Reference-Aware Language Models

We propose a general class of language models that treat reference as an explicit stochastic latent variable. This architecture allows models to create mentions of entities and their attributes by accessing external databases (required by, e.g., dialogue generation and recipe generation) and internal state (required by, e.g. language models which are aware of coreference)... (read more)

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Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT BENCHMARK
Recipe Generation allrecipes.com Latent Variable Model BLEU 15.41 # 1
Perplexity 4.97 # 1

Methods used in the Paper


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