---
title: "Denny Zhou — all works — Elamur Research"
description: "All 43 works of Denny Zhou in the Elamur Research library, the most cited first: our summaries where we have them, else the original."
canonical: "https://research.elamur.ai/free/en/authors/denny-zhou/works/"
---
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# Denny Zhou — all works

43 works · [← Denny Zhou](https://md.research.elamur.ai/free/en/authors/denny-zhou/)

1. [**Chain-of-Thought Prompting Elicits Reasoning in Large Language Models arXiv:2201.11903**Jason Wei, Xuezhi Wang, Dale Schuurmans, et al.*2022 · 11,499 citations*](https://md.research.elamur.ai/free/en/papers/wei-2022-chain-thought-prompting-elicits-reasoning/)
2. **[Scaling Instruction-Finetuned Language Models ↗](https://arxiv.org/abs/2210.11416) arXiv:2210.11416 · no summary yet**Hyung Won Chung et al.*2022 · 3,392 citations*
3. [**Self-Consistency Improves Chain of Thought Reasoning in Language Models arXiv:2203.11171**Xuezhi Wang, Jason Wei, Dale Schuurmans, et al.*2022 · 3,121 citations*](https://md.research.elamur.ai/free/en/papers/wang-2022-self-consistency-improves-chain-thought/)
4. [**Emergent Abilities of Large Language Models arXiv:2206.07682**Jason Wei, Yi Tay, Rishi Bommasani, et al.*2022 · 2,269 citations*](https://md.research.elamur.ai/free/en/papers/wei-2022-emergent-abilities-large-language-models/)
5. **[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*
6. **[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/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhiqing Sun, Hongkun Yu, Xiaodan Song, et al.*2020 · 1,016 citations*
7. [**Instruction-Following Evaluation for Large Language Models arXiv:2311.07911**Jeffrey Zhou, Tianjian Lu, Swaroop Mishra, et al.*2023 · 615 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2023-instruction-following-evaluation-large-language/)
8. [**The Flan Collection: Designing Data and Methods for Effective Instruction Tuning arXiv:2301.13688**Shayne Longpre, Le Hou, Tu Vu, et al.*2023 · 607 citations*](https://md.research.elamur.ai/free/en/papers/longpre-2023-flan-collection-designing-data-methods/)
9. **[DeepFusion: Lidar-Camera Deep Fusion for Multi-Modal 3D Object Detection ↗](https://doi.org/10.1109/cvpr52688.2022.01667) IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yet**Yingwei Li et al.*2022 · 563 citations*
10. [**Large Language Models Can Be Easily Distracted by Irrelevant Context arXiv:2302.00093**Freda Shi, Xinyun Chen, Kanishka Misra, et al.*2023 · 534 citations*](https://md.research.elamur.ai/free/en/papers/shi-2023-large-language-models-easily-distracted/)
11. [**Language Models are Multilingual Chain-of-Thought Reasoners arXiv:2210.03057**Freda Shi, Mirac Suzgun, Markus Freitag, et al.*2022 · 494 citations*](https://md.research.elamur.ai/free/en/papers/shi-2022-language-models-multilingual-chain-thought/)
12. [**Large Language Models as Optimizers arXiv:2309.03409**Chengrun Yang, Xuezhi Wang, Yifeng Lu, et al.*2023 · 413 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-large-language-models-optimizers/)
13. [**Large Language Models Cannot Self-Correct Reasoning Yet arXiv:2310.01798**Jie Huang, Xinyun Chen, Swaroop Mishra, et al.*2023 · 412 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-large-language-models-cannot-self/)
14. [**UL2: Unifying Language Learning Paradigms arXiv:2205.05131**Yi Tay, Mostafa Dehghani, Vinh Q. Tran, et al.*2022 · 347 citations*](https://md.research.elamur.ai/free/en/papers/tay-2022-ul2-unifying-language-learning-paradigms/)
15. [**Larger language models do in-context learning differently arXiv:2303.03846**Jerry Wei, Jason Wei, Yi Tay, et al.*2023 · 285 citations*](https://md.research.elamur.ai/free/en/papers/wei-2023-larger-language-models-context-learning/)
16. [**What learning algorithm is in-context learning? Investigations with linear models arXiv:2211.15661**Ekin Akyürek, Dale Schuurmans, Jacob Andreas, et al.*2022 · 236 citations*](https://md.research.elamur.ai/free/en/papers/akyurek-2022-learning-algorithm-context-learning-investigations/)
17. **[Fast WordPiece Tokenization ↗](https://aclanthology.org/2021.emnlp-main.160/) Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing · no summary yet**Xinying Song et al.*2021 · 225 citations*
18. **[CRISPR-GPT for Agentic Automation of Gene-editing Experiments ↗](https://arxiv.org/abs/2404.18021) arXiv:2404.18021 · no summary yet**Yuanhao Qu et al.*2024 · 163 citations*
19. **[Chain-of-Thought Reasoning Without Prompting ↗](https://arxiv.org/abs/2402.10200) arXiv:2402.10200 · no summary yet**Xuezhi Wang, Denny Zhou*2024 · 149 citations*
20. [**FreshLLMs: Refreshing Large Language Models with Search Engine Augmentation arXiv:2310.03214**Tu Vu, Mohit Iyyer, Xuezhi Wang, et al.*2023 · 134 citations*](https://md.research.elamur.ai/free/en/papers/vu-2023-freshllms-refreshing-large-language-models/)
