The Distributional Hypothesis

By Magnus Sahlgren. 2008

522 citations recorded by the source corpus.

Subfields: Computational Linguistics & Semantics, Linguistics

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Linguistics & Semantics

1. Elia Bruni
2. Rasmus Précenth
3. Marco Baroni
4. Vered Shwartz
5. Nam Khanh Tran
6. Ido Dagan
7. Brenden M. Lake
8. Tal Linzen

In Linguistics

1. Rasmus Précenth
2. Marco Baroni
3. Alexis Conneau
4. Elia Bruni
5. Vered Shwartz
6. Nam Khanh Tran
7. Ido Dagan

Citations in the corpus

• Multimodal Distributional Semantics (2013, methodology): “They have moreover been reported to be at the state of the art in various semantic tasks (Rapp, 2003; Sahlgren, 2008), and in Bruni, Uijlings, Baroni, and Sebe (2012) we show that the window-based methods we use here outperform both a document-as-context model and a sophisticated syntax- and lexical”
• Discovering and Categorising Language Biases in Reddit (2020, background): “The encoding of language in word embeddings answers to the distributional hypothesis in linguistics, which holds that the statistical contexts of words capture much of what we mean by meaning (Sahlgren 2008).”
• Word Embeddings and Gender Stereotypes in Swedish and English (2019, background): “The common way of creating a distributed representation is by following the distributional hypothesis [19]; words can be understood from the contexts they occur in and by the words they can be replaced by [19, 36].”
• Hurtful words: quantifying biases in clinical contextual word embeddings (2020, background): “There are a wide variety of popular word embedding algorithms, and although all word embeddings use context in creating word representations, as they are based on the distributional hypothesis [56], they can largely be classified as either contextual or non-contextual.”
• Meta-Prod2Vec: Product Embeddings Using Side-Information for Recommendation (2016, background): “Most of the work in this area is based on the Distributional Hypothesis [27], which states that words that appear in the same contexts have close if not identical meanings.”
• Still a Pain in the Neck: Evaluating Text Representations on Lexical Composition (2019, background): “Their training is based on the distributional hypothesis, according to which semantically-similar words tend to appear in the same contexts (Harris, 1954).”