Ge Zhang
Artificial Intelligence · with Chen · 2023–2024
A researcher in the Science corpus: 9 papers; trusts 60 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 342 citations into it
- Large Language Models — 160 citations into it
- Computer Vision and Pattern Recognition — 113 citations into it
- Natural Language Processing — 89 citations into it
- Evaluation & Benchmarks — 78 citations into it
- Prompting & Reasoning — 70 citations into it
Whom Ge Zhang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Diederik P. Kingma
- Yoshua Bengio
- Alex Krizhevsky
- Ilya Sutskever
- Kaiming He
- Yann LeCun
- Alex Graves
- Dan Hendrycks
- Jimmy Ba
Papers from Ge Zhang's perspective
Ordered by how strongly the researchers Ge Zhang trusts endorse each paper. Same corpus, a different order for every researcher.
- Attention is All you Need (Neural Information Processing Systems)
- 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)
- Long Short-Term Memory
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
Their papers
- MMMU: A Massive Multi-Discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI (2023) — 2,391 citations
- Yi: Open Foundation Models by 01.AI (2024) — 869 citations
- MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning (2023) — 596 citations
- MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark (2024) — 1,918 citations
- Long-context LLMs Struggle with Long In-context Learning (2024) — 375 citations
- MAmmoTH2: Scaling Instructions from the Web (2024) — 170 citations
- OpenCodeInterpreter: Integrating Code Generation with Execution and Refinement (2024) — 279 citations
- Second Thoughts are Best: Learning to Re-Align With Human Values from Text Edits (2023) — 44 citations
- MERT: Acoustic Music Understanding Model with Large-Scale Self-supervised Training (2023) — 320 citations