I recently attended the Empirical Methods in Natural Language Processing (EMNLP) conference. In this post I write about the most remarkable stuff presented there and in the co-located events, from the point of view of a neural machine translation researcher. These are just my opinions, feel free to disagree.
Feedback is very welcome. Please leave your comments as replies to this tweet.
If, after reading this post, you want to know more about what happened at EMNLP 2018, I recommend searching for hashtag #emnlp2018 on twitter as there was plenty of live tweeting.
I recently attended the Conference of the European Association for Machine Translation, EAMT 2018. Before this conference I had only attended ICLR, which is an AI conference focused on representation learning, irrespective of the specific task or paradigm (RL, GANs, NLP, images, etc). On the other hand EAMT is purely machine translation-focused.
This year EAMT took place over three days. The first day was focused on research (mostly academia), the second day on products and projects (industry) and the third one on translators (translators track).
I recently attended ICLR 2018, as I had a workshop article accepted. Please, consider taking a look: A differentiable BLEU loss. Analysis and first results.
This was the first time I attended a conference, so I tried to learn as much as I could. These are some random notes about how the conference works and what people talked about.
How the conference works ICLR is an artificial intelligence conference that uses a double-blind peer review process via OpenReview.