2nd Workshop for Natural Language Processing Open Source Software (NLP-OSS)

19 Nov 2020 @ EMNLP 2020 (Virtual Workshop)

With great scientific breakthrough comes solid engineering and open communities. The Natural Language Processing (NLP) community has benefited greatly from the open culture in sharing knowledge, data, and software. The primary objective of this workshop is to further the sharing of insights on the engineering and community aspects of creating, developing, and maintaining NLP open source software (OSS), which we seldom talk about in scientific publications. Our secondary goal is to promote synergies between different open source projects and encourage cross-software collaborations and comparisons.

We refer to Natural Language Processing OSS as an umbrella term that not only covers traditional syntactic, semantic, phonetic, and pragmatic applications; we extend the definition to include task-specific applications (e.g., machine translation, information retrieval, question-answering systems), low-level string processing that contains valid linguistic information (e.g. Unicode creation for new languages, language-based character set definitions) and machine learning/artificial intelligence frameworks with functionalities focusing on text applications.

In the earlier days of NLP, linguistic software was often monolithic and the learning curve to install, use, and extend the tools was steep and frustrating. More often than not, NLP OSS developers/users interact in siloed communities within the ecologies of their respective projects. In addition to the engineering aspects of NLP software, the open source movement has brought a community aspect that we often overlook in building impactful NLP technologies.

An example of precious OSS knowledge comes from SpaCy developer Montani (2017), who shared her thoughts and challenges of maintaining commercial NLP-OSS, such as handling open issues on the issue tracker, model release and packaging strategy and monetizing NLP OSS for sustainability.

More recently, the Transformers library created by Hugging Face, has gathered much interest from the community by open sourcing implementations to use pretrained weights of BERT-like models, in a clean and well-organized structure. The interoperability of various pretrained models trained with different tools in one library enables quick benchmarking across the models, as well as developing best practices for reading/saving serialized interoperable models.

We hope that the NLP-OSS workshop becomes the intellectual forum to collate various open source knowledge beyond the scientific contribution, announce new software/features, promote the open source culture and best practices that go beyond the conferences.

Call for Papers

We invite full papers (8 pages) or short papers (4 pages) on topics related to NLP-OSS broadly categorized into (i) software development, (ii) scientific contribution and (iii) NLP-OSS case studies.

Submission information

Authors are invited to submit a

Submissions can be non-archival and be presented in the NLP-OSS workshop, but we would still require at least a 4-page submission so that reviewers have enough information to make the acceptance/rejection decision. This non-archival option is helpful for author(s) who wants to publish or had published the work elsewhere and would like to present/discuss pertinent NLP-OSS related work to the workshop PCs and attendees.

All papers are allowed unlimited but sensible pages for references. Final camera-ready versions will be allowed an additional page of content to address reviewers’ comments.

Due to the nature of open source software, we find it a bit tricky to “anonymize” “open source”. For this reason, we don’t require your publication to be anonymous. However, if you prefer your paper to be anonymized, please mask any identifiable phrase with REDACTED. We have an option setup in softconf so that you can explicitly opt-in / opt-out of anonymity.

Submission should be formatted according to the EMNLP 2020 LaTeX or MS Word templates at https://2020.emnlp.org/files/emnlp2020-templates.zip.

Submissions should be uploaded to Softconf conference management system at https://www.softconf.com/emnlp2020/nlposs/.

Note: Paper can be dual-submitted to both EMNLP 2020 and the NLP-OSS workshop.

Important dates

The 2nd NLP-OSS workshop will be co-located with the EMNLP 2020 conference.

Invited Speakers

Principles of Good Machine Learning Systems Design

Chip Huyen, Snorkel AI / Stanford University

This talk covers what it means to operationalize Machine Learning (ML) models. It starts by analyzing the difference between ML in research vs. in production, ML systems vs. traditional software, as well as myths about ML production. It then goes over the principles of good ML systems design and introduces an iterative framework for ML systems design, from scoping the project, data management, model development, deployment, maintenance, to business analysis. It covers the differences between DataOps, ML Engineering, MLOps, and data science, and where each fits into the framework. The talk ends with a survey of the ML production ecosystem, the economics of open source, and open-core businesses.

Chip Huyen


Chip Huyen is an engineer who develops tools and best practices for machine learning production. She’s currently with Snorkel AI and she’ll be teaching Machine Learning Systems Design at Stanford. Previously, she was with Netflix, NVIDIA, Primer. She’s also the author of four bestselling Vietnamese books.

On Typing: Historical and Potential Interactions in Word-processing

Spencer Kelly, Freelance Developer

People love typing, in a surprising and universal way. In this talk we look at the development of word-processing, and the design-decisions in this historic interface. Can NLP contribute to word-processing, without making it worse? What would a text-centered computer really look like? We look at the history of punctuation, keyboards, and markup languages. We look at Wikipedia, text-editors, and data structures - with the goal of authoring usable data in text.

