Generalized LL Parsing - <a href="http:&#x2F;&#x2F;dotat.at&#x2F;tmp&#x2F;gll.pdf" rel="nofollow">http:&#x2F;&#x2F;dotat.at&#x2F;tmp&#x2F;gll.pdf</a><p>Parse ambiguous context-free grammars in worst-case cubic time and unambiguous grammars in linear time, with an intuitive recursive-descent-ish algorithm. GLL is the future of parsing IMO, more powerful than packrat&#x2F;PEG parsers and comparatively easy to write by hand. It also handles ambiguities more elegantly than GLR, IMO.<p>Dependency-Based Word Embeddings - <a href="https:&#x2F;&#x2F;levyomer.files.wordpress.com&#x2F;2014&#x2F;04&#x2F;dependency-based-word-embeddings-acl-2014.pdf" rel="nofollow">https:&#x2F;&#x2F;levyomer.files.wordpress.com&#x2F;2014&#x2F;04&#x2F;dependency-base...</a><p>word2vec algorithm with context based on linguistic dependencies instead of a skip-gram approach. A quick explanation is skip-grams give words related to the embedding (ex: Hogwarts -&gt; Dumbledore) and dependencies give words that can be used like the embedding (ex: Hogwards -&gt; Sunnydale). It&#x27;s not meant to replace skip-grams, but augment them; skip-gram contexts learn the domain and dependency-based contexts learn the semantic type.