Xingxu Xie
Artificial Intelligence · 2023
A researcher in the Science corpus: 4 papers; trusts 12 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 249 citations into it
Whom Xingxu Xie trusts
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma (in Artificial Intelligence)
- Yoshua Bengio (in Artificial Intelligence)
- Geoffrey E. Hinton (in Artificial Intelligence)
- Christopher D. Manning (in Artificial Intelligence)
- Ilya Sutskever (in Artificial Intelligence)
- Jimmy Ba (in Artificial Intelligence)
- Quoc V. Le (in Artificial Intelligence)
- Christian Szegedy (in Artificial Intelligence)
- Oriol Vinyals (in Artificial Intelligence)
- Ian J. Goodfellow (in Artificial Intelligence)
Papers from Xingxu Xie's perspective
Ordered by how strongly the researchers Xingxu Xie trusts endorse each paper. Same corpus, a different order for every researcher.
- Attention is All you Need (Neural Information Processing Systems)
- 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
- Language Models are Unsupervised Multitask Learners
- Language Models are Few-Shot Learners (Neural Information Processing Systems)
- Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer (Journal of machine learning research)
- Improving Language Understanding by Generative Pre-Training
- Bleu: a Method for Automatic Evaluation of Machine Translation
- Explaining and Harnessing Adversarial Examples
- Decoupled Weight Decay Regularization
Their papers
- A Survey on Evaluation of Large Language Models (2023) — 3,582 citations
- PandaLM: An Automatic Evaluation Benchmark for LLM Instruction Tuning Optimization (2023) — 400 citations
- On the Robustness of ChatGPT: An Adversarial and Out-of-distribution Perspective (2023) — 310 citations
- PromptRobust: Towards Evaluating the Robustness of Large Language Models on Adversarial Prompts (2023) — 312 citations