default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
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
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 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- [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) - [c113]Zhenyu Wu, Meng Jiang, Chao Shen:
Get an A in Math: Progressive Rectification Prompting. AAAI 2024: 19288-19296 - [c112]Zheyuan Liu, Guangyao Dou, Zhaoxuan Tan, Yijun Tian, Meng Jiang:
Towards Safer Large Language Models through Machine Unlearning. ACL (Findings) 2024: 1817-1829 - [c111]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 - [c110]Ziyi Kou, Yijun Tian, Meng Jiang, Xiangliang Zhang:
FaDE: A Face Segment Driven Identity Anonymization Framework For Fair Face Recognition. CIKM 2024: 1121-1131 - [c109]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 - [c108]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 - [c107]Zhaoxuan Tan, Zheyuan Liu, Meng Jiang:
Personalized Pieces: Efficient Personalized Large Language Models through Collaborative Efforts. EMNLP 2024: 6459-6475 - [c106]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 - [c105]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 - [c104]Bang Nguyen, Mengxia Yu, Yun Huang, Meng Jiang:
Reference-based Metrics Disprove Themselves in Question Generation. EMNLP (Findings) 2024: 13651-13666 - [c103]Noah Ziems, Zhihan Zhang, Meng Jiang:
TOWER: Tree Organized Weighting for Evaluating Complex Instructions. EMNLP (Findings) 2024: 13803-13810 - [c102]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 - [c101]Ziyi Kou, Shichao Pei, Meng Jiang, Xiangliang Zhang:
RAt: Injecting Implicit Bias for Text-To-Image Prompt Refinement Models. EMNLP 2024: 20561-20570 - [c100]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 - [c99]Zhenyu Wu, Chao Shen, Meng Jiang:
Instructing Large Language Models to Identify and Ignore Irrelevant Conditions. NAACL-HLT 2024: 6799-6819 - [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. 46(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. 46(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]