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% Prompt Engineering Strategies
% CoT
@misc{wei2022chain,
title={Chain of Thought Prompting Elicits Reasoning in Large Language Models},
author={Jason Wei and Xuezhi Wang and Dale Schuurmans and Maarten Bosma and Brian Ichter and Fei Xia and Ed Chi and Quoc Le and Denny Zhou},
year={2022},
eprint={2201.11903},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
0-shot CoT
@misc{kojima2022large,
title={Large Language Models are Zero-Shot Reasoners},
author={Takeshi Kojima and Shixiang Shane Gu and Machel Reid and Yutaka Matsuo and Yusuke Iwasawa},
year={2022},
eprint={2205.11916},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
% self consistency
@misc{wang2022selfconsistency,
title={Self-Consistency Improves Chain of Thought Reasoning in Language Models},
author={Xuezhi Wang and Jason Wei and Dale Schuurmans and Quoc Le and Ed Chi and Sharan Narang and Aakanksha Chowdhery and Denny Zhou},
year={2022},
eprint={2203.11171},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
% showing similar training examples
@misc{liu2021makes,
title={What Makes Good In-Context Examples for GPT-3?},
author={Jiachang Liu and Dinghan Shen and Yizhe Zhang and Bill Dolan and Lawrence Carin and Weizhu Chen},
year={2021},
eprint={2101.06804},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
% generated knowledge
@misc{liu2021generated,
title={Generated Knowledge Prompting for Commonsense Reasoning},
author={Jiacheng Liu and Alisa Liu and Ximing Lu and Sean Welleck and Peter West and Ronan Le Bras and Yejin Choi and Hannaneh Hajishirzi},
year={2021},
eprint={2110.08387},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
% recitation augmented
@misc{sun2022recitationaugmented,
title={Recitation-Augmented Language Models},
author={Zhiqing Sun and Xuezhi Wang and Yi Tay and Yiming Yang and Denny Zhou},
year={2022},
eprint={2210.01296},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
% structure over content in prompts
@misc{min2022rethinking,
title={Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?},
author={Sewon Min and Xinxi Lyu and Ari Holtzman and Mikel Artetxe and Mike Lewis and Hannaneh Hajishirzi and Luke Zettlemoyer},
year={2022},
eprint={2202.12837},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
% scratchpads
@misc{nye2021work,
title={Show Your Work: Scratchpads for Intermediate Computation with Language Models},
author={Maxwell Nye and Anders Johan Andreassen and Guy Gur-Ari and Henryk Michalewski and Jacob Austin and David Bieber and David Dohan and Aitor Lewkowycz and Maarten Bosma and David Luan and Charles Sutton and Augustus Odena},
year={2021},
eprint={2112.00114},
archivePrefix={arXiv},
primaryClass={cs.LG}
}
% Maieutic
@misc{jung2022maieutic,
title={Maieutic Prompting: Logically Consistent Reasoning with Recursive Explanations},
author={Jaehun Jung and Lianhui Qin and Sean Welleck and Faeze Brahman and Chandra Bhagavatula and Ronan Le Bras and Yejin Choi},
year={2022},
eprint={2205.11822},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
% STaR
@misc{zelikman2022star,
title={STaR: Bootstrapping Reasoning With Reasoning},
author={Eric Zelikman and Yuhuai Wu and Jesse Mu and Noah D. Goodman},
year={2022},
eprint={2203.14465},
archivePrefix={arXiv},
primaryClass={cs.LG}
}
% least to most
@misc{zhou2022leasttomost,
title={Least-to-Most Prompting Enables Complex Reasoning in Large Language Models},
author={Denny Zhou and Nathanael Schärli and Le Hou and Jason Wei and Nathan Scales and Xuezhi Wang and Dale Schuurmans and Claire Cui and Olivier Bousquet and Quoc Le and Ed Chi},
year={2022},
eprint={2205.10625},
archivePrefix={arXiv},
primaryClass={cs.AI}
}
% instruction prompts
@article{mishra2022reframing,
title={Reframing Instructional Prompts to GPTk’s Language},
url={http://dx.doi.org/10.18653/v1/2022.findings-acl.50},
DOI={10.18653/v1/2022.findings-acl.50},
journal={Findings of the Association for Computational Linguistics: ACL 2022},
publisher={Association for Computational Linguistics},
author={Mishra, Swaroop and Khashabi, Daniel and Baral, Chitta and Choi, Yejin and Hajishirzi, Hannaneh},
year={2022}
}
@misc{efrat2020turking,
title={The Turking Test: Can Language Models Understand Instructions?},
author={Avia Efrat and Omer Levy},
year={2020},
eprint={2010.11982},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
% SCAN dataset (compositional generalization)
@misc{lake2018scan,
title = {Generalization without Systematicity: {{On}} the Compositional Skills of Sequence-to-Sequence Recurrent Networks},
author = {Lake, Brenden M. and Baroni, Marco},
year = {2018},
eprint = {1711.00350},
archivePrefix = {arxiv},
primaryclass = {cs.AI},
doi = {10.48550/arXiv.1711.00350},
}
% Reliability
% mathprompter
@misc{imani2023mathprompter,
title={MathPrompter: Mathematical Reasoning using Large Language Models},
author={Shima Imani and Liang Du and Harsh Shrivastava},
year={2023},
eprint={2303.05398},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
% unreliable CoT
@misc{ye2022unreliability,
title={The Unreliability of Explanations in Few-shot Prompting for Textual Reasoning},
author={Xi Ye and Greg Durrett},
year={2022},
eprint={2205.03401},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
% analyzing harm
@misc{si2022prompting,
title={Prompting GPT-3 To Be Reliable},
author={Chenglei Si and Zhe Gan and Zhengyuan Yang and Shuohang Wang and Jianfeng Wang and Jordan Boyd-Graber and Lijuan Wang},
year={2022},
eprint={2210.09150},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
% diverse prompts
@misc{li2022advance,
title={On the Advance of Making Language Models Better Reasoners},
author={Yifei Li and Zeqi Lin and Shizhuo Zhang and Qiang Fu and Bei Chen and Jian-Guang Lou and Weizhu Chen},
year={2022},
eprint={2206.02336},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
% Ask-Me-Anything Prompting
@misc{arora2022ama,
