---
title: "Research Triangle — works of 2022: 7 papers, the most cited first"
description: "7 works of Research Triangle from 2022 in our library, the most cited first. Among them: Emergent Abilities of Large Language Models…"
canonical: "https://research.elamur.ai/free/en/agglomerations/research-triangle/year/2022/"
---
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# Works of Research Triangle from 2022

7 works · the most cited first · [← Research Triangle](https://md.research.elamur.ai/free/en/agglomerations/research-triangle/)

1. [**Emergent Abilities of Large Language Models arXiv:2206.07682**Jason Wei, Yi Tay, Rishi Bommasani, et al.*2022 · 2,269 citations*](https://md.research.elamur.ai/free/en/papers/wei-2022-emergent-abilities-large-language-models/)
2. [**What Makes Good In-Context Examples for GPT-3? Proceedings of Deep Learning Inside Out (DeeLIO 2022): The 3rd Workshop on Knowledge Extraction and Integration for Deep Learning Architectures**Jiachang Liu, Dinghan Shen, Yizhe Zhang, et al.*2022 · 1,256 citations*](https://md.research.elamur.ai/free/en/papers/liu-2022-what-makes-good-context-examples/)
3. [**Alpa: Automating Inter- and Intra-Operator Parallelism for Distributed Deep Learning OSDI 2022**Lianmin Zheng, Zhuohan Li, Hao Zhang, et al.*2022 · 279 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2022-alpa-automating-inter-intra-operator/)
4. **[ASQA: Factoid Questions Meet Long-Form Answers](https://md.research.elamur.ai/free/en/papers/stelmakh-2022-asqa-factoid-questions-meet-long/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ivan Stelmakh, Yi Luan, Bhuwan Dhingra, et al.*2022 · 245 citations*
5. **[SummScreen: A Dataset for Abstractive Screenplay Summarization](https://md.research.elamur.ai/free/en/papers/chen-2022-summscreen-dataset-abstractive-screenplay-summarization/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mingda Chen, Zewei Chu, Sam Wiseman, et al.*2022 · 136 citations*
6. **[FactPEGASUS: Factuality-Aware Pre-training and Fine-tuning for Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/wan-2022-factpegasus-factuality-aware-pre-training/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**David Wan, Mohit Bansal*2022 · 101 citations*
7. **[Distributed NLI: Learning to Predict Human Opinion Distributions for Language Reasoning](https://md.research.elamur.ai/free/en/papers/zhou-2022-distributed-nli-learning-predict-human/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiang Zhou, Yixin Nie, Mohit Bansal*2022 · 36 citations*
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