Bing Nie

Artificial Intelligence · 2023

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 28 citations into it

Whom Bing Nie trusts overall

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

1. Eleni Adamopoulou

Papers from Bing Nie's perspective

Ordered by how strongly the researchers Bing Nie trusts endorse each paper. Same corpus, a different order for every researcher.

1. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
2. Language Models are Few-Shot Learners (Neural Information Processing Systems)
3. Improving Language Understanding by Generative Pre-Training
4. RoBERTa: A Robustly Optimized BERT Pretraining Approach (arXiv.org)
5. XLNet: Generalized Autoregressive Pretraining for Language Understanding (Neural Information Processing Systems)
6. Why Does Unsupervised Pre-training Help Deep Learning?
7. On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜
8. Energy and Policy Considerations for Deep Learning in NLP
9. OpenAI Gym
10. What Makes Good In-Context Examples for GPT-3?

Their papers

• ChatGPT and a new academic reality: Artificial Intelligence‐written research papers and the ethics of the large language models in scholarly publishing (2023) — 785 citations