--- title: "Who cites Instruction Induction: From Few — 85 citing papers" description: "85 papers of the Elamur Research library cite «Instruction Induction: From Few Examples to Natural Language Task Descriptions», found in their…" canonical: "https://research.elamur.ai/free/en/papers/honovich-2022-instruction-induction-few-examples-natural/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/honovich-2022-instruction-induction-few-examples-natural/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Instruction Induction: From Few Examples to…](https://md.research.elamur.ai/free/en/papers/honovich-2022-instruction-induction-few-examples-natural/) / cited by # Who cites «Instruction Induction: From Few Examples to Natural Language Task Descriptions» 85 papers of our library cite it (of the 149,439 whose bibliographies we read) · 21 with a page here, the most cited first · [← back to «Instruction Induction: From Few Examples to Natural Language Task Descriptions»](https://md.research.elamur.ai/free/en/papers/honovich-2022-instruction-induction-few-examples-natural/) 1. [**A Survey on In-context Learning arXiv:2301.00234**Qingxiu Dong, Lei Li, Damai Dai, et al.*2023 · 978 citations*](https://md.research.elamur.ai/free/en/papers/dong-2023-survey-context-learning/) 2. [**Large Language Models Are Human-Level Prompt Engineers arXiv:2211.01910**Yongchao Zhou, Andrei Ioan Muresanu, Ziwen Han, et al.*2022 · 701 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2022-large-language-models-human-level/) 3. **[Large language models are few-shot clinical information extractors](https://md.research.elamur.ai/free/en/papers/agrawal-2022-large-language-models-are-few/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Monica Agrawal, Stefan Hegselmann, Hunter Lang, et al.*2022 · 454 citations* 4. **[Automatic Prompt Optimization with “Gradient Descent” and Beam Search](https://md.research.elamur.ai/free/en/papers/pryzant-2023-automatic-prompt-optimization-gradient-descent/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Reid Pryzant, Dan Iter, Jerry Li, et al.*2023 · 409 citations* 5. **[Large Language Models are Few-Shot Clinical Information Extractors](https://md.research.elamur.ai/free/en/papers/agrawal-2022-large-language-models-few-shot/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Monica Agrawal, Stefan Hegselmann, Hunter Lang, et al.*2022 · 384 citations* 6. [**Jailbreak and Guard Aligned Language Models with Only Few In-Context Demonstrations arXiv:2310.06387**Zeming Wei, Yifei Wang, Ang Li, et al.*2023 · 130 citations*](https://md.research.elamur.ai/free/en/papers/wei-2023-jailbreak-guard-aligned-language-models/) 7. [**Large Language Models Understand and Can be Enhanced by Emotional Stimuli arXiv:2307.11760**Cheng Li, Jindong Wang, Yixuan Zhang, et al.*2023 · 116 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-large-language-models-understand-enhanced/) 8. [**FLASK: Fine-grained Language Model Evaluation based on Alignment Skill Sets arXiv:2307.10928**Seonghyeon Ye, Doyoung Kim, Sungdong Kim, et al.*2023 · 100 citations*](https://md.research.elamur.ai/free/en/papers/ye-2023-flask-fine-grained-language-model/) 9. **[WebGLM: Towards An Efficient Web-Enhanced Question Answering System with Human Preferences](https://md.research.elamur.ai/free/en/papers/liu-2023-webglm-efficient-web-enhanced/) [ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)](https://md.research.elamur.ai/free/en/venues/acm-sigkdd-conference-on-knowledge-discovery-and-data-mining-kdd/)**Xiao Liu, Hanyu Lai, Hao Yu, et al.*2023 · 95 citations* 10. [**Goal Driven Discovery of Distributional Differences via Language Descriptions arXiv:2302.14233**Ruiqi Zhong, Peter Zhang, Steve Li, et al.*2023 · 42 citations*](https://md.research.elamur.ai/free/en/papers/zhong-2023-goal-driven-discovery-distributional-differences/) 11. **[A Systematic Survey of Automatic Prompt Optimization Techniques](https://md.research.elamur.ai/free/en/papers/ramnath-2025-systematic-survey-automatic-prompt-optimization/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kiran Ramnath, Kang Zhou, Sheng Guan, et al.*2025 · 40 citations* 12. **[Evaluating Language Models as Synthetic Data Generators](https://md.research.elamur.ai/free/en/papers/kim-2025-evaluating-language-models-as-synthetic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Seungone Kim, Juyoung Suk, Xiang Yue, et al.*2025 · 32 citations* 13. [**Dynamic Planning with a LLM arXiv:2308.06391**Gautier Dagan, Frank Keller, Alex Lascarides*2023 · 25 citations*](https://md.research.elamur.ai/free/en/papers/dagan-2023-dynamic-planning-llm/) 14. **[Joint Prompt Optimization of Stacked LLMs using Variational Inference](https://md.research.elamur.ai/free/en/papers/sordoni-2023-joint-prompt-optimization-stacked-llms/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Alessandro Sordoni, Xingdi Yuan, Marc-Alexandre Cote, et al.*2023 · 23 citations* 15. **[A Survey of Post-Training Scaling in Large Language Models](https://md.research.elamur.ai/free/en/papers/lai-2025-survey-post-training-scaling-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hanyu Lai, Xiao Liu, Junjie Gao, et al.*2025 · 18 citations* 16. [**An Incomplete Loop: Deductive, Inductive, and Abductive Reasoning in Language Models arXiv:2404.03028**Emmy Liu, Graham Neubig, Jacob Andreas*2024 · 12 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-incomplete-loop-deductive-inductive-abductive/) 17. **[A Survey of Inductive Reasoning for Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2026-survey-inductive-reasoning-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kedi Chen, Dezhao Ruan, Yuhao Dan, et al.*2026 · 10 citations* 18. **[RETUYT-INCO at BEA 2026 Shared Task 2: Meta-prompting in Rubric-based Scoring for German](https://md.research.elamur.ai/free/en/papers/sastre-2026-retuyt-inco-bea-2026-shared/) [Workshop on Innovative Use of NLP for Building Educational Applications (BEA)](https://md.research.elamur.ai/free/en/venues/bea/)**Ignacio Sastre, Ignacio Remersaro, Facundo Díaz, et al.*2026 · 1 citation* 19. **[Shuttle Between Symbolic Instructions and Neural Parameters of Large Language Models](https://md.research.elamur.ai/free/en/papers/sun-2026-shuttle-between-symbolic-instructions-neural/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wangtao Sun, Haotian Xu, Huanxuan Liao, et al.*2026* 20. **[Soft Head Selection for Injecting ICL-Derived Task Embeddings](https://md.research.elamur.ai/free/en/papers/park-2026-soft-head-selection-injecting-icl/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jungwon Park, Jimyeong Kim, Changin Choi, et al.*2026* 21. **[What Question Did You Answer? Refining Contact Center Evaluation Plans via Backward Questions](https://md.research.elamur.ai/free/en/papers/sood-2026-what-question-did-you-answer/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Prajwal Sood, Rushikesh Pawar, Digvijay Anil Ingle, et al.*2026* 64 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/honovich-2022-instruction-induction-few-examples-natural/) — Instruction Induction: From Few Examples to Natural Language Task Descriptions