Junyang Lin
Artificial Intelligence · 2018–2024
A researcher in the Science corpus: 18 papers; trusts 990 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 645 citations into it
- Computer Vision and Pattern Recognition — 447 citations into it; #19,452 of 21,575 by trust here, #1,788 by citations
- Natural Language Processing — 226 citations into it
- Multimodal Learning — 189 citations into it; #1,208 of 1,211 by trust here, #216 by citations
- Large Language Models — 181 citations into it
- Evaluation & Benchmarks — 111 citations into it
- Model Architectures — 96 citations into it
- Representation & Self-Supervised Learning — 67 citations into it
Whom Junyang Lin trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Kaiming He
- Diederik P. Kingma
- Yoshua Bengio
- Ilya Sutskever
- Alex Krizhevsky
- Yann LeCun
- Ross B. Girshick
- Oriol Vinyals
- Karen Simonyan
Who trusts Junyang Lin overall
- Pengchuan Zhang
- Wenliang Dai
- Fei Zhao
- P. Xu
- Barret Zoph
- Peng Wang
- Jinze Bai
- Canwen Xu
- Xiujun Li
- Kun Zhou
Papers from Junyang Lin's perspective
Ordered by how strongly the researchers Junyang Lin trusts endorse each paper. Same corpus, a different order for every researcher.
- 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)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- CogView: Mastering Text-to-Image Generation via Transformers (2021) — 1,011 citations
- OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework (2022) — 1,080 citations
- Qwen-VL: A Frontier Large Vision-Language Model with Versatile Abilities (2023) — 1,892 citations
- Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond (2023) — 2,258 citations
- M6: A Chinese Multimodal Pretrainer (2021) — 152 citations
- M6-10T: A Sharing-Delinking Paradigm for Efficient Multi-Trillion Parameter Pretraining (2021) — 47 citations
- InterBERT: Vision-and-Language Interaction for Multi-modal Pretraining (2020) — 91 citations
- Diversity-Promoting GAN: A Cross-Entropy Based Generative Adversarial Network for Diversified Text Generation (2018) — 152 citations
- Qwen Technical Report (2023) — 4,095 citations
- Sketch and Refine: Towards Faithful and Informative Table-to-Text Generation (2021) — 25 citations
- An Image is Worth 1/2 Tokens After Layer 2: Plug-and-Play Inference Acceleration for Large Vision-Language Models (2024) — 629 citations
- Qwen2 Technical Report (2024) — 2,333 citations
- Qwen2-Audio Technical Report (2024) — 663 citations
- Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework (2022) — 252 citations
- Understanding and Improving Layer Normalization (2019) — 543 citations
- Towards Knowledge-Based Recommender Dialog System (2019) — 310 citations
- Global Encoding for Abstractive Summarization (2018) — 153 citations
- DP-GAN: Diversity-Promoting Generative Adversarial Network for Generating Informative and Diversified Text (2018) — 70 citations