Nethmi Tharushika·Jul 15The 2010s: How NLP Learned to Think in VectorsIf you had to pick one idea that defined natural language processing in the 2010s, it wouldn’t be a single model , it would be a shift in…
Feliks VP Samosir·May 24Dari Hitungan ke Prediksi: Bagaimana Mesin Belajar Memahami Hubungan AntarkataIni adalah bagian kedua dari seri catatan belajar saya atas video perkuliahan dari CS224N (Stanford University) dan CMU 11–737 (Carnegie…
Lekshana Priya Ravi·Apr 20How Machines Learned Meaning: Distributed Language RepresentationHow vectors, context, and neural models reshaped language processing — from Word2Vec to BERT and beyond.
Mohammedsafa·Apr 12Do Static Word Embeddings Really Fail on Polysemy?We usually say static embeddings fail on polysemy. And in one important sense, they do. But that may not be the whole story.
