Improving the reliability of deep neural networks in NLP: A review
Deep learning models have achieved great success in solving a variety of natural language
processing (NLP) problems. An ever-growing body of research, however, illustrates the …
processing (NLP) problems. An ever-growing body of research, however, illustrates the …
Stress test evaluation for natural language inference
Natural language inference (NLI) is the task of determining if a natural language hypothesis
can be inferred from a given premise in a justifiable manner. NLI was proposed as a …
can be inferred from a given premise in a justifiable manner. NLI was proposed as a …
The repeval 2017 shared task: Multi-genre natural language inference with sentence representations
This paper presents the results of the RepEval 2017 Shared Task, which evaluated neural
network sentence representation learning models on the Multi-Genre Natural Language …
network sentence representation learning models on the Multi-Genre Natural Language …
EQUATE: A benchmark evaluation framework for quantitative reasoning in natural language inference
Quantitative reasoning is a higher-order reasoning skill that any intelligent natural language
understanding system can reasonably be expected to handle. We present EQUATE …
understanding system can reasonably be expected to handle. We present EQUATE …
Distance-based self-attention network for natural language inference
J Im, S Cho - arxiv preprint arxiv:1712.02047, 2017 - arxiv.org
Attention mechanism has been used as an ancillary means to help RNN or CNN. However,
the Transformer (Vaswani et al., 2017) recently recorded the state-of-the-art performance in …
the Transformer (Vaswani et al., 2017) recently recorded the state-of-the-art performance in …
Sentence embeddings in NLI with iterative refinement encoders
Sentence-level representations are necessary for various natural language processing
tasks. Recurrent neural networks have proven to be very effective in learning distributed …
tasks. Recurrent neural networks have proven to be very effective in learning distributed …
A hybrid siamese neural network for natural language inference in cyber-physical systems
Cyber-Physical Systems (CPS), as a multi-dimensional complex system that connects the
physical world and the cyber world, has a strong demand for processing large amounts of …
physical world and the cyber world, has a strong demand for processing large amounts of …
[PDF][PDF] Natural language inference with hierarchical bilstm max pooling architecture
Recurrent neural networks have proven to be very effective for natural language inference
tasks. We build on top of one such model, namely BiLSTM with max pooling, and show that …
tasks. We build on top of one such model, namely BiLSTM with max pooling, and show that …
A Study of the State of the Art Approaches and Datasets for Multilingual Natural Language Inference
Natural language inference is critical in Natural Language Processing where semantics is
involved. Also known as textual entailment recognition, it defines a directional relationship …
involved. Also known as textual entailment recognition, it defines a directional relationship …
Convolutional interaction network for natural language inference
Attention-based neural models have achieved great success in natural language inference
(NLI). In this paper, we propose the Convolutional Interaction Network (CIN), a general …
(NLI). In this paper, we propose the Convolutional Interaction Network (CIN), a general …