54 citations · 171 across the 5 of their papers we have counts for
4 papers · 1 filter
Language models show human-like content effects on reasoning tasks
Ishita Dasgupta, Andrew K. Lampinen, Stephanie C. Y. Chan +5
Reasoning is a key ability for an intelligent system. Large language models (LMs) achieve above-chance performance on abstract reasoning tasks, but exhibit many imperfections. Howe…
Embedding Word Similarity with Neural Machine Translation
Felix Hill, Kyunghyun Cho, Sebastien Jean +2
Neural language models learn word representations, or embeddings, that capture rich linguistic and conceptual information. Here we investigate the embeddings learned by neural mach…
Not All Neural Embeddings are Born Equal
Felix Hill, KyungHyun Cho, Sebastien Jean +2
Neural language models learn word representations that capture rich linguistic and conceptual information. Here we investigate the embeddings learned by neural machine translation…
SimLex-999: Evaluating Semantic Models with (Genuine) Similarity Estimation
Felix Hill, Roi Reichart, Anna Korhonen
We present SimLex-999, a gold standard resource for evaluating distributional semantic models that improves on existing resources in several important ways. First, in contrast to g…