---
title: "Greater Boston — works of 2022: 20 papers, the most cited first"
description: "20 works of Greater Boston from 2022 in our library, the most cited first. Among them: GLM: General Language Model Pretraining with…"
canonical: "https://research.elamur.ai/free/en/agglomerations/greater-boston/year/2022/"
---
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# Works of Greater Boston from 2022

20 works · the most cited first · [← Greater Boston](https://md.research.elamur.ai/free/en/agglomerations/greater-boston/)

1. **[GLM: General Language Model Pretraining with Autoregressive Blank Infilling](https://md.research.elamur.ai/free/en/papers/du-2022-glm-general-language-model-pretraining/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhengxiao Du, Yujie Qian, Xiao Liu, et al.*2022 · 1,452 citations*
2. [**Crosslingual Generalization through Multitask Finetuning arXiv:2211.01786**Niklas Muennighoff, Thomas Wang, Lintang Sutawika, et al.*2022 · 695 citations*](https://md.research.elamur.ai/free/en/papers/muennighoff-2022-crosslingual-generalization-through-multitask-finetuning/)
3. **[ToxiGen: A Large-Scale Machine-Generated Dataset for Adversarial and Implicit Hate Speech Detection](https://md.research.elamur.ai/free/en/papers/hartvigsen-2022-toxigen-large-scale-machine-generated/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Thomas Hartvigsen, Saadia Gabriel, Hamid Palangi, et al.*2022 · 571 citations*
4. **[Large language models are few-shot clinical information extractors](https://md.research.elamur.ai/free/en/papers/agrawal-2022-large-language-models-are-few/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Monica Agrawal, Stefan Hegselmann, Hunter Lang, et al.*2022 · 450 citations*
5. **[Do Prompt-Based Models Really Understand the Meaning of Their Prompts?](https://md.research.elamur.ai/free/en/papers/webson-2022-do-prompt-based-models-really/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Albert Webson, Ellie Pavlick*2022 · 398 citations*
6. **[RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/deng-2022-rlprompt-optimizing-discrete-text-prompts/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Mingkai Deng, Jianyu Wang, Cheng-Ping Hsieh, et al.*2022 · 328 citations*
7. **[DiffCSE: Difference-based Contrastive Learning for Sentence Embeddings](https://md.research.elamur.ai/free/en/papers/chuang-2022-diffcse-difference-based-contrastive-learning/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Yung-Sung Chuang, Rumen Dangovski, Hongyin Luo, et al.*2022 · 269 citations*
8. [**What learning algorithm is in-context learning? Investigations with linear models arXiv:2211.15661**Ekin Akyürek, Dale Schuurmans, Jacob Andreas, et al.*2022 · 225 citations*](https://md.research.elamur.ai/free/en/papers/akyurek-2022-learning-algorithm-context-learning-investigations/)
9. [**FOLIO: Natural Language Reasoning with First-Order Logic arXiv:2209.00840**Simeng Han, Hailey Schoelkopf, Yilun Zhao, et al.*2022 · 217 citations*](https://md.research.elamur.ai/free/en/papers/han-2022-folio-natural-language-reasoning-first/)
10. **[Systematic Inequalities in Language Technology Performance across the World's Languages](https://md.research.elamur.ai/free/en/papers/blasi-2022-systematic-inequalities-language-technology-performance/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Damian Blasi, Antonios Anastasopoulos, Graham Neubig*2022 · 214 citations*
11. **[LILA: A Unified Benchmark for Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/mishra-2022-lila-unified-benchmark-mathematical-reasoning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Swaroop Mishra, Matthew Finlayson, Pan Lu, et al.*2022 · 177 citations*
12. [**PromptSource: An Integrated Development Environment and Repository for Natural Language Prompts arXiv:2202.01279**Stephen H. Bach, Victor Sanh, Zheng-Xin Yong, et al.*2022 · 167 citations*](https://md.research.elamur.ai/free/en/papers/bach-2022-promptsource-integrated-development-environment-repository/)
13. **[Language Models as Agent Models](https://md.research.elamur.ai/free/en/papers/andreas-2022-language-models-as-agent-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jacob Andreas*2022 · 157 citations*
14. **[MasakhaNER 2.0: Africa-centric Transfer Learning for Named Entity Recognition](https://md.research.elamur.ai/free/en/papers/adelani-2022-masakhaner-2-0-africa-centric/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**David Ifeoluwa Adelani, Graham Neubig, Sebastian Ruder, et al.*2022 · 150 citations*
15. **[MultiHiertt: Numerical Reasoning over Multi Hierarchical Tabular and Textual Data](https://md.research.elamur.ai/free/en/papers/zhao-2022-multihiertt-numerical-reasoning-over-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yilun Zhao, Yunxiang Li, Chenying Li, et al.*2022 · 128 citations*
16. **[POLITICS: Pretraining with Same-story Article Comparison for Ideology Prediction and Stance Detection](https://md.research.elamur.ai/free/en/papers/liu-2022-politics-pretraining-same-story-article/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yujian Liu, Xinliang Frederick Zhang, David Wegsman, et al.*2022 · 70 citations*
17. **[Predicting scalar diversity with context-driven uncertainty over alternatives](https://md.research.elamur.ai/free/en/papers/hu-2022-predicting-scalar-diversity-context-driven/) [Workshop on Cognitive Modeling and Computational Linguistics (CMCL)](https://md.research.elamur.ai/free/en/venues/cmcl/)**Jennifer Hu, Roger Levy, Sebastian Schuster*2022 · 19 citations*
18. [**The Aligned Multimodal Movie Treebank: An audio, video, dependency-parse treebank**Adam Yaari, Jan DeWitt, Henry Hu, et al.*2022 · 7 citations*](https://md.research.elamur.ai/free/en/papers/yaari-2022-aligned-multimodal-movie-treebank-audio/)
19. [**Referring Expressions with Rational Speech Act Framework: A Probabilistic Approach**Hieu Le, Taufiq Daryanto, Fabian Zhafransyah, et al.*2022 · 2 citations*](https://md.research.elamur.ai/free/en/papers/le-2022-referring-expressions-rational-speech-act/)
20. [**Word-Embeddings Distinguish Denominal and Root-Derived Verbs in Semitic**Ido Benbaji, Omri Doron, Adele Henot-Mortier*2022 · 1 citation*](https://md.research.elamur.ai/free/en/papers/benbaji-2022-word-embeddings-distinguish-denominal-root/)
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