Spencer Kelly<


Spencer Kelly is the author of compromise, - a small natural language processing library for the browser. He is a web developer, and maintainer of open-source libraries. His background is in the semantic web and Wikipedia. Today his work focuses on creating infographics. His open-source work is funded by freelance web development. He is from Toronto, Canada.

An Introduction to Transfer Learning in NLP and HuggingFace

Thomas Wolf, Huggingface

In this talk I’ll start by introducing the recent breakthroughs in NLP that resulted from the combination of Transfer Learning schemes and Transformer architectures. The second part of the talk will be dedicated to an introduction of the open-source tools released by HuggingFace, in particular our Transformers, Tokenizers and Datasets libraries and our models.

Thomas Wolf<


Thomas Wolf is co-founder and Chief Science Officer of HuggingFace. His team is on a mission to catalyze and democratize NLP research. Prior to HuggingFace, Thomas gained a Ph.D. in physics, and later a law degree. He worked as a physics researcher and a European Patent Attorney.

Workshop Program

The timezone for the program schedule below are in Pacific Time (Los Angeles).

0500 - 0530    Opening Remarks

0530 - 0630    Invited Talk 1: Spencer Kelly (YouTube)

0630 - 0730    Invited Talk 2: Thomas Wolf (YouTube)

0730 - 0900    Talks Session 1 (Watch on your own, authors encouraged to mend their slidelive chat but not complusory)

A Framework to Assist Chat Operators of Mental Healthcare Services
Thiago Madeira, Heder Bernardino, Jairo Francisco De Souza, Henrique Gomide, Nathália Munck Machado, Bruno Marcos Pinheiro da Silva and Alexandre Vieira Pereira Pacelli

ARBML: Democritizing Arabic Natural Language Processing Tools
Zaid Alyafeai and Maged Al-Shaibani

CLEVR Parser: A Graph Parser Library for Geometric Learning on Language Grounded Image Scenes
Raeid Saqur and Ameet Deshpande

End-to-end NLP Pipelines in Rust
Guillaume Becquin

Fair Embedding Engine: A Library for Analyzing and Mitigating Gender Bias in Word Embeddings
Vaibhav Kumar, Tenzin Bhotia and Vaibhav Kumar

Flexible retrieval with NMSLIB and FlexNeuART
Leonid Boytsov and Eric Nyberg

fugashi, a Tool for Tokenizing Japanese in Python
Paul McCann

Going Beyond T-SNE: Exposing whatlies in Text Embeddings
Vincent Warmerdam, Thomas Kober and Rachael Tatman

Howl: A Deployed, Open-Source Wake Word Detection System
Raphael Tang, Jaejun Lee, Afsaneh Razi, Julia Cambre, Ian Bicking, Jofish Kaye and Jimmy Lin

iNLTK: Natural Language Toolkit for Indic Languages
Gaurav Arora

0900 - 1430    Long Break

1430 - 1600    Talks Session 2 (Watch on your own, authors encouraged to mend their slidelive chat but not complusory)

iobes: A Library for Span-Level Processing
Brian Lester

jiant: A Software Toolkit for Research on General-Purpose Text Understanding Models
Yada Pruksachatkun, Phil Yeres, Haokun Liu, Jason Phang, Phu Mon Htut, Alex Wang, Ian Tenney and Samuel R. Bowman

KLPT -- Kurdish Language Processing Toolkit
Sina Ahmadi

Open Korean Corpora: A Practical Report
Won Ik Cho, Sangwhan Moon and Youngsook Song

Open-Source Morphology for Endangered Mordvinic Languages
Jack Rueter, Mika Hämäläinen and Niko Partanen

Pimlico: A toolkit for corpus-processing pipelines and reproducible experiments
Mark Granroth-Wilding

PySBD: Pragmatic Sentence Boundary Disambiguation
Nipun Sadvilkar and Mark Neumann

SacreROUGE: An Open-Source Library for Using and Developing Summarization Evaluation Metrics
Daniel Deutsch and Dan Roth

TextAttack: Lessons learned in designing Python frameworks for NLP
John Morris, Jin Yong Yoo and Yanjun Qi

TOMODAPI: A Topic Modeling API to Train, Use and Compare Topic Models
Pasquale Lisena, Ismail Harrando, Oussama Kandakji and Raphael Troncy

User-centered & Robust NLP OSS: Lessons Learned from Developing & Maintaining RSMTool
Nitin Madnani and Anastassia Loukina

WAFFLE: A Graph for WordNet Applied to FreeForm Linguistic Exploration
Berk Ekmekci and Blake Howald

1600 - 1730    Gather-town (Live) + Poster QnA

1730 - 1800    Short Break

1800 - 1900    Invited Talk: Chip Huyen (YouTube)

1900 - 1930    Closing Remarks


Programme Committee

Previous Workshop

First Workshop for Natural Language Processing Open Source Software (NLP-OSS 2018)