Fetching the paper…
Reading the bibliography…
The emergence of foundation models, such as large language models (LLMs) GPT-4 and text-to-image models DALL-E, has opened up numerous possibilities across various domains.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 1901
Earlier work this paper cites.
Controlling the false discovery rate: a practical and powerful approach to multiple testing
Yoav Benjamini and Yosef Hochberg. 1995 · 1995
Earlier work this paper cites.
Design patterns: elements of reusable object-oriented software
Erich Gamma, Richard Helm, Ralph Johnson, Ralph E Johnson, and John Vlissides. 1995 · 1995
Earlier work this paper cites.
A Cognitive Dimensions questionnaire optimised for users.. In PPIG , Vol. 13. Citeseer
Alan F Blackwell and Thomas RG Green. 2000 · 2000
Earlier work this paper cites.
Experimental and quasi-experimental designs for generalized causal inference . Vol. 1195
Thomas D Cook, Donald Thomas Campbell, and William Shadish. 2002 · 2002
Earlier work this paper cites.
Software requirements
Karl Wiegers and Joy Beatty. 2013 · 2013
Earlier work this paper cites.
Razer—a hri for visual task-level programming and intuitive skill parameterization
Franz Steinmetz, Annika Wollschläger, and Roman Weitschat. 2018 · 2018
Earlier work this paper cites.
Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al · 2019
Earlier work this paper cites.
Vipo: Spatial-visual programming with functions for robot-IoT workflows. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems . 1–13
Gaoping Huang, Pawan S Rao, Meng-Han Wu, Xun Qian, Shimon Y Nof, Karthik Ramani, and Alexander J Quinn. 2020 · 2020
Earlier work this paper cites.
On the opportunities and risks of foundation models
Rishi Bommasani, Drew A Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, et al · 2021
Earlier work this paper cites.
Reframing Instructional Prompts to GPTk’s Language
Swaroop Mishra, Daniel Khashabi, Chitta Baral, Yejin Choi, and Hannaneh Hajishirzi. 2021 · 2021
Earlier work this paper cites.
Zero-shot text-to-image generation. In International Conference on Machine Learning . PMLR, 8821–8831
Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, and Ilya Sutskever. 2021 · 2021
Earlier work this paper cites.
Calibrate Before Use: Improving Few-shot Performance of Language Models. In Proceedings of the 38th International Conference on Machine Learning (Proceedings of Machine Learning Research, Vol. 139) , Marina Meila and Tong Zhang (Eds.). PMLR, 12697–12706
Zihao Zhao, Eric Wallace, Shi Feng, Dan Klein, and Sameer Singh. 2021 · 2021
Earlier work this paper cites.
Ask Me Anything: A simple strategy for prompting language models
Simran Arora, Avanika Narayan, Mayee F Chen, Laurel J Orr, Neel Guha, Kush Bhatia, Ines Chami, Frederic Sala, and Christopher Ré. 2022 · 2022
Earlier work this paper cites.
Faithful reasoning using large language models
Antonia Creswell and Murray Shanahan. 2022 · 2022
Earlier work this paper cites.
Selection-inference: Exploiting large language models for interpretable logical reasoning
Antonia Creswell, Murray Shanahan, and Irina Higgins. 2022 · 2022
Earlier work this paper cites.
Demystifying Prompts in Language Models via Perplexity Estimation
Hila Gonen, Srini Iyer, Terra Blevins, Noah A. Smith, and Luke Zettlemoyer. 2022 · 2022
Earlier work this paper cites.
PromptMaker: Prompt-based Prototyping with Large Language Models. In CHI Conference on Human Factors in Computing Systems Extended Abstracts . 1–8
Ellen Jiang, Kristen Olson, Edwin Toh, Alejandra Molina, Aaron Donsbach, Michael Terry, and Carrie J Cai. 2022 · 2022
Earlier work this paper cites.
LAMBADA: Backward Chaining for Automated Reasoning in Natural Language
Seyed Mehran Kazemi, Najoung Kim, Deepti Bhatia, Xin Xu, and Deepak Ramachandran. 2022 · 2022
Cited alongside, same era.
Large Language Models are Zero-Shot Reasoners. In Advances in Neural Information Processing Systems , S. Koyejo, S. Mohamed, A. Agarwal, D. Belgrave, K. Cho, and A. Oh (Eds.), Vol. 35. Curran Associates, Inc., 22199–22213
Takeshi Kojima, Shixiang (Shane) Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa. 2022 · 2022
Cited alongside, same era.