title = {Ask Me Anything: A simple strategy for prompting language models},
author = {Arora, Simran and Narayan, Avanika and Chen, Mayee F. and Orr, Laurel and Guha, Neel and Bhatia, Kush and Chami, Ines and Sala, Frederic and Ré, Christopher},
keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
year = {2022},
eprint={2210.02441},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
% problems with biases
@misc{zhao2021calibrate,
title={Calibrate Before Use: Improving Few-Shot Performance of Language Models},
author={Tony Z. Zhao and Eric Wallace and Shi Feng and Dan Klein and Sameer Singh},
year={2021},
eprint={2102.09690},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
% augment with search results
@misc{livin2022large,
title={Can large language models reason about medical questions?},
author={Valentin Liévin and Christoffer Egeberg Hother and Ole Winther},
year={2022},
eprint={2207.08143},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
% enhanced self consistency
@misc{mitchell2022enhancing,
title={Enhancing Self-Consistency and Performance of Pre-Trained Language Models through Natural Language Inference},
author={Eric Mitchell and Joseph J. Noh and Siyan Li and William S. Armstrong and Ananth Agarwal and Patrick Liu and Chelsea Finn and Christopher D. Manning},
year={2022},
eprint={2211.11875},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
% bias in 0 shot CoT
@misc{shaikh2022second,
title={On Second Thought, Let's Not Think Step by Step! Bias and Toxicity in Zero-Shot Reasoning},
author={Omar Shaikh and Hongxin Zhang and William Held and Michael Bernstein and Diyi Yang},
year={2022},
eprint={2212.08061},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
@misc{chase2022evaluating,
title={Evaluating language models can be tricky},
author={Harrison Chase},
year={2022},
month={Dec},
day={26},
url={https://twitter.com/hwchase17/status/1607428141106008064}
}
% constitutional
@misc{bai2022constitutional,
title={Constitutional AI: Harmlessness from AI Feedback},
author={Yuntao Bai and Saurav Kadavath and Sandipan Kundu and Amanda Askell and Jackson Kernion and Andy Jones and Anna Chen and Anna Goldie and Azalia Mirhoseini and Cameron McKinnon and Carol Chen and Catherine Olsson and Christopher Olah and Danny Hernandez and Dawn Drain and Deep Ganguli and Dustin Li and Eli Tran-Johnson and Ethan Perez and Jamie Kerr and Jared Mueller and Jeffrey Ladish and Joshua Landau and Kamal Ndousse and Kamile Lukosuite and Liane Lovitt and Michael Sellitto and Nelson Elhage and Nicholas Schiefer and Noemi Mercado and Nova DasSarma and Robert Lasenby and Robin Larson and Sam Ringer and Scott Johnston and Shauna Kravec and Sheer El Showk and Stanislav Fort and Tamera Lanham and Timothy Telleen-Lawton and Tom Conerly and Tom Henighan and Tristan Hume and Samuel R. Bowman and Zac Hatfield-Dodds and Ben Mann and Dario Amodei and Nicholas Joseph and Sam McCandlish and Tom Brown and Jared Kaplan},
year={2022},
eprint={2212.08073},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
% Automated Prompt Engineering
% definition of prompting
@article{shin2020autoprompt,
title={AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts},
url={http://dx.doi.org/10.18653/v1/2020.emnlp-main.346},
DOI={10.18653/v1/2020.emnlp-main.346},
journal={Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)},
publisher={Association for Computational Linguistics},
author={Shin, Taylor and Razeghi, Yasaman and Logan IV, Robert L. and Wallace, Eric and Singh, Sameer},
year={2020} }
% automatic prompt engineer
@misc{zhou2022large,
title={Large Language Models Are Human-Level Prompt Engineers},
author={Yongchao Zhou and Andrei Ioan Muresanu and Ziwen Han and Keiran Paster and Silviu Pitis and Harris Chan and Jimmy Ba},
year={2022},
eprint={2211.01910},
archivePrefix={arXiv},
primaryClass={cs.LG}
}
% Language Model Guides
@book{jurafsky2009,
author={Daniel Jurafsky and James H Martin},
editor={},
publisher={Prentice Hall},
title={Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics and Speech Recognition},
year={2009}
}
% Language Models
% ChatGPT
@misc{chatgpt2022,
author={OpenAI},
title={ChatGPT: Optimizing Language Models for Dialogue},
howpublished = {\url{https://openai.com/blog/chatgpt/}},
year={2022}
}
% gpt3
@misc{brown2020language,
title={Language Models are Few-Shot Learners},
author={Tom B. Brown and Benjamin Mann and Nick Ryder and Melanie Subbiah and Jared Kaplan and Prafulla Dhariwal and Arvind Neelakantan and Pranav Shyam and Girish Sastry and Amanda Askell and Sandhini Agarwal and Ariel Herbert-Voss and Gretchen Krueger and Tom Henighan and Rewon Child and Aditya Ramesh and Daniel M. Ziegler and Jeffrey Wu and Clemens Winter and Christopher Hesse and Mark Chen and Eric Sigler and Mateusz Litwin and Scott Gray and Benjamin Chess and Jack Clark and Christopher Berner and Sam McCandlish and Alec Radford and Ilya Sutskever and Dario Amodei},
year={2020},
eprint={2005.14165},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
% gpt3 instruct
@misc{ouyang2022training,
title={Training language models to follow instructions with human feedback},
author={Long Ouyang and Jeff Wu and Xu Jiang and Diogo Almeida and Carroll L. Wainwright and Pamela Mishkin and Chong Zhang and Sandhini Agarwal and Katarina Slama and Alex Ray and John Schulman and Jacob Hilton and Fraser Kelton and Luke Miller and Maddie Simens and Amanda Askell and Peter Welinder and Paul Christiano and Jan Leike and Ryan Lowe},
year={2022},
eprint={2203.02155},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
% gpt-4
@misc{openai2023gpt4,
title={GPT-4 Technical Report},
author={OpenAI},
year={2023},
eprint={2303.08774},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
% PaLM
@misc{chowdhery2022palm,
title={PaLM: Scaling Language Modeling with Pathways},
