Chang Zhou

Artificial Intelligence · 2017–2024

A researcher in the Science corpus: 22 papers; trusts 998 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 687 citations into it; #34,786 of 35,345 by trust here, #2,577 by citations
• Computer Vision and Pattern Recognition — 523 citations into it; #20,851 of 21,575 by trust here, #2,050 by citations
• Natural Language Processing — 205 citations into it; #5,618 of 5,688 by trust here, #2,132 by citations
• Multimodal Learning — 196 citations into it
• Large Language Models — 175 citations into it
• Information Systems — 109 citations into it; #8,258 of 8,771 by trust here, #1,220 by citations
• Representation & Self-Supervised Learning — 106 citations into it
• Generative Models — 103 citations into it

Whom Chang Zhou trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Ilya Sutskever
5. Alex Krizhevsky
6. Kaiming He
7. Yann LeCun
8. Oriol Vinyals
9. Jimmy Ba
10. Alex Graves

Who trusts Chang Zhou overall

1. Yukuo Cen
2. Hongwei Wang
3. Daokun Zhang
4. Pengyu Zhao
5. Ming Ding
6. Shuai Zhang
7. Yufei Feng
8. Xiaowen Huang
9. Xu Han
10. Swering With Extra

Papers from Chang Zhou's perspective

Ordered by how strongly the researchers Chang Zhou trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. 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
• Cognitive Graph for Multi-Hop Reading Comprehension at Scale (2019) — 246 citations
• M6-UFC: Unifying Multi-Modal Controls for Conditional Image Synthesis via Non-Autoregressive Generative Transformers (2021) — 49 citations
• M6-10T: A Sharing-Delinking Paradigm for Efficient Multi-Trillion Parameter Pretraining (2021) — 47 citations
• AliGraph: A Comprehensive Graph Neural Network Platform (2019) — 469 citations
• Scaling Relationship on Learning Mathematical Reasoning with Large Language Models (2023) — 354 citations
• Qwen Technical Report (2023) — 4,095 citations
• Sketch and Refine: Towards Faithful and Informative Table-to-Text Generation (2021) — 25 citations
• Controllable Multi-Interest Framework for Recommendation (2020) — 384 citations
• Deep Interest Evolution Network for Click-Through Rate Prediction (2018) — 1,336 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-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution (2024) — 4,557 citations
• Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework (2022) — 252 citations
• Are we really making much progress?: Revisiting, benchmarking and refining heterogeneous graph neural networks (2021) — 479 citations
• UFC-BERT: Unifying Multi-Modal Controls for Conditional Image Synthesis (2021) — 43 citations
• CogLTX: Applying BERT to Long Texts (2020) — 161 citations
• Learning Disentangled Representations for Recommendation (2019) — 399 citations