To do this, we define the RA of a word t as the mean difference between the probability of the actual referentr being TRUE p t (r) and the mean probability for all other entities R \r for every occurrence of the word in the training data: One alternative to this metric that we considered was the area under the receiver operating characteristic (ROC) curve (AUC).
we have shown that it is possible to improve reference resolution for situated dialog by incrementally adapting word semantic model parameters to a given dialog in order to accommodate idiosyncratic language use by dyad partners, and the effect of the partners' own alignment makes this method even more beneficial over time.