Jiacheng Xu
Artificial Intelligence · with Wang · 2021–2023
A researcher in the Science corpus: 4 papers; trusts 25 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 37 citations into it
- Natural Language Processing — 21 citations into it
- Computer Vision and Pattern Recognition — 12 citations into it
- Evaluation & Benchmarks — 6 citations into it
Whom Jiacheng Xu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Pranav Rajpurkar
- Ilya Sutskever
- Yoshua Bengio
- Geoffrey E. Hinton
- Sergey Ioffe
- Dzmitry Bahdanau
- Jacob Devlin
- Diederik P. Kingma
- Christian Szegedy
- Alex Krizhevsky
Papers from Jiacheng Xu's perspective
Ordered by how strongly the researchers Jiacheng Xu 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
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- 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)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Gradient-based learning applied to document recognition
Their papers
- A Long Way to Go: Investigating Length Correlations in RLHF (2023) — 284 citations
- Disfl-QA: A Benchmark Dataset for Understanding Disfluencies in Question Answering (2021) — 37 citations
- Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models (2023) — 266 citations
- Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models (2022) — 2,561 citations