--- title: "Wen-tau Yih — papers of 2023 — 5 papers, the most cited first" description: "Wen-tau Yih — papers of 2023: 5 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/wen-tau-yih/year/2023/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/wen-tau-yih/year/2023/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Wen-tau Yih](https://md.research.elamur.ai/free/en/authors/wen-tau-yih/) / 2023 # Wen-tau Yih — papers of 2023 — 5 papers, the most cited first 5 papers · [all years of Wen-tau Yih](https://md.research.elamur.ai/free/en/authors/wen-tau-yih/#years) **[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 **[Task-aware Retrieval with Instructions](https://md.research.elamur.ai/free/en/papers/asai-2023-task-aware-retrieval-instructions/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Akari Asai, Timo Schick, Patrick Lewis, et al.*2023 · 132 citations* - [LEVER: Learning to Verify Language-to-Code Generation with Execution arXiv:2302.08468](https://md.research.elamur.ai/free/en/papers/ni-2023-lever-learning-verify-language-code/) — Ansong Ni, Srini Iyer, Dragomir Radev, et al. · 2023 · 126 citations **[How to Train Your Dragon: Diverse Augmentation Towards Generalizable Dense Retrieval](https://md.research.elamur.ai/free/en/papers/lin-2023-how-train-your-dragon-diverse/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Sheng-Chieh Lin, Akari Asai, Minghan Li, et al.*2023 · 116 citations*