Zhuosheng Zhang

Artificial Intelligence · 2018–2023

A researcher in the Science corpus: 17 papers; trusts 706 researchers and is trusted by 15 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 582 citations into it; #10,985 of 35,345 by trust here, #3,878 by citations
• Natural Language Processing — 415 citations into it; #2,266 of 5,688 by trust here, #1,351 by citations
• Computer Vision and Pattern Recognition — 258 citations into it
• Large Language Models — 122 citations into it
• Evaluation & Benchmarks — 108 citations into it
• Prompting & Reasoning — 68 citations into it; #190 of 359 by trust here, #201 by citations
• Multimodal Learning — 64 citations into it
• Model Architectures — 50 citations into it

Whom Zhuosheng Zhang trusts overall

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

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

Who trusts Zhuosheng Zhang overall

1. Shuailiang Zhang
2. Zhao Hai
3. Yuwei Wu
4. Guohao Li
5. Chenfei Wu
6. Hai Zhao
7. Shukang Yin
8. Jie Huang
9. Qingxiu Dong
10. M. Pourreza

Papers from Zhuosheng Zhang's perspective

Ordered by how strongly the researchers Zhuosheng 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. 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. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
8. Gradient-based learning applied to document recognition
9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• Multimodal Chain-of-Thought Reasoning in Language Models (2023) — 914 citations
• Automatic Chain of Thought Prompting in Large Language Models (2022) — 1,007 citations
• Dual Co-Matching Network for Multi-choice Reading Comprehension (2019) — 138 citations
• Is ChatGPT a General-Purpose Natural Language Processing Task Solver? (2023) — 872 citations
• Semantics-aware BERT for Language Understanding (2019) — 401 citations
• Retrospective Reader for Machine Reading Comprehension (2020) — 241 citations
• Modeling Multi-turn Conversation with Deep Utterance Aggregation (2018) — 256 citations
• SG-Net: Syntax-Guided Machine Reading Comprehension (2019) — 195 citations
• MedAgents: Large Language Models as Collaborators for Zero-shot Medical Reasoning (2023) — 457 citations
• Universal Multimodal Representation for Language Understanding (2023) — 35 citations
• Task-specific Objectives of Pre-trained Language Models for Dialogue Adaptation (2020) — 23 citations
• Data-dependent Gaussian Prior Objective for Language Generation (2020) — 69 citations
• Neural Machine Translation with Universal Visual Representation (2020) — 122 citations
• Effective Subword Segmentation for Text Comprehension (2018) — 30 citations
• Subword-augmented Embedding for Cloze Reading Comprehension (2018) — 32 citations
• Effective Character-Augmented Word Embedding for Machine Reading Comprehension (2018) — 17 citations
• I Know What You Want: Semantic Learning for Text Comprehension (2018) — 21 citations