Fetching the paper…
Reading the bibliography…
Large Language Models (LLMs) have impacted the writing process, enhancing productivity by collaborating with humans in content creation platforms.
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. 2020 · 1901
Earlier work this paper cites.
Text and context: Explorations in the semantics and pragmatics of discourse
Teun Adrianus Van Dijk. 1977 · 1977
Earlier work this paper cites.
A framework for a cognitive theory of writing
Allan Collins and Dedre Gentner. 1980 · 1980
Earlier work this paper cites.
identifying the organization of wi iiing processes
JR Hayes. 1980 · 1980
Earlier work this paper cites.
8c watson, d.(1995). constructing validity: Basic issues in objective scale development
LA Clark · 1995
Earlier work this paper cites.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber. 1997 · 1997
Earlier work this paper cites.
The relationship between essay reading style and scoring proficiency in a psychometric scoring system
Edward W. Wolfe. 1997 · 1997
Earlier work this paper cites.
A brief tutorial on the development of measures for use in survey questionnaires
Timothy R Hinkin. 1998 · 1998
Earlier work this paper cites.
Gptscore: Evaluate as you desire
Sara Cushing Weigle. 2002 · 2002
Earlier work this paper cites.
Evaluation of text generation: A survey
Asli Celikyilmaz, Elizabeth Clark, and Jianfeng Gao. 2020 · 2006
Earlier work this paper cites.
Revisiting readability: A unified framework for predicting text quality
Emily Pitler and Ani Nenkova. 2008 · 2008
Earlier work this paper cites.
Rating scales for diagnostic assessment of writing: What should they look like and where should the criteria come from?
Ute Knoch. 2011 · 2011
Earlier work this paper cites.
Exploring topic coherence over many models and many topics
Keith Stevens, Philip Kegelmeyer, David Andrzejewski, and David Buttler. 2012 · 2012
Earlier work this paper cites.
Machine reading tea leaves: Automatically evaluating topic coherence and topic model quality
Jey Han Lau, David Newman, and Timothy Baldwin. 2014 · 2014
Earlier work this paper cites.
Texygen: A benchmarking platform for text generation models
Yaoming Zhu, Sidi Lu, Lei Zheng, Jiaxian Guo, Weinan Zhang, Jun Wang, and Yong Yu. 2018 · 2018
Earlier work this paper cites.
GEval: Tool for debugging NLP datasets and models
Filip Graliński, Anna Wróblewska, Tomasz Stanisławek, Kamil Grabowski, and Tomasz Górecki. 2019 · 2019
Earlier work this paper cites.
A topic augmented text generation model: Joint learning of semantics and structural features
Hongyin Tang, Miao Li, and Beihong Jin. 2019 · 2019
Cited alongside, same era.
Best practices for the human evaluation of automatically generated text
Chris van der Lee, Albert Gatt, Emiel van Miltenburg, Sander Wubben, and Emiel J. Krahmer. 2019 · 2019
Cited alongside, same era.
Topic modeling in embedding spaces
Adji B. Dieng, Francisco J. R. Ruiz, and David M. Blei. 2020 · 2020
Cited alongside, same era.
Retrieval-augmented generation for knowledge-intensive nlp tasks
Patrick Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, et al. 2020 · 2020
Cited alongside, same era.
Measuring and improving consistency in pretrained language models
Yanai Elazar, Nora Kassner, Shauli Ravfogel, Abhilasha Ravichander, Eduard Hovy, Hinrich Schütze, and Yoav Goldberg. 2021 · 2021
Cited alongside, same era.
Gptscore: Evaluate as you desire
Jinlan Fu, See-Kiong Ng, Zhengbao Jiang, and Pengfei Liu. 2023 · 2023
Later among the works it cites.
Evaluating human-language model interaction
Mina Lee, Megha Srivastava, Amelia Hardy, John Thickstun, Esin Durmus, Ashwin Paranjape, Ines Gerard-Ursin, Xiang Lisa Li, Faisal Ladhak, Frieda Rong, Rose E Wang, Minae Kwon, Joon Sung Park, Hancheng Cao, Tony Lee, Rishi Bommasani, Michael S. Bernstein, and Percy Liang. 2023 · 2023
Later among the works it cites.
Gpteval: Nlg evaluation using gpt-4 with better human alignment
Yang Liu, Dan Iter, Yichong Xu, Shuohang Wang, Ruochen Xu, and Chenguang Zhu. 2023 · 2023
Later among the works it cites.
Co-writing screenplays and theatre scripts with language models: Evaluation by industry professionals
Piotr Mirowski, Kory W. Mathewson, Jaylen Pittman, and Richard Evans. 2023 · 2023
Later among the works it cites.
