Dongxu Li
Computer Vision and Pattern Recognition · 2019–2024
A researcher in the Science corpus: 8 papers; trusts 919 researchers and is trusted by 316 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 255 citations into it; #2,300 of 21,575 by trust here, #1,181 by citations
- Artificial Intelligence — 222 citations into it; #3,706 of 35,345 by trust here, #1,666 by citations
- Multimodal Learning — 125 citations into it; #129 of 1,211 by trust here, #101 by citations
- Model Architectures — 46 citations into it
- Large Language Models — 42 citations into it; #108 of 799 by trust here, #209 by citations
- Natural Language Processing — 41 citations into it
- Representation & Self-Supervised Learning — 41 citations into it
- Evaluation & Benchmarks — 34 citations into it
Whom Dongxu Li trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Alex Krizhevsky
- Diederik P. Kingma
- Kaiming He
- Yoshua Bengio
- Karen Simonyan
- Ilya Sutskever
- Yann LeCun
- Ross B. Girshick
- Andrew Zisserman
Who trusts Dongxu Li overall
- Bo Li
- Junnan Li
- Antoine Yang
- Yuanhan Zhang
- Qinghao Ye
- Renrui Zhang
- Runpei Dong
- Zhiqiu Lin
- Lin Chen
- Haotian Liu
Papers from Dongxu Li's perspective
Ordered by how strongly the researchers Dongxu Li 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
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- ImageNet Large Scale Visual Recognition Challenge
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
Their papers
- BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation (2022) — 7,032 citations
- BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models (2023) — 8,665 citations
- InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning (2023) — 3,705 citations
- BLIP-Diffusion: Pre-trained Subject Representation for Controllable Text-to-Image Generation and Editing (2023) — 559 citations
- LongVideoBench: A Benchmark for Long-context Interleaved Video-Language Understanding (2024) — 654 citations
- cosFormer: Rethinking Softmax in Attention (2022) — 331 citations
- Word-level Deep Sign Language Recognition from Video: A New Large-scale Dataset and Methods Comparison (2019) — 648 citations
- Align and Prompt: Video-and-Language Pre-training with Entity Prompts (2021) — 230 citations