Chien-Sheng Wu
Artificial Intelligence · 2018–2022
A researcher in the Science corpus: 12 papers; trusts 528 researchers and is trusted by 50 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 469 citations into it; #3,966 of 35,345 by trust here, #3,523 by citations
- Natural Language Processing — 358 citations into it; #1,107 of 5,688 by trust here, #1,059 by citations
- Computer Vision and Pattern Recognition — 125 citations into it
- Evaluation & Benchmarks — 107 citations into it
- Large Language Models — 56 citations into it
- Model Architectures — 42 citations into it
- Representation & Self-Supervised Learning — 41 citations into it; #3,093 of 3,145 by trust here, #1,811 by citations
- Information Systems — 28 citations into it
Whom Chien-Sheng Wu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Yoshua Bengio
- Geoffrey E. Hinton
- Alex Graves
- Oriol Vinyals
- Jimmy Ba
- Ilya Sutskever
- Christopher D. Manning
- Alex Krizhevsky
- Richard Socher
Who trusts Chien-Sheng Wu overall
- Andrea Madotto
- Zhaojiang Lin
- Ehsan Hosseini-Asl
- Jianguo Zhang
- Jinjie Ni
- Chia-Hsuan Lee
- Fei Mi
- Genta Indra Winata
- Min Yang
- Richard Socher
Papers from Chien-Sheng Wu's perspective
Ordered by how strongly the researchers Chien-Sheng Wu trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet classification with deep convolutional neural networks
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models (2022) — 362 citations
- A Simple Language Model for Task-Oriented Dialogue (2020) — 583 citations
- Transferable Multi-Domain State Generator for Task-Oriented Dialogue Systems (2019) — 481 citations
- Mem2Seq: Effectively Incorporating Knowledge Bases into End-to-End Task-Oriented Dialog Systems (2018) — 320 citations
- Revisiting the Gold Standard: Grounding Summarization Evaluation with Robust Human Evaluation (2022) — 179 citations
- Global-to-local Memory Pointer Networks for Task-Oriented Dialogue (2019) — 173 citations
- TOD-BERT: Pre-trained Natural Language Understanding for Task-Oriented Dialogue (2020) — 350 citations
- GraPPa: Grammar-Augmented Pre-Training for Table Semantic Parsing (2020) — 296 citations
- Improving Large-Scale Fact-Checking using Decomposable Attention Models and Lexical Tagging (2018) — 25 citations
- Discriminative Nearest Neighbor Few-Shot Intent Detection by Transferring Natural Language Inference (2020) — 99 citations
- Find or Classify? Dual Strategy for Slot-Value Predictions on Multi-Domain Dialog State Tracking (2019) — 179 citations
- Personalizing Dialogue Agents via Meta-Learning (2019) — 202 citations