565 citations · 1.2k across the 34 of their papers we have counts for
6 papers · 2 filters
Problems With Evaluation of Word Embeddings Using Word Similarity Tasks
Manaal Faruqui, Yulia Tsvetkov, Pushpendre Rastogi +1
Lacking standardized extrinsic evaluation methods for vector representations of words, the NLP community has relied heavily on word similarity tasks as a proxy for intrinsic evalua…
Correlation-based Intrinsic Evaluation of Word Vector Representations
Yulia Tsvetkov, Manaal Faruqui, Chris Dyer
We introduce QVEC-CCA--an intrinsic evaluation metric for word vector representations based on correlations of learned vectors with features extracted from linguistic resources. We…
Learning the Curriculum with Bayesian Optimization for Task-Specific Word Representation Learning
Yulia Tsvetkov, Manaal Faruqui, Wang Ling +2
We use Bayesian optimization to learn curricula for word representation learning, optimizing performance on downstream tasks that depend on the learned representations as features.…
Polyglot Neural Language Models: A Case Study in Cross-Lingual Phonetic Representation Learning
Yulia Tsvetkov, Sunayana Sitaram, Manaal Faruqui +6
We introduce polyglot language models, recurrent neural network models trained to predict symbol sequences in many different languages using shared representations of symbols and c…
Cross-lingual Models of Word Embeddings: An Empirical Comparison
Shyam Upadhyay, Manaal Faruqui, Chris Dyer +1
Despite interest in using cross-lingual knowledge to learn word embeddings for various tasks, a systematic comparison of the possible approaches is lacking in the literature. We pe…
Morpho-syntactic Lexicon Generation Using Graph-based Semi-supervised Learning
Manaal Faruqui, Ryan McDonald, Radu Soricut
Morpho-syntactic lexicons provide information about the morphological and syntactic roles of words in a language. Such lexicons are not available for all languages and even when av…