--- title: "Who cites The CommitmentBank: Investigating projection in…" description: "234 papers of the Elamur Research library cite «The CommitmentBank: Investigating projection in naturally occurring discourse», found in their…" canonical: "https://research.elamur.ai/free/en/papers/enprag-2019-marneffe-commitmentbank-investigating-projection-naturally/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/enprag-2019-marneffe-commitmentbank-investigating-projection-naturally/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [The CommitmentBank: Investigating projection in…](https://md.research.elamur.ai/free/en/papers/enprag-2019-marneffe-commitmentbank-investigating-projection-naturally/) / cited by # Who cites «The CommitmentBank: Investigating projection in naturally occurring discourse» 234 papers of our library cite it (of the 140884 whose bibliographies we read) · 36 with a page here, the most cited first · page 1 of 2 · [← the paper](https://md.research.elamur.ai/free/en/papers/enprag-2019-marneffe-commitmentbank-investigating-projection-naturally/) **1** [2](https://md.research.elamur.ai/free/en/papers/enprag-2019-marneffe-commitmentbank-investigating-projection-naturally/cited-by/page/2/) [next →](https://md.research.elamur.ai/free/en/papers/enprag-2019-marneffe-commitmentbank-investigating-projection-naturally/cited-by/page/2/) - [SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems](https://md.research.elamur.ai/free/en/papers/wang-2019-superglue-stickier-benchmark-general-purpose/) — Alex Wang, Yada Pruksachatkun, Nikita Nangia, et al. · 2019 · 2 187 citations - [DeBERTa: Decoding-enhanced BERT with Disentangled Attention](https://md.research.elamur.ai/free/en/papers/he-2020-deberta-decoding-enhanced-bert-disentangled/) — Pengcheng He, Xiaodong Liu, Jianfeng Gao, et al. · 2020 · 1 800 citations - [Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models](https://md.research.elamur.ai/free/en/papers/srivastava-2022-imitation-game-quantifying-extrapolating-capabilities/) — Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, et al. · 2022 · 1 695 citations - [Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?](https://md.research.elamur.ai/free/en/papers/min-2022-rethinking-role-demonstrations-what-makes/) — Sewon Min, Xinxi Lyu, Ari Holtzman, et al. · 2022 · 1 423 citations - [A Comprehensive Overview of Large Language Models](https://md.research.elamur.ai/free/en/papers/naveed-2023-comprehensive-overview-large-language-models/) — Humza Naveed, Asad Ullah Khan, Shi Qiu, et al. · 2023 · 1 286 citations - [Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity](https://md.research.elamur.ai/free/en/papers/lu-2022-fantastically-ordered-prompts-where-find/) — Yao Lu, Max Bartolo, Alastair Moore, et al. · 2022 · 1 187 citations - [It's Not Just Size That Matters: Small Language Models Are Also Few-Shot Learners](https://md.research.elamur.ai/free/en/papers/schick-2021-it-s-not-just-size/) — Timo Schick, Hinrich Schütze · 2021 · 1 118 citations - [GPT Understands, Too](https://md.research.elamur.ai/free/en/papers/liu-2021-gpt-understands-too/) — Xiao Liu, Yanan Zheng, Zhengxiao Du, et al. · 2021 · 1 039 citations - [AdapterFusion: Non-Destructive Task Composition for Transfer Learning](https://md.research.elamur.ai/free/en/papers/pfeiffer-2020-adapterfusion-non-destructive-task-composition/) — Jonas Pfeiffer, Aishwarya Kamath, Andreas Rücklé, et al. · 2020 · 948 citations - [Is ChatGPT a General-Purpose Natural Language Processing Task Solver?](https://md.research.elamur.ai/free/en/papers/qin-2023-chatgpt-general-purpose-natural-language/) — Chengwei Qin, Aston Zhang, Zhuosheng Zhang, et al. · 2023 · 818 citations - [Calibrate Before Use: Improving Few-Shot Performance of Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2021-calibrate-before-use-improving-few/) — Tony Z. 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