Mengzhou Xia

Artificial Intelligence · 2019–2024

A researcher in the Science corpus: 9 papers; trusts 226 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 295 citations into it; #30,466 of 35,345 by trust here, #9,092 by citations
• Large Language Models — 99 citations into it
• Natural Language Processing — 94 citations into it
• Computer Vision and Pattern Recognition — 77 citations into it; #19,155 of 21,575 by trust here, #15,955 by citations
• Evaluation & Benchmarks — 46 citations into it
• Safety, Robustness & Interpretability — 41 citations into it
• Alignment & RLHF — 36 citations into it
• Efficiency & Compression — 28 citations into it

Whom Mengzhou Xia trusts overall

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

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

Who trusts Mengzhou Xia overall

1. Xiang Dai
2. Tanmay Garg
3. Xuhui Zhou
4. Sufeng Duan
5. Xisen Jin
6. Surafel Melaku Lakew
7. Yung-Sung Chuang
8. Xin Men
9. Bill Yuchen Lin
10. Heike Adel

Papers from Mengzhou Xia's perspective

Ordered by how strongly the researchers Mengzhou Xia 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. Attention is All you Need (Neural Information Processing Systems)
3. ImageNet classification with deep convolutional neural networks
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
7. ImageNet: A large-scale hierarchical image database
8. Gradient-based learning applied to document recognition
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• Demoting Racial Bias in Hate Speech Detection (2020) — 140 citations
• Choosing Transfer Languages for Cross-Lingual Learning (2019) — 265 citations
• Generalized Data Augmentation for Low-Resource Translation (2019) — 128 citations
• Training Trajectories of Language Models Across Scales (2022) — 81 citations
• SimPO: Simple Preference Optimization with a Reference-Free Reward (2024) — 1,086 citations
• LESS: Selecting Influential Data for Targeted Instruction Tuning (2024) — 544 citations
• Detecting Pretraining Data from Large Language Models (2023) — 424 citations
• Sheared LLaMA: Accelerating Language Model Pre-training via Structured Pruning (2023) — 500 citations
• Catastrophic Jailbreak of Open-source LLMs via Exploiting Generation (2023) — 525 citations