Zhaojiang Lin
Artificial Intelligence · 2019–2021
A researcher in the Science corpus: 10 papers; trusts 466 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 345 citations into it; #20,932 of 35,345 by trust here, #8,893 by citations
- Natural Language Processing — 267 citations into it; #4,940 of 5,688 by trust here, #2,605 by citations
- Computer Vision and Pattern Recognition — 128 citations into it
- Large Language Models — 71 citations into it
- Evaluation & Benchmarks — 39 citations into it
- Model Architectures — 33 citations into it
- Representation & Self-Supervised Learning — 26 citations into it
- Dialogue & Conversational AI — 19 citations into it
Whom Zhaojiang Lin trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- Diederik P. Kingma
- Ilya Sutskever
- Alex Krizhevsky
- Jimmy Ba
- Kaiming He
- Yann LeCun
- Richard Socher
- Alex Graves
Who trusts Zhaojiang Lin overall
- Andrea Madotto
- Genta Indra Winata
- Chia-Hsuan Lee
- Renrui Zhang
- Pascale Fung
- Jinjie Ni
- Lingling Xu
- Qi Zhu
- Fei Mi
- Young-Jun Lee
Papers from Zhaojiang Lin's perspective
Ordered by how strongly the researchers Zhaojiang Lin 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
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- 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
- Plug-and-Play Conversational Models (2020) — 58 citations
- Language Models are Few-shot Multilingual Learners (2021) — 173 citations
- Continual Learning in Task-Oriented Dialogue Systems (2020) — 148 citations
- FaceFormer: Speech-Driven 3D Facial Animation with Transformers (2021) — 326 citations
- BiToD: A Bilingual Multi-Domain Dataset For Task-Oriented Dialogue Modeling (2021) — 68 citations
- MinTL: Minimalist Transfer Learning for Task-Oriented Dialogue Systems (2020) — 183 citations
- Exploring Versatile Generative Language Model Via Parameter-Efficient Transfer Learning (2020) — 196 citations
- Leveraging Slot Descriptions for Zero-Shot Cross-Domain Dialogue StateTracking (2021) — 97 citations
- Learning Knowledge Bases with Parameters for Task-Oriented Dialogue Systems (2020) — 72 citations
- Personalizing Dialogue Agents via Meta-Learning (2019) — 202 citations