author={Aakanksha Chowdhery and Sharan Narang and Jacob Devlin and Maarten Bosma and Gaurav Mishra and Adam Roberts and Paul Barham and Hyung Won Chung and Charles Sutton and Sebastian Gehrmann and Parker Schuh and Kensen Shi and Sasha Tsvyashchenko and Joshua Maynez and Abhishek Rao and Parker Barnes and Yi Tay and Noam Shazeer and Vinodkumar Prabhakaran and Emily Reif and Nan Du and Ben Hutchinson and Reiner Pope and James Bradbury and Jacob Austin and Michael Isard and Guy Gur-Ari and Pengcheng Yin and Toju Duke and Anselm Levskaya and Sanjay Ghemawat and Sunipa Dev and Henryk Michalewski and Xavier Garcia and Vedant Misra and Kevin Robinson and Liam Fedus and Denny Zhou and Daphne Ippolito and David Luan and Hyeontaek Lim and Barret Zoph and Alexander Spiridonov and Ryan Sepassi and David Dohan and Shivani Agrawal and Mark Omernick and Andrew M. Dai and Thanumalayan Sankaranarayana Pillai and Marie Pellat and Aitor Lewkowycz and Erica Moreira and Rewon Child and Oleksandr Polozov and Katherine Lee and Zongwei Zhou and Xuezhi Wang and Brennan Saeta and Mark Diaz and Orhan Firat and Michele Catasta and Jason Wei and Kathy Meier-Hellstern and Douglas Eck and Jeff Dean and Slav Petrov and Noah Fiedel},
year={2022},
eprint={2204.02311},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
% bloom
@misc{scao2022bloom,
title={BLOOM: A 176B-Parameter Open-Access Multilingual Language Model},
author={Teven Le Scao and Angela Fan and Christopher Akiki and Ellie Pavlick and Suzana Ilić and Daniel Hesslow and Roman Castagné and Alexandra Sasha Luccioni and François Yvon and Matthias Gallé and Jonathan Tow and Alexander M. Rush and Stella Biderman and Albert Webson and Pawan Sasanka Ammanamanchi and Thomas Wang and Benoît Sagot and Niklas Muennighoff and Albert Villanova del Moral and Olatunji Ruwase and Rachel Bawden and Stas Bekman and Angelina McMillan-Major and Iz Beltagy and Huu Nguyen and Lucile Saulnier and Samson Tan and Pedro Ortiz Suarez and Victor Sanh and Hugo Laurençon and Yacine Jernite and Julien Launay and Margaret Mitchell and Colin Raffel and Aaron Gokaslan and Adi Simhi and Aitor Soroa and Alham Fikri Aji and Amit Alfassy and Anna Rogers and Ariel Kreisberg Nitzav and Canwen Xu and Chenghao Mou and Chris Emezue and Christopher Klamm and Colin Leong and Daniel van Strien and David Ifeoluwa Adelani and Dragomir Radev and Eduardo González Ponferrada and Efrat Levkovizh and Ethan Kim and Eyal Bar Natan and Francesco De Toni and Gérard Dupont and Germán Kruszewski and Giada Pistilli and Hady Elsahar and Hamza Benyamina and Hieu Tran and Ian Yu and Idris Abdulmumin and Isaac Johnson and Itziar Gonzalez-Dios and Javier de la Rosa and Jenny Chim and Jesse Dodge and Jian Zhu and Jonathan Chang and Jörg Frohberg and Joseph Tobing and Joydeep Bhattacharjee and Khalid Almubarak and Kimbo Chen and Kyle Lo and Leandro Von Werra and Leon Weber and Long Phan and Loubna Ben allal and Ludovic Tanguy and Manan Dey and Manuel Romero Muñoz and Maraim Masoud and María Grandury and Mario Šaško and Max Huang and Maximin Coavoux and Mayank Singh and Mike Tian-Jian Jiang and Minh Chien Vu and Mohammad A. Jauhar and Mustafa Ghaleb and Nishant Subramani and Nora Kassner and Nurulaqilla Khamis and Olivier Nguyen and Omar Espejel and Ona de Gibert and Paulo Villegas and Peter Henderson and Pierre Colombo and Priscilla Amuok and Quentin Lhoest and Rheza Harliman and Rishi Bommasani and Roberto Luis López and Rui Ribeiro and Salomey Osei and Sampo Pyysalo and Sebastian Nagel and Shamik Bose and Shamsuddeen Hassan Muhammad and Shanya Sharma and Shayne Longpre and Somaieh Nikpoor and Stanislav Silberberg and Suhas Pai and Sydney Zink and Tiago Timponi Torrent and Timo Schick and Tristan Thrush and Valentin Danchev and Vassilina Nikoulina and Veronika Laippala and Violette Lepercq and Vrinda Prabhu and Zaid Alyafeai and Zeerak Talat and Arun Raja and Benjamin Heinzerling and Chenglei Si and Elizabeth Salesky and Sabrina J. Mielke and Wilson Y. Lee and Abheesht Sharma and Andrea Santilli and Antoine Chaffin and Arnaud Stiegler and Debajyoti Datta and Eliza Szczechla and Gunjan Chhablani and Han Wang and Harshit Pandey and Hendrik Strobelt and Jason Alan Fries and Jos Rozen and Leo Gao and Lintang Sutawika and M Saiful Bari and Maged S. Al-shaibani and Matteo Manica and Nihal Nayak and Ryan Teehan and Samuel Albanie and Sheng Shen and Srulik Ben-David and Stephen H. Bach and Taewoon Kim and Tali Bers and Thibault Fevry and Trishala Neeraj and Urmish Thakker and Vikas Raunak and Xiangru Tang and Zheng-Xin Yong and Zhiqing Sun and Shaked Brody and Yallow Uri and Hadar Tojarieh and Adam Roberts and Hyung Won Chung and Jaesung Tae and Jason Phang and Ofir Press and Conglong Li and Deepak Narayanan and Hatim Bourfoune and Jared Casper and Jeff Rasley and Max Ryabinin and Mayank Mishra and Minjia Zhang and Mohammad Shoeybi and Myriam Peyrounette and Nicolas Patry and Nouamane Tazi and Omar Sanseviero and Patrick von Platen and Pierre Cornette and Pierre François Lavallée and Rémi Lacroix and Samyam Rajbhandari and Sanchit Gandhi and Shaden Smith and Stéphane Requena and Suraj Patil and Tim Dettmers and Ahmed Baruwa and Amanpreet Singh and Anastasia Cheveleva and Anne-Laure Ligozat and Arjun Subramonian and Aurélie Névéol and Charles Lovering and Dan Garrette and Deepak Tunuguntla and Ehud Reiter and Ekaterina Taktasheva and Ekaterina Voloshina and Eli Bogdanov and Genta Indra Winata and Hailey Schoelkopf and Jan-Christoph Kalo and Jekaterina Novikova and Jessica Zosa Forde and Jordan Clive and Jungo Kasai and Ken Kawamura and Liam Hazan and Marine Carpuat and Miruna Clinciu and Najoung Kim and Newton Cheng and Oleg Serikov and Omer Antverg and Oskar van der Wal and Rui Zhang and Ruochen Zhang and Sebastian Gehrmann and Shani Pais and Tatiana Shavrina and Thomas Scialom and Tian Yun and Tomasz Limisiewicz and Verena Rieser and Vitaly Protasov and Vladislav Mikhailov and Yada Pruksachatkun and Yonatan Belinkov and Zachary Bamberger and Zdeněk Kasner and Alice