Standing on the shoulders of giant frozen language models
Yoav Levine, Itay Dalmedigos, Ori Ram, Yoel Zeldes, Daniel Jannai, Dor Muhlgay, Yoni Osin, Opher Lieber, Barak Lenz, Shai Shalev-Shwartz, et al · 2022
Cited alongside, same era.
Language models of code are few-shot commonsense learners
Aman Madaan, Shuyan Zhou, Uri Alon, Yiming Yang, and Graham Neubig. 2022 · 2022
Cited alongside, same era.
Welcome to LangChain
Harrison Chase. 2023 · 2023
Closest in time.
short for if this then that
ifttt. 2023 · 2023
Closest in time.
Workflow Patterns home page
Workflow Patterns Initiative. 2023 · 2023
Closest in time.
AI as an ersatz natural science
Subbarao Kambhampati. 2022 · 2023
Closest in time.
What Do ChatGPT and AI-based Automatic Program Generation Mean for the Future of Software
Bertrand Meyer. 2022 · 2023
Closest in time.
Microsoft AI Builder
microsoft. 2023 · 2023
Closest in time.
Midjourney
Midjourney. 2023 · 2023
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Measuring and Narrowing the Compositionality Gap in Language Models
Ofir Press, Muru Zhang, Sewon Min, Ludwig Schmidt, Noah A Smith, and Mike Lewis. 2022 · 2022
Cited alongside, same era.
High-Resolution Image Synthesis With Latent Diffusion Models. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) . 10684–10695
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer. 2022 · 2022
Cited alongside, same era.
PEER: A Collaborative Language Model
Timo Schick, Jane Dwivedi-Yu, Zhengbao Jiang, Fabio Petroni, Patrick Lewis, Gautier Izacard, Qingfei You, Christoforos Nalmpantis, Edouard Grave, and Sebastian Riedel. 2022 · 2022
Cited alongside, same era.
Progprompt: Generating situated robot task plans using large language models
Ishika Singh, Valts Blukis, Arsalan Mousavian, Ankit Goyal, Danfei Xu, Jonathan Tremblay, Dieter Fox, Jesse Thomason, and Animesh Garg. 2022 · 2022
Cited alongside, same era.
Self-consistency improves chain of thought reasoning in language models
Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc Le, Ed Chi, and Denny Zhou. 2022 · 2022
Cited alongside, same era.
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models. In Advances in Neural Information Processing Systems , S. Koyejo, S. Mohamed, A. Agarwal, D. Belgrave, K. Cho, and A. Oh (Eds.), Vol. 35. Curran Associates, Inc., 24824–24837
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, brian ichter, Fei Xia, Ed Chi, Quoc V Le, and Denny Zhou. 2022 · 2022
Cited alongside, same era.
Ai chains: Transparent and controllable human-ai interaction by chaining large language model prompts. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems . 1–22
Tongshuang Wu, Michael Terry, and Carrie Jun Cai. 2022b · 2022
Cited alongside, same era.
Re3: Generating longer stories with recursive reprompting and revision
Kevin Yang, Nanyun Peng, Yuandong Tian, and Dan Klein. 2022 · 2022
Cited alongside, same era.
OpenAI. 2023b · 2023
Closest in time.
Introducing ChatGPT
Openai. 2023 · 2023
Closest in time.
prompts as programming
OpenAI. 2023 · 2023
Closest in time.
Reflexion: an autonomous agent with dynamic memory and self-reflection
Noah Shinn, Beck Labash, and Ashwin Gopinath. 2023 · 2023
Closest in time.
Collaboration for Hybrid Teams
Inc. Stork Tech. 2023 · 2023
Closest in time.
structuredprompt
structuredprompt. 2023 · 2023
Closest in time.
superbio.ai
superbio. 2023 · 2023
Closest in time.
Cooperative principle
wikipedia. 2022 · 2023
Closest in time.
wix: Create a website without limits
wix. 2023 · 2023
Closest in time.
In-Context Instruction Learning
Seonghyeon Ye, Hyeonbin Hwang, Sohee Yang, Hyeongu Yun, Yireun Kim, and Minjoon Seo. 2023 · 2023
Closest in time.
Large Language Models Are Human-Level Prompt Engineers
Yongchao Zhou, Andrei Ioan Muresanu, Ziwen Han, Keiran Paster, Silviu Pitis, Harris Chan, and Jimmy Ba. 2023 · 2023
Closest in time.