu Dong, Wenhao Yu, Chenguang Zhu, Meng Jiang:
Injecting Entity Types into Entity-Guided Text Generation. CoRR abs/2009.13401 (2020) - [i14]Wenhao Yu, Chenguang Zhu, Zaitang Li, Zhiting Hu, Qingyun Wang, Heng Ji, Meng Jiang:
A Survey of Knowledge-Enhanced Text Generation. CoRR abs/2010.04389 (2020) - [i13]Wenhao Yu, Lingfei Wu, Yu Deng, Qingkai Zeng, Ruchi Mahindru, Sinem Güven, Meng Jiang:
Technical Question Answering across Tasks and Domains. CoRR abs/2010.09780 (2020) - [i12]Tong Zhao, Bo Ni, Wenhao Yu, Meng Jiang:
Early Anomaly Detection by Learning and Forecasting Behavior. CoRR abs/2010.10016 (2020)
2010 – 2019
- 2019
- [c38]Tianwen Jiang, Zhihan Zhang, Tong Zhao, Bing Qin, Ting Liu, Nitesh V. Chawla, Meng Jiang:
CTGA: Graph-based Biomedical Literature Search. BIBM 2019: 395-400 - [c37]Yifan Ding, Daheng Wang, Tim Weninger, Meng Jiang:
Preserving Composition and Crystal Structures of Chemical Compounds in Atomic Embedding. IEEE BigData 2019: 6037-6039 - [c36]Tianwen Jiang, Tong Zhao, Bing Qin, Ting Liu, Nitesh V. Chawla, Meng Jiang:
Multi-Input Multi-Output Sequence Labeling for Joint Extraction of Fact and Condition Tuples from Scientific Text. EMNLP/IJCNLP (1) 2019: 302-312 - [c35]Yihong Ma, Qingkai Zeng, Tianwen Jiang, Liang Cai, Meng Jiang:
A Study of Person Entity Extraction and Profiling from Classical Chinese Historiography. EYRE@CIKM 2019: 8-15 - [c34]Tianwen Jiang, Tong Zhao, Bing Qin, Ting Liu, Nitesh V. Chawla, Meng Jiang:
The Role of: A Novel Scientific Knowledge Graph Representation and Construction Model. KDD 2019: 1634-1642 - [c33]Daheng Wang, Tianwen Jiang, Nitesh V. Chawla, Meng Jiang:
TUBE: Embedding Behavior Outcomes for Predicting Success. KDD 2019: 1682-1690 - [c32]Tianchen Wang, Jinjun Xiong, Xiaowei Xu, Meng Jiang, Haiyun Yuan, Meiping Huang, Jian Zhuang, Yiyu Shi:
MSU-Net: Multiscale Statistical U-Net for Real-Time 3D Cardiac MRI Video Segmentation. MICCAI (2) 2019: 614-622 - [c31]Qingkai Zeng, Mengxia Yu, Wenhao Yu, Jinjun Xiong, Yiyu Shi, Meng Jiang:
Faceted Hierarchy: A New Graph Type to Organize Scientific Concepts and a Construction Method. TextGraphs@EMNLP 2019: 140-150 - [c30]Xueying Wang, Haiqiao Zhang, Qi Li, Yiyu Shi, Meng Jiang:
A Novel Unsupervised Approach for Precise Temporal Slot Filling from Incomplete and Noisy Temporal Contexts. WWW 2019: 3328-3334 - [c29]Wenhao Yu, Zongze Li, Qingkai Zeng, Meng Jiang:
Tablepedia: Automating PDF Table Reading in an Experimental Evidence Exploration and Analytic System. WWW 2019: 3615-3619 - [i11]Tianwen Jiang, Tong Zhao, Bing Qin, Ting Liu, Nitesh V. Chawla, Meng Jiang:
Constructing Information-Lossless Biological Knowledge Graphs from Conditional Statements. CoRR abs/1907.00720 (2019) - [i10]Tianchen Wang, Jinjun Xiong, Xiaowei Xu, Meng Jiang, Yiyu Shi, Haiyun Yuan, Meiping Huang, Jian Zhuang:
MSU-Net: Multiscale Statistical U-Net for Real-time 3D Cardiac MRI Video Segmentation. CoRR abs/1909.06726 (2019) - [i9]Huaxiu Yao, Chuxu Zhang, Ying Wei, Meng Jiang, Suhang Wang, Junzhou Huang, Nitesh V. Chawla, Zhenhui Li:
