Ee-Peng Lim
Artificial Intelligence · 2001–2023
A researcher in the Science corpus: 14 papers; trusts 90 researchers and is trusted by 42 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 206 citations into it; #6,904 of 35,345 by trust here, #5,565 by citations
- Natural Language Processing — 127 citations into it; #4,153 of 5,688 by trust here, #3,369 by citations
- Computer Vision and Pattern Recognition — 53 citations into it; #10,030 of 21,575 by trust here, #14,822 by citations
- Information Systems — 44 citations into it; #627 of 8,771 by trust here, #254 by citations
- Statistical and Nonlinear Physics — 26 citations into it; #2,572 of 10,127 by trust here, #1,004 by citations
- Sociology and Political Science — 22 citations into it
- Evaluation & Benchmarks — 17 citations into it
- Communication — 14 citations into it
Whom Ee-Peng Lim trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Jerome H. Friedman
- Yoshua Bengio
- Diederik P. Kingma
- Yoav Freund
- Alex Krizhevsky
- Leo Breiman
- Ilya Sutskever
- Susan T. Dumais
- Kalervo Järvelin
Who trusts Ee-Peng Lim overall
- B. Liu
- Leman Akoglu
- Arjun Mukherjee
- Lei Zhang
- Shebuti Rayana
- Kumar Ravi
- Mikalai Tsytsarau
- Kamran Kowsari
- Geli Fei
- Nasir Naveed
Papers from Ee-Peng Lim's perspective
Ordered by how strongly the researchers Ee-Peng Lim trusts endorse each paper. Same corpus, a different order for every researcher.
- Attention is All you Need (Neural Information Processing Systems)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Gradient-based learning applied to document recognition
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models (2023) — 783 citations
- Finding unusual review patterns using unexpected rules (2010) — 371 citations
- Detecting product review spammers using rating behaviors (2010) — 846 citations
- Characterizing Silent Users in Social Media Communities (2015) — 88 citations
- LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models (2023) — 497 citations
- MWPToolkit: An Open-Source Framework for Deep Learning-Based Math Word Problem Solvers (2021) — 79 citations
- Teacher-Student Networks with Multiple Decoders for Solving Math Word Problem (2020) — 72 citations
- Graph-to-Tree Learning for Solving Math Word Problems (2020) — 213 citations
- On Unravelling Opinions of Issue Specific-Silent Users in Social Media (2016) — 9 citations
- Detecting click fraud in online advertising: a data mining approach (2014) — 95 citations
- Comparing Twitter and Traditional Media Using Topic Models (2011) — 1,335 citations
- TwitterRank: finding topic-sensitive influential twitterers (2010) — 2,098 citations
- Hierarchical text classification and evaluation (2001) — 476 citations
- Mobile Commerce: Promises, Challenges and Research Agenda (2001) — 432 citations