Rueda and Amanda Pestana and Amir Feizpour and Ammar Khan and Amy Faranak and Ana Santos and Anthony Hevia and Antigona Unldreaj and Arash Aghagol and Arezoo Abdollahi and Aycha Tammour and Azadeh HajiHosseini and Bahareh Behroozi and Benjamin Ajibade and Bharat Saxena and Carlos Muñoz Ferrandis and Danish Contractor and David Lansky and Davis David and Douwe Kiela and Duong A. Nguyen and Edward Tan and Emi Baylor and Ezinwanne Ozoani and Fatima Mirza and Frankline Ononiwu and Habib Rezanejad and Hessie Jones and Indrani Bhattacharya and Irene Solaiman and Irina Sedenko and Isar Nejadgholi and Jesse Passmore and Josh Seltzer and Julio Bonis Sanz and Karen Fort and Livia Dutra and Mairon Samagaio and Maraim Elbadri and Margot Mieskes and Marissa Gerchick and Martha Akinlolu and Michael McKenna and Mike Qiu and Muhammed Ghauri and Mykola Burynok and Nafis Abrar and Nazneen Rajani and Nour Elkott and Nour Fahmy and Olanrewaju Samuel and Ran An and Rasmus Kromann and Ryan Hao and Samira Alizadeh and Sarmad Shubber and Silas Wang and Sourav Roy and Sylvain Viguier and Thanh Le and Tobi Oyebade and Trieu Le and Yoyo Yang and Zach Nguyen and Abhinav Ramesh Kashyap and Alfredo Palasciano and Alison Callahan and Anima Shukla and Antonio Miranda-Escalada and Ayush Singh and Benjamin Beilharz and Bo Wang and Caio Brito and Chenxi Zhou and Chirag Jain and Chuxin Xu and Clémentine Fourrier and Daniel León Periñán and Daniel Molano and Dian Yu and Enrique Manjavacas and Fabio Barth and Florian Fuhrimann and Gabriel Altay and Giyaseddin Bayrak and Gully Burns and Helena U. Vrabec and Imane Bello and Ishani Dash and Jihyun Kang and John Giorgi and Jonas Golde and Jose David Posada and Karthik Rangasai Sivaraman and Lokesh Bulchandani and Lu Liu and Luisa Shinzato and Madeleine Hahn de Bykhovetz and Maiko Takeuchi and Marc Pàmies and Maria A Castillo and Marianna Nezhurina and Mario Sänger and Matthias Samwald and Michael Cullan and Michael Weinberg and Michiel De Wolf and Mina Mihaljcic and Minna Liu and Moritz Freidank and Myungsun Kang and Natasha Seelam and Nathan Dahlberg and Nicholas Michio Broad and Nikolaus Muellner and Pascale Fung and Patrick Haller and Ramya Chandrasekhar and Renata Eisenberg and Robert Martin and Rodrigo Canalli and Rosaline Su and Ruisi Su and Samuel Cahyawijaya and Samuele Garda and Shlok S Deshmukh and Shubhanshu Mishra and Sid Kiblawi and Simon Ott and Sinee Sang-aroonsiri and Srishti Kumar and Stefan Schweter and Sushil Bharati and Tanmay Laud and Théo Gigant and Tomoya Kainuma and Wojciech Kusa and Yanis Labrak and Yash Shailesh Bajaj and Yash Venkatraman and Yifan Xu and Yingxin Xu and Yu Xu and Zhe Tan and Zhongli Xie and Zifan Ye and Mathilde Bras and Younes Belkada and Thomas Wolf},
year={2022},
eprint={2211.05100},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
% bloom+1
@misc{yong2022bloom1,
title={BLOOM+1: Adding Language Support to BLOOM for Zero-Shot Prompting},
author={Zheng-Xin Yong and Hailey Schoelkopf and Niklas Muennighoff and Alham Fikri Aji and David Ifeoluwa Adelani and Khalid Almubarak and M Saiful Bari and Lintang Sutawika and Jungo Kasai and Ahmed Baruwa and Genta Indra Winata and Stella Biderman and Dragomir Radev and Vassilina Nikoulina},
year={2022},
eprint={2212.09535},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
% Jurassic 1
@article{lieberjurassic,
title={Jurassic-1: Technical Details and Evaluation, White paper, AI21 Labs, 2021},
author={Lieber, O and Sharir, O and Lentz, B and Shoham, Y},
year={2021},
journal={URL: https://uploads-ssl. webflow. com/60fd4503684b466578c0d307/61138924626a6981ee09caf6\_jurassic\_ tech\_paper. pdf}
}
% gpt-j
@misc{wange2021gptj,
author = {Wang, Ben and Komatsuzaki, Aran},
title = {{GPT-J-6B: A 6 Billion Parameter Autoregressive Language Model}},
howpublished = {\url{https://github.com/kingoflolz/mesh-transformer-jax}},
year = 2021,
month = May
}
@article{liu2019roberta,
title={Roberta: A robustly optimized bert pretraining approach},
author={Liu, Yinhan and Ott, Myle and Goyal, Naman and Du, Jingfei and Joshi, Mandar and Chen, Danqi and Levy, Omer and Lewis, Mike and Zettlemoyer, Luke and Stoyanov, Veselin},
journal={arXiv preprint arXiv:1907.11692},
year={2019}
}
% Image models
% stable diffusion
@misc{rombach2021highresolution,
title={High-Resolution Image Synthesis with Latent Diffusion Models},
author={Robin Rombach and Andreas Blattmann and Dominik Lorenz and Patrick Esser and Björn Ommer},
year={2021},
eprint={2112.10752},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
% dalle
@misc{ramesh2022hierarchical,
title={Hierarchical Text-Conditional Image Generation with CLIP Latents},
author={Aditya Ramesh and Prafulla Dhariwal and Alex Nichol and Casey Chu and Mark Chen},
year={2022},
eprint={2204.06125},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
% Prompt Engineering IDEs
@unknown{tang2022textbox,
author = {Tang, Tianyi and Junyi, Li and Chen, Zhipeng and Hu, Yiwen and Yu, Zhuohao and Dai, Wenxun and Dong, Zican and Cheng, Xiaoxue and Wang, Yuhao and Zhao, Wayne and Nie, Jian-yun and Wen, Ji-Rong},
year = {2022},
month = {12},
pages = {},
title = {TextBox 2.0: A Text Generation Library with Pre-trained Language Models}
}
% prompt ide
@misc{strobelt2022promptide,
doi = {10.48550/ARXIV.2208.07852},
url = {https://arxiv.org/abs/2208.07852},
author = {Strobelt, Hendrik and Webson, Albert and Sanh, Victor and Hoover, Benjamin and Beyer, Johanna and Pfister, Hanspeter and Rush, Alexander M.},
keywords = {Computation and Language (cs.CL), Human-Computer Interaction (cs.HC), Machine Learning (cs.LG), FOS: Computer and information sciences, FOS: Computer and information sciences},
title = {Interactive and Visual Prompt Engineering for Ad-hoc Task Adaptation with Large Language Models},
publisher = {arXiv},
year = {2022}
}
% prompt source
@misc{bach2022promptsource,
title={PromptSource: An Integrated Development Environment and Repository for Natural Language Prompts},