Graph Few-shot Learning via Knowledge Transfer. CoRR abs/1910.03053 (2019) - [i8]Chuxu Zhang, Huaxiu Yao, Chao Huang, Meng Jiang, Zhenhui Li, Nitesh V. Chawla:
Few-Shot Knowledge Graph Completion. CoRR abs/1911.11298 (2019) - 2018
- [j11]Kun Kuang, Meng Jiang, Peng Cui, Hengliang Luo, Shiqiang Yang:
Effective Promotional Strategies Selection in Social Media: A Data-Driven Approach. IEEE Trans. Big Data 4(4): 487-501 (2018) - [j10]Jingbo Shang, Meng Jiang, Wenzhu Tong, Jinfeng Xiao, Jian Peng, Jiawei Han:
DPPred: An Effective Prediction Framework with Concise Discriminative Patterns. IEEE Trans. Knowl. Data Eng. 30(7): 1226-1239 (2018) - [j9]Jingbo Shang, Jialu Liu, Meng Jiang, Xiang Ren, Clare R. Voss, Jiawei Han:
Automated Phrase Mining from Massive Text Corpora. IEEE Trans. Knowl. Data Eng. 30(10): 1825-1837 (2018) - [c28]Sendong Zhao, Meng Jiang, Ming Liu, Bing Qin, Ting Liu:
CausalTriad: Toward Pseudo Causal Relation Discovery and Hypotheses Generation from Medical Text Data. BCB 2018: 184-193 - [c27]Tong Zhao, Matthew Malir, Meng Jiang:
Actionable Objective Optimization for Suspicious Behavior Detection on Large Bipartite Graphs. IEEE BigData 2018: 1248-1257 - [c26]Yukun Ding, Jinglan Liu, Jinjun Xiong, Meng Jiang, Yiyu Shi:
Optimizing Boiler Control in Real-Time with Machine Learning for Sustainability. CIKM 2018: 2147-2154 - [c25]Fangbo Tao, Chao Zhang, Xiusi Chen, Meng Jiang, Tim Hanratty, Lance M. Kaplan, Jiawei Han:
Doc2Cube: Allocating Documents to Text Cube Without Labeled Data. ICDM 2018: 1260-1265 - [c24]Qi Li, Meng Jiang, Xikun Zhang, Meng Qu, Timothy P. Hanratty, Jing Gao, Jiawei Han:
TruePIE: Discovering Reliable Patterns in Pattern-Based Information Extraction. KDD 2018: 1675-1684 - [c23]Daheng Wang, Meng Jiang, Qingkai Zeng, Zachary Eberhart, Nitesh V. Chawla:
Multi-Type Itemset Embedding for Learning Behavior Success. KDD 2018: 2397-2406 - [c22]Chao Zhang, Fangbo Tao, Xiusi Chen, Jiaming Shen, Meng Jiang, Brian M. Sadler, Michelle Vanni, Jiawei Han:
TaxoGen: Unsupervised Topic Taxonomy Construction by Adaptive Term Embedding and Clustering. KDD 2018: 2701-2709 - [c21]Srijan Kumar, Meng Jiang, Taeho Jung, Roger Jie Luo, Jure Leskovec:
MIS2: Misinformation and Misbehavior Mining on the Web. WSDM 2018: 799-800 - [r1]Meng Jiang:
Behavior Modeling in Social Networks. Encyclopedia of Social Network Analysis and Mining. 2nd Ed. 2018 - [i7]Jingbo Shang, Xiyao Shi, Meng Jiang, Liyuan Liu, Timothy P. Hanratty, Jiawei Han:
Contrast Subgraph Mining from Coherent Cores. CoRR abs/1802.06189 (2018) - [i6]Jinglan Liu, Jiaxin Zhang, Yukun Ding, Xiaowei Xu, Meng Jiang, Yiyu Shi:
PBGAN: Partial Binarization of Deconvolution Based Generators. CoRR abs/1802.09153 (2018) - [i5]Chao Zhang, Fangbo Tao, Xiusi Chen, Jiaming Shen, Meng Jiang, Brian M. Sadler, Michelle Vanni, Jiawei Han:
TaxoGen: Unsupervised Topic Taxonomy Construction by Adaptive Term Embedding and Clustering. CoRR abs/1812.09551 (2018) - 2017
- [j8]Huan Gui, Jialu Liu, Fangbo Tao, Meng Jiang, Brandon Norick, Lance M. Kaplan, Jiawei Han:
Embedding Learning with Events in Heterogeneous Information Networks. IEEE Trans. Knowl. Data Eng. 29(11): 2428-2441 (2017) - [c20]Kun Kuang, Peng Cui, Bo Li, Meng Jiang, Shiqiang Yang, Fei Wang:
Treatment Effect Estimation with Data-Driven Variable Decomposition. AAAI 2017: 140-146 - [c19]Xiang Ren, Jiaming Shen, Meng Qu, Xuan Wang, Zeqiu Wu, Qi Zhu, Meng Jiang, Fangbo Tao, Saurabh Sinha, David Liem, Peipei Ping, Richard M. Weinshilboum, Jiawei Han:
Life-iNet: A Structured Network-Based Knowledge Exploration and Analytics System for Life Sciences. ACL (System Demonstrations) 2017: 55-60 - [c18]Stan Zhao, Meng Jiang, Quan Yuan, Bing Qin, Ting Liu, ChengXiang Zhai:
ContextCare: Incorporating Contextual Information Networks to Representation Learning on Medical Forum Data. IJCAI 2017: 3497-3503 - [c17]Kun Kuang, Peng Cui, Bo Li, Meng Jiang, Shiqiang Yang:
Estimating Treatment Effect in the Wild via Differentiated Confounder Balancing. KDD 2017: 265-274 - [c16]Meng Jiang, Jingbo Shang, Taylor Cassidy, Xiang Ren, Lance M. Kaplan, Timothy P. Hanratty, Jiawei Han:
MetaPAD: Meta Pattern Discovery from Massive Text Corpora. KDD 2017: 877-886 - [c15]Xiang Ren, Meng Jiang, Jingbo Shang, Jiawei Han:
Building Structured Databases of Factual Knowledge from Massive Text Corpora. SIGMOD Conference 2017: 1741-1745 - [c14]Xiang Ren, Meng Jiang, Jingbo Shang, Jiawei Han:
Constructing Structured Information Networks from Massive Text Corpora. WWW (Companion Volume) 2017: 951-954 - [i4]Jingbo Shang, Jialu Liu, Meng Jiang, Xiang Ren, Clare R. Voss, Jiawei Han:
Automated Phrase Mining from Massive Text Corpora. CoRR abs/1702.04457 (2017) - [i3]Meng Jiang, Jingbo Shang, Taylor Cassidy, Xiang Ren, Lance M. Kaplan, Timothy P. Hanratty, Jiawei Han:
MetaPAD: Meta Pattern Discovery from Massive Text Corpora. CoRR abs/1703.04213 (2017) - [i2]Liang-Wei Chen, Bhargav Mangipudi, Jayachandu Bandlamudi, Richa Sehgal, Yun Hao, Meng Jiang, Huan Gui:
Integrating Knowledge from Latent and Explicit Features for Triple Scoring - Team Radicchio's Triple Scorer at WSDM Cup 2017. CoRR abs/1712.08357 (2017) - 2016
- [j7]Meng Jiang, Peng Cui, Christos Faloutsos:
Suspicious Behavior Detection: Current Trends and Future Directions. IEEE Intell. Syst. 31(1): 31-39 (2016) - [j6]Meng Jiang, Peng Cui, Alex Beutel, Christos Faloutsos, Shiqiang Yang:
Inferring lockstep behavior from connectivity pattern in large graphs. Knowl. Inf. Syst. 48(2): 399-428 (2016) - [j5]Meng Jiang, Peng Cui, Alex Beutel, Christos Faloutsos, Shiqiang Yang:
Catching Synchronized Behaviors in Large Networks: A Graph Mining Approach. ACM Trans. Knowl. Discov. Data 10(4): 35:1-35:27 (2016) - [j4]Meng Jiang, Alex Beutel, Peng Cui, Bryan Hooi, Shiqiang Yang, Christos Faloutsos:
Spotting Suspicious Behaviors in Multimodal Data: A General Metric and Algorithms. IEEE Trans. Knowl. Data Eng. 28(8): 2187-2200 (2016) - [c13]Meng Jiang, Peng Cui, Nicholas Jing Yuan, Xing Xie, Shiqiang Yang:
Little Is Much: Bridging Cross-Platform Behaviors through Overlapped Crowds. AAAI 2016: 13-19 - [c12]Meng Jiang:
Catching Social Media Advertisers with Strategy Analysis. CyberSafety@CIKM 2016: 5-10 - [c11]Huan Gui, Jialu Liu, Fangbo Tao, Meng Jiang, Brandon Norick, Jiawei Han:
Large-Scale Embedding Learning in Heterogeneous Event Data. ICDM 2016: 907-912 - [c10]Kun Kuang, Meng Jiang, Peng Cui, Shiqiang Yang:
Steering Social Media Promotions with Effective Strategies. ICDM 2016: 985-990 - [c9]Meng Jiang, Christos Faloutsos, Jiawei Han:
CatchTartan: Representing and Summarizing Dynamic Multicontextual Behaviors. KDD 2016: 945-954 - [i1]Jingbo Shang, Meng Jiang, Wenzhu Tong, Jinfeng Xiao, Jian Peng, Jiawei Han:
DPPred: An Effective Prediction Framework with Concise Discriminative Patterns. CoRR abs/1610.09778 (2016) - 2015
- [j3]Meng Jiang, Peng Cui, Xumin Chen, Fei Wang, Wenwu Zhu, Shiqiang Yang:
Social Recommendation with Cross-Domain Transferable Knowledge. IEEE Trans. Knowl. Data Eng. 27(11): 3084-3097 (2015) - [c8]Meng Jiang, Alex Beutel, Peng Cui, Bryan Hooi, Shiqiang Yang, Christos Faloutsos:
A General Suspiciousness Metric for Dense Blocks in Multimodal Data. ICDM 2015: 781-786 - 2014
- [j2]Meng Jiang, Peng Cui, Fei Wang, Wenwu Zhu, Shiqiang Yang:
Scalable Recommendation with Social Contextual Information. IEEE Trans. Knowl. Data Eng. 26(11): 2789-2802 (2014) - [c7]Meng Jiang, Peng Cui, Alex Beutel, Christos Faloutsos, Shiqiang Yang:
CatchSync: catching synchronized behavior in large directed graphs. KDD 2014: 941-950 - [c6]Meng Jiang, Peng Cui, Fei Wang, Xinran Xu, Wenwu Zhu, Shiqiang Yang:
FEMA: flexible evolutionary multi-faceted analysis for dynamic behavioral pattern discovery. KDD 2014: 1186-1195 - [c5]Meng Jiang, Peng Cui, Alex Beutel, Christos Faloutsos, Shiqiang Yang:
Inferring Strange Behavior from Connectivity Pattern in Social Networks. PAKDD (1) 2014: 126-138 - [c4]Meng Jiang, Peng Cui, Alex Beutel, Christos Faloutsos, Shiqiang Yang:
Detecting suspicious following behavior in multimillion-node social networks. WWW (Companion Volume) 2014: 305-306 - 2012
- [j1]Lu Liu, Feida Zhu, Meng Jiang, Jiawei Han, Lifeng Sun, Shiqiang Yang:
Mining diversity on social media networks. Multim. Tools Appl. 56(1): 179-205 (2012) - [c3]Meng Jiang, Peng Cui, Rui Liu, Qiang Yang, Fei Wang, Wenwu Zhu, Shiqiang Yang:
Social contextual recommendation. CIKM 2012: 45-54 - [c2]Meng Jiang, Peng Cui, Fei Wang, Qiang Yang, Wenwu Zhu, Shiqiang Yang:
Social recommendation across multiple relational domains. CIKM 2012: 1422-1431 - 2010
- [c1]Lu Liu, Jie Tang, Jiawei Han, Meng Jiang, Shiqiang Yang:
Mining topic-level influence in heterogeneous networks. CIKM 2010: 199-208
Coauthor Index
[b1] [c112] [c103] [i82] [i78] [i73] [j29] [j27] [c98] [c97] [c96] [c95] [c94] [c93] [c89] [c86] [i64] [i62] [i61] [i60] [i59] [i55] [i53] [j24] [c85] [c84] [c83] [c81] [c80] [c79] [i47] [i46] [i42] [i40] [i39] [i38] [c72] [c71] [c70] [c69] [c64] [c61] [c59] [i37] [i35] [i33] [i31] [i30] [i28] [c54] [c49] [c47] [c45] [c40] [c39] [i23] [i15] [i14] [i13] [i12] [c31] [c29]
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