---
title: "Denny Zhou — papers"
description: "Denny Zhou: 15 papers in the Elamur Research library (2020–2023) — our summary of each, its ideas, references and who cites it."
canonical: "https://research.elamur.ai/free/en/authors/denny-zhou/"
---
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# Denny Zhou

15 papers on this site (2020–2023)

[OpenAlex](https://openalex.org/A5061512999) · h-index 33 · 89 works · 15817 citations (openalex-snapshot, 2026-10-14)

Profile data from OpenAlex; authors with the same name are not always told apart.

- [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/) — Mirac Suzgun, Nathan Scales, Nathanael Schärli, et al. · 2023
- [FreshLLMs: Refreshing Large Language Models with Search Engine Augmentation](https://md.research.elamur.ai/free/en/papers/vu-2023-freshllms-refreshing-large-language-models/) — Tu Vu, Mohit Iyyer, Xuezhi Wang, et al. · 2023
- [Instruction-Following Evaluation for Large Language Models](https://md.research.elamur.ai/free/en/papers/zhou-2023-instruction-following-evaluation-large-language/) — Jeffrey Zhou, Tianjian Lu, Swaroop Mishra, et al. · 2023
- [Large Language Models as Optimizers](https://md.research.elamur.ai/free/en/papers/yang-2023-large-language-models-optimizers/) — Chengrun Yang, Xuezhi Wang, Yifeng Lu, et al. · 2023
- [Large Language Models Can Be Easily Distracted by Irrelevant Context](https://md.research.elamur.ai/free/en/papers/shi-2023-large-language-models-easily-distracted/) — Freda Shi, Xinyun Chen, Kanishka Misra, et al. · 2023
- [Large Language Models Cannot Self-Correct Reasoning Yet](https://md.research.elamur.ai/free/en/papers/huang-2023-large-language-models-cannot-self/) — Jie Huang, Xinyun Chen, Swaroop Mishra, et al. · 2023
- [Larger language models do in-context learning differently](https://md.research.elamur.ai/free/en/papers/wei-2023-larger-language-models-context-learning/) — Jerry Wei, Jason Wei, Yi Tay, et al. · 2023
- [The Flan Collection: Designing Data and Methods for Effective Instruction Tuning](https://md.research.elamur.ai/free/en/papers/longpre-2023-flan-collection-designing-data-methods/) — Shayne Longpre, Le Hou, Tu Vu, et al. · 2023
- [Chain-of-Thought Prompting Elicits Reasoning in Large Language Models](https://md.research.elamur.ai/free/en/papers/wei-2022-chain-thought-prompting-elicits-reasoning/) — Jason Wei, Xuezhi Wang, Dale Schuurmans, et al. · 2022
- [Emergent Abilities of Large Language Models](https://md.research.elamur.ai/free/en/papers/wei-2022-emergent-abilities-large-language-models/) — Jason Wei, Yi Tay, Rishi Bommasani, et al. · 2022
- [Language Models are Multilingual Chain-of-Thought Reasoners](https://md.research.elamur.ai/free/en/papers/shi-2022-language-models-multilingual-chain-thought/) — Freda Shi, Mirac Suzgun, Markus Freitag, et al. · 2022
- [Self-Consistency Improves Chain of Thought Reasoning in Language Models](https://md.research.elamur.ai/free/en/papers/wang-2022-self-consistency-improves-chain-thought/) — Xuezhi Wang, Jason Wei, Dale Schuurmans, et al. · 2022
- [UL2: Unifying Language Learning Paradigms](https://md.research.elamur.ai/free/en/papers/tay-2022-ul2-unifying-language-learning-paradigms/) — Yi Tay, Mostafa Dehghani, Vinh Q. Tran, et al. · 2022
- [What learning algorithm is in-context learning? Investigations with linear models](https://md.research.elamur.ai/free/en/papers/akyurek-2022-learning-algorithm-context-learning-investigations/) — Ekin Akyürek, Dale Schuurmans, Jacob Andreas, et al. · 2022
- [MobileBERT: a Compact Task-Agnostic BERT for Resource-Limited Devices](https://md.research.elamur.ai/free/en/papers/sun-2020-mobilebert-compact-task-agnostic-bert/) — Zhiqing Sun, Hongkun Yu, Xiaodan Song, et al. · 2020