author={Stephen H. Bach and Victor Sanh and Zheng-Xin Yong and Albert Webson and Colin Raffel and Nihal V. Nayak and Abheesht Sharma and Taewoon Kim and M Saiful Bari and Thibault Fevry and Zaid Alyafeai and Manan Dey and Andrea Santilli and Zhiqing Sun and Srulik Ben-David and Canwen Xu and Gunjan Chhablani and Han Wang and Jason Alan Fries and Maged S. Al-shaibani and Shanya Sharma and Urmish Thakker and Khalid Almubarak and Xiangru Tang and Xiangru Tang and Mike Tian-Jian Jiang and Alexander M. Rush},
year={2022},
eprint={2202.01279},
archivePrefix={arXiv},
primaryClass={cs.LG}
}
% prompt chainer
@misc{wu2022promptchainer,
title={PromptChainer: Chaining Large Language Model Prompts through Visual Programming},
author={Tongshuang Wu and Ellen Jiang and Aaron Donsbach and Jeff Gray and Alejandra Molina and Michael Terry and Carrie J Cai},
year={2022},
eprint={2203.06566},
archivePrefix={arXiv},
primaryClass={cs.HC}
}
% openprompt
@article{ding2021openprompt,
title={OpenPrompt: An Open-source Framework for Prompt-learning},
author={Ding, Ning and Hu, Shengding and Zhao, Weilin and Chen, Yulin and Liu, Zhiyuan and Zheng, Hai-Tao and Sun, Maosong},
journal={arXiv preprint arXiv:2111.01998},
year={2021}
}
% PromptMaker
@inproceedings{jiang2022promptmaker,
author = {Jiang, Ellen and Olson, Kristen and Toh, Edwin and Molina, Alejandra and Donsbach, Aaron and Terry, Michael and Cai, Carrie J},
title = {PromptMaker: Prompt-Based Prototyping with Large Language Models},
year = {2022},
isbn = {9781450391566},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3491101.3503564},
doi = {10.1145/3491101.3503564},
abstract = {Prototyping is notoriously difficult to do with machine learning (ML), but recent advances in large language models may lower the barriers to people prototyping with ML, through the use of natural language prompts. This case study reports on the real-world experiences of industry professionals (e.g. designers, program managers, front-end developers) prototyping new ML-powered feature ideas via prompt-based prototyping. Through interviews with eleven practitioners during a three-week sprint and a workshop, we find that prompt-based prototyping reduced barriers of access by substantially broadening who can prototype with ML, sped up the prototyping process, and grounded communication between collaborators. Yet, it also introduced new challenges, such as the need to reverse-engineer prompt designs, source example data, and debug and evaluate prompt effectiveness. Taken together, this case study provides important implications that lay the groundwork toward a new future of prototyping with ML.},
booktitle = {Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems},
articleno = {35},
numpages = {8},
location = {New Orleans, LA, USA},
series = {CHI EA '22}
}
% Tooling
@software{Chase_LangChain_2022,
author = {Chase, Harrison},
month = {10},
title = {{LangChain}},
url = {https://github.com/hwchase17/langchain},
version = {0.0.66},
year = {2022}
}
@software{Liu_GPT_Index_2022,
author = {Liu, Jerry},
doi = {10.5281/zenodo.1234},
month = {11},
title = {{GPT Index}},
url = {https://github.com/jerryjliu/gpt_index},
year = {2022}
}
% Soft Prompting
% soft prompting
@misc{lester2021power,
title={The Power of Scale for Parameter-Efficient Prompt Tuning},
author={Brian Lester and Rami Al-Rfou and Noah Constant},
year={2021},
eprint={2104.08691},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
% discretized soft prompting (interpreting)
@misc{khashabi2021prompt,
title={Prompt Waywardness: The Curious Case of Discretized Interpretation of Continuous Prompts},
author={Daniel Khashabi and Shane Lyu and Sewon Min and Lianhui Qin and Kyle Richardson and Sean Welleck and Hannaneh Hajishirzi and Tushar Khot and Ashish Sabharwal and Sameer Singh and Yejin Choi},
year={2021},
eprint={2112.08348},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
% Image Prompt Engineering
% images vocab
@misc{oppenlaender2022taxonomy,
title={A Taxonomy of Prompt Modifiers for Text-To-Image Generation},
author={Jonas Oppenlaender},
year={2022},
eprint={2204.13988},
archivePrefix={arXiv},
primaryClass={cs.MM}
}
@misc{wang2022diffusiondb,
title={DiffusionDB: A Large-scale Prompt Gallery Dataset for Text-to-Image Generative Models},
author={Zijie J. Wang and Evan Montoya and David Munechika and Haoyang Yang and Benjamin Hoover and Duen Horng Chau},
year={2022},
eprint={2210.14896},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
@misc{hao2022optimizing,
title={Optimizing Prompts for Text-to-Image Generation},
author={Yaru Hao and Zewen Chi and Li Dong and Furu Wei},
year={2022},
eprint={2212.09611},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
% vocab
@unknown{oppenlaender2022prompt,
author = {Oppenlaender, Jonas},
year = {2022},
month = {04},
title = {Prompt Engineering for Text-Based Generative Art}
}
%% image PE guides
@misc{parsons2022dalleprompt,
author={Guy Parsons},
url={https://dallery.gallery/the-dalle-2-prompt-book/},
title={The DALLE 2 Prompt Book},
year={2022},
month={July},
}
% fix hands
@misc{blake2022with,
author={Blake},
url={https://www.reddit.com/r/StableDiffusion/comments/z7salo/with_the_right_prompt_stable_diffusion_20_can_do/},
title={With the right prompt, Stable Diffusion 2.0 can do hands.},
year={2022},
}
% Datasets
% GSM8K
@misc{cobbe2021training,
title={Training Verifiers to Solve Math Word Problems},
author={Karl Cobbe and Vineet Kosaraju and Mohammad Bavarian and Mark Chen and Heewoo Jun and Lukasz Kaiser and Matthias Plappert and Jerry Tworek and Jacob Hilton and Reiichiro Nakano and Christopher Hesse and John Schulman},
year={2021},
eprint={2110.14168},
archivePrefix={arXiv},
primaryClass={cs.LG}
}
% hotpotQA
@misc{yang2018hotpotqa,
title={HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering},
