Nayeon Lee
Artificial Intelligence · 2018–2023
A researcher in the Science corpus: 10 papers; trusts 174 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 375 citations into it
- Natural Language Processing — 332 citations into it
- Computer Vision and Pattern Recognition — 119 citations into it
- Evaluation & Benchmarks — 82 citations into it
- Large Language Models — 71 citations into it
- Safety, Robustness & Interpretability — 37 citations into it
- Information Systems — 20 citations into it
- Information Retrieval & Search — 13 citations into it
Whom Nayeon Lee trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- Diederik P. Kingma
- Ilya Sutskever
- Alex Krizhevsky
- Jacob Devlin
- Christopher D. Manning
- Yann LeCun
- Richard Socher
- Kaiming He
Who trusts Nayeon Lee overall
- Emily Dinan
- Yejin Bang
- Boshi Wang
- Ziwei Xu
- Nicola De Cao
- Yilun Du
- Hannah Devinney
- Orion Weller
- Angela Fan
- Ziwei Ji
Papers from Nayeon Lee's perspective
Ordered by how strongly the researchers Nayeon Lee 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)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet classification with deep convolutional neural networks
- Long Short-Term Memory
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
Their papers
- Survey of Hallucination in Natural Language Generation (2022) — 5,175 citations
- Factuality Enhanced Language Models for Open-Ended Text Generation (2022) — 310 citations
- Language Models as Fact Checkers? (2020) — 86 citations
- Improving Large-Scale Fact-Checking using Decomposable Attention Models and Lexical Tagging (2018) — 25 citations
- Towards Mitigating LLM Hallucination via Self Reflection (2023) — 496 citations
- A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity (2023) — 1,776 citations
- Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models (2022) — 2,561 citations
- Assessing Political Prudence of Open-domain Chatbots (2021) — 31 citations
- Exploring Social Bias in Chatbots using Stereotype Knowledge (2019) — 52 citations
- Understanding the Shades of Sexism in Popular TV Series (2019) — 5 citations