Papers by German Kruszewski

2 papers
What you can cram into a single $&!#* vector: Probing sentence embeddings for linguistic properties (P18-1)

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Challenge: a lack of understanding of the properties of sentence embeddings is limiting the use of the techniques.
Approach: They propose 10 probing tasks designed to capture simple linguistic features of sentences . they use three different encoders to train embeddings in eight different ways .
Outcome: The proposed tasks capture key linguistic features of sentences, but they are difficult to infer from them.
The emergence of number and syntax units in LSTM language models (N19-1)

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Challenge: a recent study shows that LSTMs can capture syntax-sensitive generalizations such as long-distance number agreement.
Approach: They investigate the inner mechanics of number tracking in LSTMs at the single neuron level . they find that long-distance number information is largely managed by two "number units" importantly, the behaviour of these units is partially controlled by other units to track syntactic structure .
Outcome: The proposed model is based on a language model with a long-distance number agreement task.

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