author={Zhilin Yang and Peng Qi and Saizheng Zhang and Yoshua Bengio and William W. Cohen and Ruslan Salakhutdinov and Christopher D. Manning},
year={2018},
eprint={1809.09600},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
% multiarith
@inproceedings{roy-roth-2015-solving,
title = "Solving General Arithmetic Word Problems",
author = "Roy, Subhro and
Roth, Dan",
booktitle = "Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing",
month = sep,
year = "2015",
address = "Lisbon, Portugal",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D15-1202",
doi = "10.18653/v1/D15-1202",
pages = "1743--1752",
}
% fever dataset
@misc{thorne2018fever,
title={FEVER: a large-scale dataset for Fact Extraction and VERification},
author={James Thorne and Andreas Vlachos and Christos Christodoulopoulos and Arpit Mittal},
year={2018},
eprint={1803.05355},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
% bbq
@misc{parrish2021bbq,
title={BBQ: A Hand-Built Bias Benchmark for Question Answering},
author={Alicia Parrish and Angelica Chen and Nikita Nangia and Vishakh Padmakumar and Jason Phang and Jana Thompson and Phu Mon Htut and Samuel R. Bowman},
year={2021},
eprint={2110.08193},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
% Applied Prompt Engineering
% cascades
@misc{dohan2022language,
title={Language Model Cascades},
author={David Dohan and Winnie Xu and Aitor Lewkowycz and Jacob Austin and David Bieber and Raphael Gontijo Lopes and Yuhuai Wu and Henryk Michalewski and Rif A. Saurous and Jascha Sohl-dickstein and Kevin Murphy and Charles Sutton},
year={2022},
eprint={2207.10342},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
% MRKL
@misc{karpas2022mrkl,
title={MRKL Systems: A modular, neuro-symbolic architecture that combines large language models, external knowledge sources and discrete reasoning},
author={Ehud Karpas and Omri Abend and Yonatan Belinkov and Barak Lenz and Opher Lieber and Nir Ratner and Yoav Shoham and Hofit Bata and Yoav Levine and Kevin Leyton-Brown and Dor Muhlgay and Noam Rozen and Erez Schwartz and Gal Shachaf and Shai Shalev-Shwartz and Amnon Shashua and Moshe Tenenholtz},
year={2022},
eprint={2205.00445},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
% ReAct
@misc{yao2022react,
title={ReAct: Synergizing Reasoning and Acting in Language Models},
author={Shunyu Yao and Jeffrey Zhao and Dian Yu and Nan Du and Izhak Shafran and Karthik Narasimhan and Yuan Cao},
year={2022},
eprint={2210.03629},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
% PAL
@misc{gao2022pal,
title={PAL: Program-aided Language Models},
author={Luyu Gao and Aman Madaan and Shuyan Zhou and Uri Alon and Pengfei Liu and Yiming Yang and Jamie Callan and Graham Neubig},
year={2022},
eprint={2211.10435},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
% User Interface Design
@inproceedings{liu2022design,
author = {Liu, Vivian and Chilton, Lydia B},
title = {Design Guidelines for Prompt Engineering Text-to-Image Generative Models},
year = {2022},
isbn = {9781450391573},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3491102.3501825},
doi = {10.1145/3491102.3501825},
abstract = {Text-to-image generative models are a new and powerful way to generate visual artwork. However, the open-ended nature of text as interaction is double-edged; while users can input anything and have access to an infinite range of generations, they also must engage in brute-force trial and error with the text prompt when the result quality is poor. We conduct a study exploring what prompt keywords and model hyperparameters can help produce coherent outputs. In particular, we study prompts structured to include subject and style keywords and investigate success and failure modes of these prompts. Our evaluation of 5493 generations over the course of five experiments spans 51 abstract and concrete subjects as well as 51 abstract and figurative styles. From this evaluation, we present design guidelines that can help people produce better outcomes from text-to-image generative models.},
booktitle = {Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems},
articleno = {384},
numpages = {23},
keywords = {computational creativity, multimodal generative models, AI co-creation, prompt engineering., text-to-image, design guidelines},
location = {New Orleans, LA, USA},
series = {CHI '22}
}
% Prompt Injection
@misc{crothers2022machine,
title={Machine Generated Text: A Comprehensive Survey of Threat Models and Detection Methods},
author={Evan Crothers and Nathalie Japkowicz and Herna Viktor},
year={2022},
eprint={2210.07321},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
@misc{nin2023new,
title={New jailbreak based on virtual functions - smuggle illegal tokens to the backend.},
author={u/Nin_kat},
url={https://www.reddit.com/r/ChatGPT/comments/10urbdj/new_jailbreak_based_on_virtual_functions_smuggle},
year={2023},
}
@misc{kang2023exploiting,
title={Exploiting Programmatic Behavior of LLMs: Dual-Use Through Standard Security Attacks},
author={Daniel Kang and Xuechen Li and Ion Stoica and Carlos Guestrin and Matei Zaharia and Tatsunori Hashimoto},
year={2023},
eprint={2302.05733},
archivePrefix={arXiv},
primaryClass={cs.CR}
}
@misc{greshake2023youve,
title={More than you've asked for: A Comprehensive Analysis of Novel Prompt Injection Threats to Application-Integrated Large Language Models},
author={Kai Greshake and Sahar Abdelnabi and Shailesh Mishra and Christoph Endres and Thorsten Holz and Mario Fritz},
year={2023},
eprint={2302.12173},
archivePrefix={arXiv},
primaryClass={cs.CR}
}
@misc{kiho2023chatgpt,
title={ChatGPT "DAN" (and other "Jailbreaks")},
author={LEE KIHO},
url={https://github.com/0xk1h0/ChatGPT_DAN},
year={2023}
}
@misc{branch2022evaluating,
title={Evaluating the Susceptibility of Pre-Trained Language Models via Handcrafted Adversarial Examples},
author={Hezekiah J. Branch and Jonathan Rodriguez Cefalu and Jeremy McHugh and Leyla Hujer and Aditya Bahl and Daniel del Castillo Iglesias and Ron Heichman and Ramesh Darwishi},
