--- title: "Luke Zettlemoyer — papers of 2023 — Elamur Research" description: "Luke Zettlemoyer — papers of 2023: 16 papers on Elamur Research, the most cited first — what each work is about in our own words." canonical: "https://research.elamur.ai/free/en/authors/luke-zettlemoyer/year/2023/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/luke-zettlemoyer/year/2023/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Luke Zettlemoyer](https://md.research.elamur.ai/free/en/authors/luke-zettlemoyer/) / 2023 # Luke Zettlemoyer — papers of 2023 — Elamur Research 16 papers · [all years of Luke Zettlemoyer](https://md.research.elamur.ai/free/en/authors/luke-zettlemoyer/#years) **[QLoRA: Efficient Finetuning of Quantized LLMs](https://md.research.elamur.ai/free/en/papers/dettmers-2023-qlora-efficient-finetuning-quantized-llms/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, et al.*2023 · 2,929 citations* **[Toolformer: Language Models Can Teach Themselves to Use Tools](https://md.research.elamur.ai/free/en/papers/schick-2023-toolformer-language-models-can-teach/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Timo Schick, Jane Dwivedi-Yu, Roberto Dessì, et al.*2023 · 2,065 citations* **[FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation](https://md.research.elamur.ai/free/en/papers/min-2023-factscore-fine-grained-atomic-evaluation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Sewon Min, Kalpesh Krishna, Xinxi Lyu, et al.*2023 · 987 citations* - [REPLUG: Retrieval-Augmented Black-Box Language Models arXiv:2301.12652](https://md.research.elamur.ai/free/en/papers/shi-2023-replug-retrieval-augmented-black-box/) — Weijia Shi, Sewon Min, Michihiro Yasunaga, et al. · 2023 · 492 citations **[Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters](https://md.research.elamur.ai/free/en/papers/wang-2023-understanding-chain-thought-prompting-empirical/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Boshi Wang, Sewon Min, Xiang Deng, et al.*2023 · 272 citations* **[The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variants](https://md.research.elamur.ai/free/en/papers/bandarkar-2023-belebele-benchmark-parallel-reading-comprehension/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lucas Bandarkar, Davis Liang, Benjamin Muller, et al.*2023 · 262 citations* **[In-context Examples Selection for Machine Translation](https://md.research.elamur.ai/free/en/papers/agrawal-2023-context-examples-selection-machine-translation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Sweta Agrawal, Chunting Zhou, Mike Lewis, et al.*2023 · 243 citations* - [RA-DIT: Retrieval-Augmented Dual Instruction Tuning arXiv:2310.01352](https://md.research.elamur.ai/free/en/papers/lin-2023-ra-dit-retrieval-augmented-dual/) — Xi Victoria Lin, Xilun Chen, Mingda Chen, et al. · 2023 · 149 citations - [Self-Alignment with Instruction Backtranslation arXiv:2308.06259](https://md.research.elamur.ai/free/en/papers/li-2023-self-alignment-instruction-backtranslation/) — Xian Li, Ping Yu, Chunting Zhou, et al. · 2023 · 139 citations **[XLM-V: Overcoming the Vocabulary Bottleneck in Multilingual Masked Language Models](https://md.research.elamur.ai/free/en/papers/liang-2023-xlm-v-overcoming-vocabulary-bottleneck/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Davis Liang, Hila Gonen, Yuning Mao, et al.*2023 · 120 citations* - [Dictionary-based Phrase-level Prompting of Large Language Models for Machine Translation arXiv:2302.07856](https://md.research.elamur.ai/free/en/papers/ghazvininejad-2023-dictionary-based-phrase-level-prompting/) — Marjan Ghazvininejad, Hila Gonen, Luke Zettlemoyer · 2023 · 95 citations - [CREPE: Open-Domain Question Answering with False Presuppositions](https://md.research.elamur.ai/free/en/papers/yu-2023-crepe-open-domain-question-answering/) — Xinyan Yu, Sewon Min, Luke Zettlemoyer, et al. · English · 66 citations **[Questions Are All You Need to Train a Dense Passage Retriever](https://md.research.elamur.ai/free/en/papers/sachan-2023-questions-are-all-you-need/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Devendra Singh Sachan, Mike Lewis, Dani Yogatama, et al.*2023 · 65 citations* - [In-context Pretraining: Language Modeling Beyond Document Boundaries arXiv:2310.10638](https://md.research.elamur.ai/free/en/papers/shi-2023-context-pretraining-language-modeling-document/) — Weijia Shi, Sewon Min, Maria Lomeli, et al. · 2023 · 61 citations - [Shepherd: A Critic for Language Model Generation arXiv:2308.04592](https://md.research.elamur.ai/free/en/papers/wang-2023-shepherd-critic-language-model-generation/) — Tianlu Wang, Ping Yu, Xiaoqing Ellen Tan, et al. · 2023 · 60 citations - [Scaling Laws for Generative Mixed-Modal Language Models arXiv:2301.03728](https://md.research.elamur.ai/free/en/papers/aghajanyan-2023-scaling-laws-generative-mixed-modal/) — Armen Aghajanyan, Lili Yu, Alexis Conneau, et al. · 2023 · 45 citations