/awesome-neural-models-for-semantic-match

A curated list of papers dedicated to neural text (semantic) matching.

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Awesome Neural Models for Semantic Match


A collection of papers maintained by MatchZoo Team.
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Text matching is a core component in many natural language processing tasks, where many task can be viewed as a matching between two texts input.

equation

Where s and t are source text input and target text input, respectively. The psi and phi are representation function for input s and t, respectively. The f is the interaction function, and g is the aggregation function. More detailed explaination about this formula can be found on A Deep Look into Neural Ranking Models for Information Retrieval. The representative matching tasks are as follows:

Tasks Source Text Target Text
Ad-hoc Information Retrieval query document (title/content)
Community Question Answering question question/answer
Paraphrase Identification string1 string2
Natural Language Inference premise hypothesis
Response Retrieval context/utterances response

Healthcheck

pip3 install -r requirements.txt
python3 healthcheck.py