Fetching the paper…
Reading the bibliography…
API documentation is often the most trusted resource for programming.
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.
On Faithfulness and Factuality in Abstractive Summarization. In
Joshua Maynez, Shashi Narayan, Bernd Bohnet, and Ryan McDonald. 2020 · 1919
Earlier work this paper cites.
Interpretation of low kappa values
DK Donker, A Hasman, and HP Van Geijn. 1993 · 1993
Earlier work this paper cites.
Lexrank: Graph-based lexical centrality as salience in text summarization
Günes Erkan and Dragomir R Radev. 2004 · 2004
Earlier work this paper cites.
Rouge: A package for automatic evaluation of summaries. In
Chin-Yew Lin. 2004 · 2004
Earlier work this paper cites.
Textrank: Bringing order into text. In
Rada Mihalcea and Paul Tarau. 2004 · 2004
Earlier work this paper cites.
The probabilistic relevance framework: BM25 and beyond
Stephen Robertson, Hugo Zaragoza, et al · 2009
Earlier work this paper cites.
A field study of API learning obstacles
Martin P Robillard and Robert DeLine. 2011 · 2011
Earlier work this paper cites.
Patterns of knowledge in API reference documentation
Walid Maalej and Martin P Robillard. 2013 · 2013
Earlier work this paper cites.
Ranking crowd knowledge to assist software development. In
Lucas BL De Souza, Eduardo C Campos, and Marcelo de A Maia. 2014 · 2014
Earlier work this paper cites.
What do mobile app users complain about?
Hammad Khalid, Emad Shihab, Meiyappan Nagappan, and Ahmed E Hassan. 2014 · 2014
Earlier work this paper cites.
The value of software documentation quality. In
Reinhold Plösch, Andreas Dautovic, and Matthias Saft. 2014 · 2014
Earlier work this paper cites.
Usage and usefulness of technical software documentation: An industrial case study
Golara Garousi, Vahid Garousi-Yusifoğlu, Guenther Ruhe, Junji Zhi, Mahmoud Moussavi, and Brian Smith. 2015 · 2015
Earlier work this paper cites.
How API documentation fails
Gias Uddin and Martin P Robillard. 2015 · 2015
Earlier work this paper cites.
What are mobile developers asking about? a large scale study using stack overflow
Christoffer Rosen and Emad Shihab. 2016 · 2016
Earlier work this paper cites.
Augmenting api documentation with insights from stack overflow. In
Christoph Treude and Martin P Robillard. 2016 · 2016
Cited alongside, same era.
Automatic summarization of API reviews. In
Gias Uddin and Foutse Khomh. 2017 · 2017
Cited alongside, same era.
AnswerBot: Automated generation of answer summary to developers’ technical questions. In
Bowen Xu, Zhenchang Xing, Xin Xia, and David Lo. 2017 · 2017
Cited alongside, same era.
An empirical study on API usages
Hao Zhong and Hong Mei. 2017 · 2017
Cited alongside, same era.
Summarizing Opinions: Aspect Extraction Meets Sentiment Prediction and They Are Both Weakly Supervised. In
Stefanos Angelidis and Maria Lapata. 2018 · 2018
Cited alongside, same era.
Automated documentation of android apps
Emad Aghajani, Gabriele Bavota, Mario Linares-Vásquez, and Michele Lanza. 2019a · 2019
Beyond accuracy: assessing software documentation quality. In
Christoph Treude, Justin Middleton, and Thushari Atapattu. 2020 · 2020
Later among the works it cites.
Coarse-to-fine query focused multi-document summarization. In
Yumo Xu and Mirella Lapata. 2020 · 2020
Later among the works it cites.
Extractive opinion summarization in quantized transformer spaces
Stefanos Angelidis, Reinald Kim Amplayo, Yoshihiko Suhara, Xiaolan Wang, and Mirella Lapata. 2021 · 2021
Later among the works it cites.
A human being wrote this law review article: GPT-3 and the practice of law
Amy B Cyphert. 2021 · 2021
Later among the works it cites.
Automatic text summarization: A comprehensive survey
Wafaa S El-Kassas, Cherif R Salama, Ahmed A Rafea, and Hoda K Mohamed. 2021 · 2021
Later among the works it cites.
Automatic detection of five api documentation smells: Practitioners’ perspectives. In
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Software documentation issues unveiled. In
Emad Aghajani, Csaba Nagy, Olga Lucero Vega-Márquez, Mario Linares-Vásquez, Laura Moreno, Gabriele Bavota, and Michele Lanza. 2019b · 2019
Cited alongside, same era.
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. In
Devlin Jacob, Chang Ming-Wei, Lee Kenton, and Toutanova Kristina. 2019 · 2019
Cited alongside, same era.
Understanding how and why developers seek and analyze API-related opinions
Gias Uddin, Olga Baysal, Latifa Guerrouj, and Foutse Khomh. 2019 · 2019
Cited alongside, same era.
Extracting API tips from developer question and answer websites. In
Shaohua Wang, NhatHai Phan, Yan Wang, and Yong Zhao. 2019 · 2019
Cited alongside, same era.
Enriching API documentation with code samples and usage scenarios from crowd knowledge
Jingxuan Zhang, He Jiang, Zhilei Ren, Tao Zhang, and Zhiqiu Huang. 2019 · 2019
Cited alongside, same era.
Software documentation: the practitioners’ perspective. In
Emad Aghajani, Csaba Nagy, Mario Linares-Vásquez, Laura Moreno, Gabriele Bavota, Michele Lanza, and David C Shepherd. 2020 · 2020
Cited alongside, same era.
Junaed Younus Khan, Md Tawkat Islam Khondaker, Gias Uddin, and Anindya Iqbal. 2021 · 2021
Later among the works it cites.
Automatic api usage scenario documentation from technical q&a sites
Gias Uddin, Foutse Khomh, and Chanchal K Roy. 2021 · 2021
Later among the works it cites.
Answer Summarization for Technical Queries: Benchmark and New Approach. In
Yang Chengran, Bowen Xu, Ferdian Thung, Yucen Shi, Ting Zhang, Zhou Yang, Xin Zhou, Jieke Shi, Junda He, DongGyun Han, et al · 2022
Later among the works it cites.
Aspect-Based API Review Classification: How Far Can Pre-Trained Transformer Model Go?. In
Chengran Yang, Bowen Xu, Junaed Younus Khan, Gias Uddin, Donggyun Han, Zhou Yang, and David Lo. 2022a · 2022
Later among the works it cites.
Prompted Opinion Summarization with GPT-3.5. In
Adithya Bhaskar, Alex Fabbri, and Greg Durrett. 2023 · 2023
Closest in time.
Survey of hallucination in natural language generation
Ziwei Ji, Nayeon Lee, Rita Frieske, Tiezheng Yu, Dan Su, Yan Xu, Etsuko Ishii, Ye Jin Bang, Andrea Madotto, and Pascale Fung. 2023 · 2023
Closest in time.
Benefits, limits, and risks of GPT-4 as an AI chatbot for medicine
Peter Lee, Sebastien Bubeck, and Joseph Petro. 2023 · 2023
Closest in time.
Stack Overflow Developer Survey 2023
Stack Overflow. [n. d.] · 2023
Closest in time.
Extractive summarization via chatgpt for faithful summary generation
Haopeng Zhang, Xiao Liu, and Jiawei Zhang. 2023b · 2023
Closest in time.
Benchmarking large language models for news summarization
Tianyi Zhang, Faisal Ladhak, Esin Durmus, Percy Liang, Kathleen McKeown, and Tatsunori B Hashimoto. 2023a · 2023
Closest in time.