With the purpose of learning and utilizing explicit dense topic embeddings, we propose three variations novel vector-quantization-based models (VQ-TMs): (1) Hard VQ-TM, (2) Soft (3) Multi-View VQ-TM. The model family capitalize on vector quantization techniques, embedded input documents, viewing words as mixtures topics. Guided by a comprehensive set evaluation metrics, conduct systematic quant...