21. **[Simple synthetic data reduces sycophancy in large language models ↗](https://arxiv.org/abs/2308.03958) arXiv:2308.03958 · no summary yet**Jerry Wei et al.*2023 · 134 citations*
22. **[Take a Step Back: Evoking Reasoning via Abstraction in Large Language Models ↗](https://arxiv.org/abs/2310.06117) arXiv:2310.06117 · no summary yet**Huaixiu Steven Zheng et al.*2023 · 126 citations*
23. **[Large Language Models as Tool Makers ↗](https://arxiv.org/abs/2305.17126) arXiv:2305.17126 · no summary yet**Tianle Cai et al.*2023 · 123 citations*
24. [**Best Practices and Lessons Learned on Synthetic Data arXiv:2404.07503**Ruibo Liu, Jerry Wei, Fangyu Liu, et al.*2024 · 119 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-best-practices-lessons-learned-synthetic/)
25. **[Recitation-Augmented Language Models ↗](https://arxiv.org/abs/2210.01296) arXiv (Cornell University) · no summary yet**Zhiqing Sun et al.*2022 · 119 citations*
26. **[Neural Symbolic Reader: Scalable Integration of Distributed and Symbolic Representations for Reading Comprehension ↗](https://openalex.org/W2995628494) International Conference on Learning Representations · no summary yet**Xinyun Chen et al.*2020 · 116 citations*
27. **[A Pretrainer's Guide to Training Data: Measuring the Effects of Data Age, Domain Coverage, Quality, & Toxicity ↗](https://arxiv.org/abs/2305.13169) arXiv:2305.13169 · no summary yet**Shayne Longpre et al.*2023 · 104 citations*
28. **[Rationale-Augmented Ensembles in Language Models ↗](https://arxiv.org/abs/2207.00747) arXiv:2207.00747 · no summary yet**Xuezhi Wang et al.*2022 · 101 citations*
29. **[Training Socially Aligned Language Models on Simulated Social Interactions ↗](https://arxiv.org/abs/2305.16960) arXiv:2305.16960 · no summary yet**Ruibo Liu et al.*2023 · 94 citations*
30. [**Universal Self-Consistency for Large Language Model Generation arXiv:2311.17311**Xinyun Chen, Renat Aksitov, Uri Alon, et al.*2023 · 92 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-universal-self-consistency-large-language/)
31. **[FreshLLMs: Refreshing Large Language Models with Search Engine Augmentation ↗](https://aclanthology.org/2024.findings-acl.813/) Findings of the Association for Computational Linguistics: ACL 2024 · no summary yet**Tu Vu et al.*2024 · 74 citations*
32. **[Large Language Models as Analogical Reasoners ↗](https://arxiv.org/abs/2310.01714) arXiv:2310.01714 · no summary yet**Michihiro Yasunaga et al.*2023 · 74 citations*
33. **[Symbol tuning improves in-context learning in language models ↗](https://aclanthology.org/2023.emnlp-main.61/) Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing · no summary yet**Jerry Wei et al.*2023 · 68 citations*
34. **[Self-Discover: Large Language Models Self-Compose Reasoning Structures ↗](https://arxiv.org/abs/2402.03620) arXiv:2402.03620 · no summary yet**Pei Zhou et al.*2024 · 61 citations*
35. **[Premise Order Matters in Reasoning with Large Language Models ↗](https://arxiv.org/abs/2402.08939) arXiv:2402.08939 · no summary yet**Xinyun Chen et al.*2024 · 58 citations*
36. **[NATURAL PLAN: Benchmarking LLMs on Natural Language Planning ↗](https://arxiv.org/abs/2406.04520) arXiv:2406.04520 · no summary yet**Huaixiu Steven Zheng et al.*2024 · 51 citations*
37. **[Compositional Generalization via Neural-Symbolic Stack Machines ↗](https://arxiv.org/abs/2008.06662) arXiv:2008.06662 · no summary yet**Xinyun Chen et al.*2020 · 51 citations*
38. **[LEGO: Latent Execution-Guided Reasoning for Multi-Hop Question Answering on Knowledge Graphs ↗](https://openalex.org/W3167967639) International Conference on Machine Learning · no summary yet**Hongyu Ren et al.*2021 · 49 citations*
39. [**Transcending Scaling Laws with 0.1% Extra Compute arXiv:2210.11399**Yi Tay, Jason Wei, Hyung Won Chung, et al.*2022 · 42 citations*](https://md.research.elamur.ai/free/en/papers/tay-2022-transcending-scaling-laws-0-1/)
40. **[SpreadsheetCoder: Formula Prediction from Semi-structured Context ↗](https://arxiv.org/abs/2106.15339) arXiv:2106.15339 · no summary yet**Xinyun Chen et al.*2021 · 31 citations*
41. **[Transformers Can Achieve Length Generalization But Not Robustly ↗](https://arxiv.org/abs/2402.09371) arXiv:2402.09371 · no summary yet**Yongchao Zhou et al.*2024 · 29 citations*
42. **[SMORE: Knowledge Graph Completion and Multi-hop Reasoning in Massive Knowledge Graphs ↗](https://arxiv.org/abs/2110.14890) arXiv:2110.14890 · no summary yet**Hongyu Ren et al.*2021 · 11 citations*
43. **[Go Wide, Then Narrow: Efficient Training of Deep Thin Networks ↗](https://arxiv.org/abs/2007.00811) arXiv (Cornell University) · no summary yet**Denny Zhou et al.*2020 · 8 citations*