(Alternately, they could keep the soft clustering, with the representation for a particular word token being the posterior probability distribution over the states.)
the CRF chunker in Huang and Yates (2009), which uses their HMM word clusters as extra features, achieves F1 lower than a baseline CRF chunker (Sha & Pereira, 2003).