Sep 20, 2016 · In this paper, we present a new state-of-the-art result, achieving the accuracy of 88.6% on the Stanford Natural Language Inference Dataset.
In this paper, we present a new state-of-the-art result, achieving the accuracy of 88.6% on the Stanford Natural Language Inference Dataset.
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Source code for "Enhanced LSTM for Natural Language Inference" runnable on GPU and CPU based on Theano. If you use this code as part of any published research, ...
Mar 15, 2021 · Summary This model implements the ESIM model, which is a sequential neural inference model based on chain LSTMs.
Dec 9, 2019 · Entailment task is to predict whether the two sentences are entailment, contradiction, and neutral. Their model is called ESIM (Enhanced ...
Oct 16, 2017 · This powerful approach is reminiscent of how information is merged for Siamese networks, opening up some new paths for research.
Enhanced Sequential Inference Model or ESIM is a sequential NLI model proposed in Enhanced LSTM for Natural Language Inference paper.
This is an implementation of Enhanced BiLSTM Inference Model for Natural Language Inference in Keras. The model is based on a paper by Chen et al.
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We improved the performance of basic LSTM recurrent neural networks on Stanford natural language inference (SNLI) corpus by adding Sentence Fusion modules which ...
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This paper presents a new state-of-the-art result, achieving the accuracy of 88.3% on the standard benchmark, the Stanford Natural Language Inference ...