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*Workshop for NLP Open Source Software (NLP-OSS)* 19 Nov 2020, Co-located with EMNLP 2020 (Virtual & Online) https://nlposs.github.io/2020 [EXTENDED] Deadline for Long and Short Paper submission: 19 August 2020 (23:59, Anywhere on earth) ---------------------------------------------------------------- Q: Why are we sending our CFP 2-3 days before the deadline? A: It's a gentle reminder to everyone who's going to submit but hasn't yet. And an encouragement to format any blogpost on your new shiny NLP-OSS or any open source implementation of NLP methods, there's still some time!!! ---------------------------------------------------------------- You have used NLP open source tools and bore grievances but found the solution after hours of coffee and computer staring. Share that at NLP-OSS and suggest how open source could change for the better (e.g. best practices, documentation, API design, etc.) You wrote an awesome blogpost about an NLP-OSS or explained how to use an NLP-OSS to an intended audience. Distilling knowledge about NLP open source implementation is also a share-worthy publication. You are tired of Zoom sessions at ACL but got inspired to write an open source for a nifty idea you got from ACL 2020. Share what you've built at NLP-OSS and what motivated you other than distracting yourself from attending Zoom QnAs; understanding about motivations of OSS forms a larger understanding of OSS sustainability in general. You encountered some nasty reviewers about your EMNLP submission that comes with an OSS or think that a workshop paper has a better chance to improve the idea before a re-submission to the next *ACL conference. Improve your papers with the reviewer's comment and share with us your new NLP-OSS! You came across an awesome SOTA system on NLP task X that once ruled the F1 score. But now the code is stale and it's difficult to understand the code and reproduce the results. Share your experience at NLP-OSS and propose how to "replicate" these forgotten systems. You see this shiny *BERT from a blogpost, tried it to reproduce similar results on a different task and it just doesn't work on your dataset. You did some magic to the code and now it works. Show us how you did it! Though they're small tweaks, well-motivated and empirically tested experiments are valid submissions to NLP-OSS. You have tried 101 NLP tools and there's none that really does what you want. So you wrote your shiny new package and made it open source. Tell us why your package is better than the existing tools, how did you design the code? Is it going to be a one-time thing? Or would you like to see thousands of people using it? You are tired of your processing routine of using bash to call Python to call Perl and then output to a file that you use shell commands to munge the data. So you wrote a better data flow system to pipeline the task. Tell us why your package is better than the existing tools, how did you design the code? Is it going to be a one-time thing? Or would you like to see thousands of people using it? At last, you've found the avenue to air these issues in an academic platform at the NLP-OSS workshop!!! P/S: LAST CALL FOR PAPERS ==== ---------------------------------------------------------------- *Workshop for NLP Open Source Software (NLP-OSS)* 19 Nov 2020, Co-located with EMNLP 2020 https://nlposs.github.io/2020 [EXTENDED] Deadline for Long and Short Paper submission: 19 August 2020 (23:59, Anywhere on earth) ---------------------------------------------------------------- The Second Workshop for NLP Open Source Software (NLP-OSS) will be co-located with EMNLP 2020 on 19 Nov 2020. Focusing more on the social and engineering aspect of NLP software and less on scientific novelty or state-of-art models, the Workshop for NLP-OSS is an academic forum to advance open source developments for NLP research, teaching and application. NLP-OSS also provides an academic workshop to announce new software/features, promote the collaborative culture and best practices that go beyond the conferences. 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. - **Software Development** - Designing and developing NLP-OSS - Licensing issues in NLP-OSS - Backward compatibility and stale code in NLP-OSS - Growing, maintaining and motivating an NLP-OSS community - Best practices for NLP-OSS documentation and testing - Contribution to NLP-OSS without coding - Incentivizing OSS contributions in NLP - Commercialization and Intellectual Property of NLP-OSS - Defining and managing NLP-OSS project scope - Issues in API design for NLP - NLP-OSS software interoperability - Analysis of the NLP-OSS community - **Scientific Contribution** - Surveying OSS for specific NLP task(s) - Demonstration, introductions and/or tutorial of NLP-OSS - Small but useful NLP-OSS - NLP components in ML OSS - Citations and references for NLP-OSS - OSS and experiment replicability - Gaps between existing NLP-OSS - Task-generic vs task-specific software - **Case studies** - Case studies of how a specific bug is fixed or feature is added - Writing wrappers for other NLP-OSS - Writing open-source APIs for open data - Teaching NLP with OSS - NLP-OSS in the industry Submission should be formatted according to the [EMNLP 2020 templates]( https://2020.emnlp.org/call-for-papers) 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. ORGANIZERS Lucy Park, NAVER Corp. Masato Hagiwara, Octanove Labs LLC Dmitrijs Milajevs, NIST and Queen Mary University of London Nelson Liu, Stanford University Geeticka Chauhan, Massachusetts Institute of Technology Liling Tan, Rakuten Institute of Technology
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