year={2022},
eprint={2209.02128},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
% https://simonwillison.net/2022/Sep/12/prompt-injection/
@misc{simon2022inject,
title={Prompt injection attacks against GPT-3},
author={Simon Willison},
year={2022},
month={Sep},
url={https://simonwillison.net/2022/Sep/12/prompt-injection/}
}
@misc{goodside2022inject,
title={Exploiting GPT-3 prompts with malicious inputs that order the model to ignore its previous directions},
author={Riley Goodside},
year={2022},
url={https://twitter.com/goodside/status/1569128808308957185}
}
@misc{goodside2022history,
title={History Correction},
author={Riley Goodside},
year={2023},
url= {https://twitter.com/goodside/status/1610110111791325188?s=20&t=ulviQABPXFIIt4ZNZPAUCQ}
}
% prompt injection examples
@misc{chase2021adversarial,
title={adversarial-prompts},
author={Harrison Chase},
year={2022},
url={https://github.com/hwchase17/adversarial-prompts}
}
@misc{goodside2021gpt,
title={GPT-3 Prompt Injection Defenses},
author={Riley Goodside},
year={2022},
url={https://twitter.com/goodside/status/1578278974526222336?s=20&t=3UMZB7ntYhwAk3QLpKMAbw}
}
% post prompting defense
@misc{christoph2022talking,
author={Christoph Mark},
title={Talking to machines: prompt engineering & injection},
year={2022},
month={Oct},
day={3},
url={https://artifact-research.com/artificial-intelligence/talking-to-machines-prompt-engineering-injection/}
}
% other defenses, eliezer
@misc{armstrong2022using,
author={Stuart Armstrong, Rebecca Gorman},
title={Using GPT-Eliezer against ChatGPT Jailbreaking},
year={2022},
month={Dec},
day={6},
url={https://www.alignmentforum.org/posts/pNcFYZnPdXyL2RfgA/using-gpt-eliezer-against-chatgpt-jailbreaking}
}
% reasonable recs
@misc{selvi2022exploring,
author={Jose Selvi},
title={Exploring Prompt Injection Attacks},
year={2022},
month={Dec},
day={5},
url={https://research.nccgroup.com/2022/12/05/exploring-prompt-injection-attacks/}
}
% Surveys
@article{liu2021pretrain,
title={Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing},
ISSN={1557-7341},
url={http://dx.doi.org/10.1145/3560815},
DOI={10.1145/3560815},
journal={ACM Computing Surveys},
publisher={Association for Computing Machinery (ACM)},
author={Liu, Pengfei and Yuan, Weizhe and Fu, Jinlan and Jiang, Zhengbao and Hayashi, Hiroaki and Neubig, Graham},
year={2022},
month={Sep}
}
@miscl{ning2022papers,
title={PromptPapers},
url={https://github.com/thunlp/PromptPapers},
year={2022},
month={Oct},
authors={Ning Ding and Shengding Hu}
}
% Dataset Generation
@misc{perez2022discovering,
title={Discovering Language Model Behaviors with Model-Written Evaluations},
author={Ethan Perez and Sam Ringer and Kamilė Lukošiūtė and Karina Nguyen and Edwin Chen and Scott Heiner and Craig Pettit and Catherine Olsson and Sandipan Kundu and Saurav Kadavath and Andy Jones and Anna Chen and Ben Mann and Brian Israel and Bryan Seethor and Cameron McKinnon and Christopher Olah and Da Yan and Daniela Amodei and Dario Amodei and Dawn Drain and Dustin Li and Eli Tran-Johnson and Guro Khundadze and Jackson Kernion and James Landis and Jamie Kerr and Jared Mueller and Jeeyoon Hyun and Joshua Landau and Kamal Ndousse and Landon Goldberg and Liane Lovitt and Martin Lucas and Michael Sellitto and Miranda Zhang and Neerav Kingsland and Nelson Elhage and Nicholas Joseph and Noemí Mercado and Nova DasSarma and Oliver Rausch and Robin Larson and Sam McCandlish and Scott Johnston and Shauna Kravec and Sheer El Showk and Tamera Lanham and Timothy Telleen-Lawton and Tom Brown and Tom Henighan and Tristan Hume and Yuntao Bai and Zac Hatfield-Dodds and Jack Clark and Samuel R. Bowman and Amanda Askell and Roger Grosse and Danny Hernandez and Deep Ganguli and Evan Hubinger and Nicholas Schiefer and Jared Kaplan},
year={2022},
eprint={2212.09251},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
@misc{su2022selective,
title={Selective Annotation Makes Language Models Better Few-Shot Learners},
author={Hongjin Su and Jungo Kasai and Chen Henry Wu and Weijia Shi and Tianlu Wang and Jiayi Xin and Rui Zhang and Mari Ostendorf and Luke Zettlemoyer and Noah A. Smith and Tao Yu},
year={2022},
eprint={2209.01975},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
% applications
@misc{izacard2022atlas,
title={Atlas: Few-shot Learning with Retrieval Augmented Language Models},
author={Gautier Izacard and Patrick Lewis and Maria Lomeli and Lucas Hosseini and Fabio Petroni and Timo Schick and Jane Dwivedi-Yu and Armand Joulin and Sebastian Riedel and Edouard Grave},
year={2022},
eprint={2208.03299},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
@misc{wang2022strudel,
title={STRUDEL: Structured Dialogue Summarization for Dialogue Comprehension},
author={Borui Wang and Chengcheng Feng and Arjun Nair and Madelyn Mao and Jai Desai and Asli Celikyilmaz and Haoran Li and Yashar Mehdad and Dragomir Radev},
year={2022},
eprint={2212.12652},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
% Miscl
@misc{beurerkellner2022prompting,
title={Prompting Is Programming: A Query Language For Large Language Models},
author={Luca Beurer-Kellner and Marc Fischer and Martin Vechev},
year={2022},
eprint={2212.06094},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
@misc{ratner2022parallel,
title={Parallel Context Windows Improve In-Context Learning of Large Language Models},
author={Nir Ratner and Yoav Levine and Yonatan Belinkov and Ori Ram and Omri Abend and Ehud Karpas and Amnon Shashua and Kevin Leyton-Brown and Yoav Shoham},
year={2022},
eprint={2212.10947},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
@misc{bursztyn2022learning,
title={Learning to Perform Complex Tasks through Compositional Fine-Tuning of Language Models},
author={Victor S. Bursztyn and David Demeter and Doug Downey and Larry Birnbaum},
year={2022},
eprint={2210.12607},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
