Ji Zhang

Computer Vision and Pattern Recognition · 2021–2024

A researcher in the Science corpus: 11 papers; trusts 756 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 425 citations into it
• Artificial Intelligence — 406 citations into it
• Multimodal Learning — 265 citations into it
• Large Language Models — 94 citations into it
• Natural Language Processing — 77 citations into it
• Evaluation & Benchmarks — 73 citations into it
• Representation & Self-Supervised Learning — 61 citations into it
• Optimization & Training — 14 citations into it

Whom Ji Zhang trusts overall

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

1. Kaiming He
2. Diederik P. Kingma
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Yoshua Bengio
6. Ilya Sutskever
7. Karen Simonyan
8. Yann LeCun
9. Ross B. Girshick
10. Andrew Zisserman

Papers from Ji Zhang's perspective

Ordered by how strongly the researchers Ji Zhang 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. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. Gradient-based learning applied to document recognition
9. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• mPLUG-Owl: Modularization Empowers Large Language Models with Multimodality (2023) — 1,270 citations
• mPLUG: Effective and Efficient Vision-Language Learning by Cross-modal Skip-connections (2022) — 295 citations
• X-CLIP: End-to-End Multi-grained Contrastive Learning for Video-Text Retrieval (2022) — 500 citations
• mPLUG-OwI2: Revolutionizing Multi-modal Large Language Model with Modality Collaboration (2023) — 705 citations
• mPLUG-Owl3: Towards Long Image-Sequence Understanding in Multi-Modal Large Language Models (2024) — 307 citations
• Mobile-Agent: Autonomous Multi-Modal Mobile Device Agent with Visual Perception (2024) — 313 citations
• CValues: Measuring the Values of Chinese Large Language Models from Safety to Responsibility (2023) — 108 citations
• Continual Few-shot Intent Detection (2022) — 17 citations
• HiTeA: Hierarchical Temporal-Aware Video-Language Pre-training (2022) — 107 citations
• ROSITA: Enhancing Vision-and-Language Semantic Alignments via Cross- and Intra-modal Knowledge Integration (2021) — 60 citations
• Achieving Human Parity on Visual Question Answering (2021) — 24 citations