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title: "Quoc Viet Le — papers of 2023 — 6 papers, the most cited first"
description: "Quoc Viet Le — papers of 2023: 6 papers on Elamur Research, the most cited first — what each work is about in our own words."
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# Quoc Viet Le — papers of 2023 — 6 papers, the most cited first

6 papers · [all years of Quoc Viet Le](https://md.research.elamur.ai/free/en/authors/quoc-viet-le/#years)

**[Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them](https://md.research.elamur.ai/free/en/papers/suzgun-2023-challenging-big-bench-tasks-whether/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mirac Suzgun, Nathan Scales, Nathanael Schärli, et al.*2023 · 1,119 citations*

- [The Flan Collection: Designing Data and Methods for Effective Instruction Tuning arXiv:2301.13688](https://md.research.elamur.ai/free/en/papers/longpre-2023-flan-collection-designing-data-methods/) — Shayne Longpre, Le Hou, Tu Vu, et al. · 2023 · 607 citations
- [Large Language Models as Optimizers arXiv:2309.03409](https://md.research.elamur.ai/free/en/papers/yang-2023-large-language-models-optimizers/) — Chengrun Yang, Xuezhi Wang, Yifeng Lu, et al. · 2023 · 413 citations
- [FreshLLMs: Refreshing Large Language Models with Search Engine Augmentation arXiv:2310.03214](https://md.research.elamur.ai/free/en/papers/vu-2023-freshllms-refreshing-large-language-models/) — Tu Vu, Mohit Iyyer, Xuezhi Wang, et al. · 2023 · 134 citations
- [Simple synthetic data reduces sycophancy in large language models arXiv:2308.03958](https://md.research.elamur.ai/free/en/papers/wei-2023-simple-synthetic-data-reduces-sycophancy/) — Jerry Wei, Da Huang, Yifeng Lu, et al. · 2023 · 134 citations
- [Take a Step Back: Evoking Reasoning via Abstraction in Large Language Models arXiv:2310.06117](https://md.research.elamur.ai/free/en/papers/zheng-2023-take-step-back-evoking-reasoning/) — Huaixiu Steven Zheng, Swaroop Mishra, Xinyun Chen, et al. · 2023 · 126 citations