Pearl: Personalizing large language model writing assistants with generation-calibrated retrievers
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Human evaluation of automatically generated text: Current trends and best practice guidelines
Chris van der Lee, Albert Gatt, Emiel van Miltenburg, and Emiel Krahmer. 2021 · 2021
Cited alongside, same era.
Of human criteria and automatic metrics: A benchmark of the evaluation of story generation
Cyril Chhun, Pierre Colombo, Chloé Clavel, and Fabian M. Suchanek. 2022 · 2022
Cited alongside, same era.
CTRLEval: An unsupervised reference-free metric for evaluating controlled text generation
Pei Ke, Hao Zhou, Yankai Lin, Peng Li, Jie Zhou, Xiaoyan Zhu, and Minlie Huang. 2022 · 2022
Cited alongside, same era.
Coauthor: Designing a human-ai collaborative writing dataset for exploring language model capabilities
Mina Lee, Percy Liang, and Qian Yang. 2022 · 2022
Cited alongside, same era.
A survey of evaluation metrics used for nlg systems
Ananya B. Sai, Akash Kumar Mohankumar, and Mitesh M. Khapra. 2022 · 2022
Cited alongside, same era.
Summarize, outline, and elaborate: Long-text generation via hierarchical supervision from extractive summaries
Xiaofei Sun, Zijun Sun, Yuxian Meng, Jiwei Li, and Chun Fan. 2022 · 2022
Cited alongside, same era.
Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, et al. 2022 · 2022
Cited alongside, same era.
Sheshera Mysore, Zhuoran Lu, Mengting Wan, Longqi Yang, Steve Menezes, Tina Baghaee, Emmanuel Barajas Gonzalez, Jennifer Neville, and Tara Safavi. 2023 · 2023
Later among the works it cites.
PEER: A collaborative language model
Timo Schick, Jane A. Yu, Zhengbao Jiang, Fabio Petroni, Patrick Lewis, Gautier Izacard, Qingfei You, Christoforos Nalmpantis, Edouard Grave, and Sebastian Riedel. 2023 · 2023
Later among the works it cites.
DOC: Improving long story coherence with detailed outline control
Kevin Yang, Dan Klein, Nanyun Peng, and Yuandong Tian. 2023 · 2023
Later among the works it cites.
Judging llm-as-a-judge with mt-bench and chatbot arena
Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric P. Xing, Haotong Zhang, Joseph Gonzalez, and Ion Stoica. 2023 · 2023
Later among the works it cites.
Recurrentgpt: Interactive generation of (arbitrarily) long text
Wangchunshu Zhou, Yuchen Eleanor Jiang, Peng Cui, Tiannan Wang, Zhenxin Xiao, Yifan Hou, Ryan Cotterell, and Mrinmaya Sachan. 2023 · 2023
Later among the works it cites.
Self-RAG: Learning to retrieve, generate, and critique through self-reflection
Akari Asai, Zeqiu Wu, Yizhong Wang, Avirup Sil, and Hannaneh Hajishirzi. 2024 · 2024
Closest in time.
Checkeval: Robust evaluation framework using large language model via checklist
Yukyung Lee, Joonghoon Kim, Jaehee Kim, Hyowon Cho, and Kang Pilsung. 2024 · 2024
Closest in time.
Toolformer: Language models can teach themselves to use tools
Timo Schick, Jane Dwivedi-Yu, Roberto Dessì, Roberta Raileanu, Maria Lomeli, Eric Hambro, Luke Zettlemoyer, Nicola Cancedda, and Thomas Scialom. 2024 · 2024
Closest in time.
Kmmlu: Measuring massive multitask language understanding in korean
Guijin Son, Hanwool Lee, Sungdong Kim, Seungone Kim, Niklas Muennighoff, Taekyoon Choi, Cheonbok Park, Kang Min Yoo, and Stella Biderman. 2024 · 2024
Closest in time.
Weaver: Foundation models for creative writing
Tiannan Wang, Jiamin Chen, Qingrui Jia, Shuai Wang, Ruoyu Fang, Huilin Wang, Zhaowei Gao, Chunzhao Xie, Chuou Xu, Jihong Dai, et al. 2024 · 2024
Closest in time.
Kang Min Yoo, Jaegeun Han, Sookyo In, Heewon Jeon, Jisu Jeong, Jaewook Kang, Hyunwook Kim, Kyung-Min Kim, Munhyong Kim, Sungju Kim, et al. 2024 · 2024
Closest in time.