Nata Stulova s0nata

The Impossible Task of Conference SACs/PCs or How I lost 3 Nights of Sleep

I am writing this post in order to share my thoughts on the processes behind acceptance/rejection decisions in top-tier (NLP) conferences. I'll first discuss the process and then share some thoughts on its shortcomings.

Before we start, a bit about me. I am an assistant professor (aka, rather junior: I have been in this position for less than 4 years, following my PhD studies and a short postdoc) working on NLP, with a focus on multilingualism and low-resource settings. While I have submitted, published at, and reviewed for *ACL conferences and workshops for many years, it was at EMNLP'23 that I was a Senior Area Chair (SAC) for the first time.

The Conference Paper Pipeline

Let's first briefly outline the process that a paper undergoes, from submission to decision:

Create a CC Block for ACM Preprints

Here are two methods to create a nice CC copyright block for your ACM preprint.

First, you need to check your acmart.cls version (you can find it from the first 50 lines of this file).

version >= v1.87

Commit jupyter notebooks code to git and keep output locally

Add a filter to git config by running the following command in bash inside the repo:

git config filter.strip-notebook-output.clean 'jupyter nbconvert --ClearOutputPreprocessor.enabled=True --to=notebook --stdin --stdout --log-level=ERROR'

Create a .gitattributes file inside the directory with the notebooks
Add the following to that file:

marp	false

Marp

Markdown presentation ecosystem

Conventional Commit Messages

See how a minor change to your commit message style can make a difference.

git commit -m"<type>(<optional scope>): <description>" \
  -m"<optional body>" \
  -m"<optional footer>"

Semantic Parsing via Paraphrasing

Introduction

Semantic parsing is the problem of mapping natural language utterances into logical forms that can be executed on a Knowledge Base (KB).
The paper presents a new approach to semantic parsing that uses paraphrasing to leverage the large amount of text which is not covered by the KB.
Link to the paper

Approach

Taken from https://web.archive.org/web/20130517134339/http://bulba.sdsu.edu/jeanette/thesis/PennTags.html (since the source document now appears to be offline)

Penn Treebank II Tags

Note: This information comes from "Bracketing Guidelines for Treebank II Style Penn Treebank Project" - part of the documentation that comes with the Penn Treebank.