@misc{wang2022supernaturalinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks},
author={Yizhong Wang and Swaroop Mishra and Pegah Alipoormolabashi and Yeganeh Kordi and Amirreza Mirzaei and Anjana Arunkumar and Arjun Ashok and Arut Selvan Dhanasekaran and Atharva Naik and David Stap and Eshaan Pathak and Giannis Karamanolakis and Haizhi Gary Lai and Ishan Purohit and Ishani Mondal and Jacob Anderson and Kirby Kuznia and Krima Doshi and Maitreya Patel and Kuntal Kumar Pal and Mehrad Moradshahi and Mihir Parmar and Mirali Purohit and Neeraj Varshney and Phani Rohitha Kaza and Pulkit Verma and Ravsehaj Singh Puri and Rushang Karia and Shailaja Keyur Sampat and Savan Doshi and Siddhartha Mishra and Sujan Reddy and Sumanta Patro and Tanay Dixit and Xudong Shen and Chitta Baral and Yejin Choi and Noah A. Smith and Hannaneh Hajishirzi and Daniel Khashabi},
year={2022},
eprint={2204.07705},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
@article{gao2021making,
title={Making Pre-trained Language Models Better Few-shot Learners},
url={http://dx.doi.org/10.18653/v1/2021.acl-long.295},
DOI={10.18653/v1/2021.acl-long.295},
journal={Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)},
publisher={Association for Computational Linguistics},
author={Gao, Tianyu and Fisch, Adam and Chen, Danqi},
year={2021} }
@misc{dang2022prompt,
title={How to Prompt? Opportunities and Challenges of Zero- and Few-Shot Learning for Human-AI Interaction in Creative Applications of Generative Models},
author={Hai Dang and Lukas Mecke and Florian Lehmann and Sven Goller and Daniel Buschek},
year={2022},
eprint={2209.01390},
archivePrefix={arXiv},
primaryClass={cs.HC}
}
@misc{akyrek2022measuring,
title={On Measuring Social Biases in Prompt-Based Multi-Task Learning},
author={Afra Feyza Akyürek and Sejin Paik and Muhammed Yusuf Kocyigit and Seda Akbiyik and Şerife Leman Runyun and Derry Wijaya},
year={2022},
eprint={2205.11605},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
@misc{jin2022plot,
title={Plot Writing From Pre-Trained Language Models},
author={Yiping Jin and Vishakha Kadam and Dittaya Wanvarie},
year={2022},
eprint={2206.03021},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
% bias in llms
@inproceedings{nadeem-etal-2021-stereoset,
title = "{S}tereo{S}et: Measuring stereotypical bias in pretrained language models",
author = "Nadeem, Moin and
Bethke, Anna and
Reddy, Siva",
booktitle = "Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)",
month = aug,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.acl-long.416",
doi = "10.18653/v1/2021.acl-long.416",
pages = "5356--5371",
abstract = "A stereotype is an over-generalized belief about a particular group of people, e.g., Asians are good at math or African Americans are athletic. Such beliefs (biases) are known to hurt target groups. Since pretrained language models are trained on large real-world data, they are known to capture stereotypical biases. It is important to quantify to what extent these biases are present in them. Although this is a rapidly growing area of research, existing literature lacks in two important aspects: 1) they mainly evaluate bias of pretrained language models on a small set of artificial sentences, even though these models are trained on natural data 2) current evaluations focus on measuring bias without considering the language modeling ability of a model, which could lead to misleading trust on a model even if it is a poor language model. We address both these problems. We present StereoSet, a large-scale natural English dataset to measure stereotypical biases in four domains: gender, profession, race, and religion. We contrast both stereotypical bias and language modeling ability of popular models like BERT, GPT-2, RoBERTa, and XLnet. We show that these models exhibit strong stereotypical biases. Our data and code are available at https://stereoset.mit.edu.",
}
% hallucinations in llms
@article{Ji_2022,
doi = {10.1145/3571730},
url = {https://doi.org/10.1145%2F3571730},
year = 2022,
month = {nov},
publisher = {Association for Computing Machinery ({ACM})},
author = {Ziwei Ji and Nayeon Lee and Rita Frieske and Tiezheng Yu and Dan Su and Yan Xu and Etsuko Ishii and Yejin Bang and Andrea Madotto and Pascale Fung},
title = {Survey of Hallucination in Natural Language Generation},
journal = {{ACM} Computing Surveys}
}
% examples
@article{2022examples,
title={What Makes Good In-Context Examples for GPT-3?},
url={http://dx.doi.org/10.18653/v1/2022.deelio-1.10},
DOI={10.18653/v1/2022.deelio-1.10},
journal={Proceedings of Deep Learning Inside Out (DeeLIO 2022): The 3rd Workshop on Knowledge Extraction and Integration for Deep Learning Architectures},
publisher={Association for Computational Linguistics},
author={Liu, Jiachang and Shen, Dinghan and Zhang, Yizhe and Dolan, Bill and Carin, Lawrence and Chen, Weizhu},
year={2022} }
@inproceedings{yuan2022wordcraft,
title={Wordcraft: Story Writing With Large Language Models},
author={Yuan, Ann and Coenen, Andy and Reif, Emily and Ippolito, Daphne},
booktitle={27th International Conference on Intelligent User Interfaces},
pages={841--852},
year={2022}
}
@article{fadnavis2022pain,
title={PainPoints: A Framework for Language-based Detection of Chronic Pain and Expert-Collaborative Text-Summarization},
author={Fadnavis, Shreyas and Dhurandhar, Amit and Norel, Raquel and Reinen, Jenna M and Agurto, Carla and Secchettin, Erica and Schweiger, Vittorio and Perini, Giovanni and Cecchi, Guillermo},
journal={arXiv preprint arXiv:2209.09814},
year={2022}
}
@misc{wang2022selfinstruct,
title={Self-Instruct: Aligning Language Model with Self Generated Instructions},
author={Yizhong Wang and Yeganeh Kordi and Swaroop Mishra and Alisa Liu and Noah A. Smith and Daniel Khashabi and Hannaneh Hajishirzi},
year={2022},
eprint={2212.10560},
archivePrefix={arXiv},
primaryClass={cs.CL}
}