Practical Foundations

Rogers, A., & Augenstein, I. (2020). What Can We Do to Improve Peer Review in NLP?. in Findings of the Association for Computational Linguistics: EMNLP 2020
Belz, A. (2009). That’s Nice… What Can You Do With It? Computational Linguistics, 35(1), 111–118.
Fokkens, A., van Erp, M., Postma, M., Pedersen, T., Vossen, P., & Freire, N. (2013). Offspring from Reproduction Problems: What Replication Failure Teaches Us. ACL 2013

Gardner, Neumann, and Grus gave a great tutorial on best practices around “Writing Code for NLP Research” at EMNLP 2018
Christopher Potts wrote an excellent and detailed overview about the practical bits and pieces to developing and writing an NLP paper for Stanford’s CS224u course.

Bender Chapter 2
J&M Chapter 6 (Optional: 18)
- Eisenstein Chapter 14 covers some of the same ground but from a different perspective, and I strongly recommended reading it in addition to the J&M chapter (it’s pretty short, too).
Goldberg Chapters 8, 10, and 11

Lilian Weng has two excellent blog posts that provide a survey of word embedding methods:
- Learning Word Embedding, Oct. 15 2017
- Generalized Language Models, Jan. 31 2019 (but continuously updated)
Robyn Speer’s How to make a racist AI without really trying
Arora, S., Li, Y., Liang, Y., Ma, T., & Risteski, A. (2016). A Latent Variable Model Approach to PMI-based Word Embeddings. Transactions of the Association for Computational Linguistics, 4, 385–399.
- If you really want to grok what’s going on with word embeddings, read this one.