The RepEval 2017 Shared Task: Multi-Genre Natural Language Inference with Sentence Representations

2017-07-25 · WS 2017 9 · Nikita Nangia, Adina Williams, Angeliki Lazaridou, Samuel R. Bowman

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 Inference corpus (MultiNLI) recently introduced by Williams et al. (2017). All of the five participating teams beat the bidirectional LSTM (BiLSTM) and continuous bag of words baselines reported in Williams et al.. The best single model used stacked BiLSTMs with residual connections to extract sentence features and reached 74.5% accuracy on the genre-matched test set. Surprisingly, the results of the competition were fairly consistent across the genre-matched and genre-mismatched test sets, and across subsets of the test data representing a variety of linguistic phenomena, suggesting that all of the submitted systems learned reasonably domain-independent representations for sentence meaning.

📄 PDF Abstract BibTeX arXiv:1707.08172

Code (0)

등록된 구현이 없습니다.

Tasks

Natural Language Inference Representation LearningSentence

Methods 이 논문이 사용한 방법론

Sigmoid Activation 설명 없음

Tanh Activation 설명 없음

LSTM An LSTM is a type of recurrent neural network that addresses the vanishing gradient problem in vanilla…

Recurrent Neural Network-Based Sentence Encoder with Gated Attention for Natural Language Inference

2017-08-04 · WS 2017 9 · Qian Chen, Xiaodan Zhu, Zhen-Hua Ling, Si Wei 외

The RepEval 2017 Shared Task aims to evaluate natural language understanding models for sentence representation, in which a sentence is represented as a fixed-length vector with neural networks and the quality of the rep…

Natural Language Inference Natural Language Understanding Sentence

LCT-MALTA's Submission to RepEval 2017 Shared Task

2017-09-01 · WS 2017 9 · Hoa Trong Vu, Thuong-Hai Pham, Xiaoyu Bai, Marc Tanti 외

System using BiLSTM and max pooling. Embedding is enhanced by POS, character and dependency info.

Natural Language Inference POS Sentence Embeddings Word Embeddings

Shortcut-Stacked Sentence Encoders for Multi-Domain Inference

2017-08-07 · WS 2017 9 · Yixin Nie, Mohit Bansal

We present a simple sequential sentence encoder for multi-domain natural language inference. Our encoder is based on stacked bidirectional LSTM-RNNs with shortcut connections and fine-tuning of word embeddings. The overa…

Natural Language Inference Sentence Word Embeddings

Emotion Detection and Classification in a Multigenre Corpus with Joint Multi-Task Deep Learning

2018-08-01 · COLING 2018 8 · Shabnam Tafreshi, Mona Diab

Detection and classification of emotion categories expressed by a sentence is a challenging task due to subjectivity of emotion. To date, most of the models are trained and evaluated on single genre and when used to pred…

Emotion Detection and Classification General Classification Multi-Task Learning Sentence

Refining Raw Sentence Representations for Textual Entailment Recognition via Attention

2017-07-11 · WS 2017 9 · Jorge A. Balazs, Edison Marrese-Taylor, Pablo Loyola, Yutaka Matsuo

In this paper we present the model used by the team Rivercorners for the 2017 RepEval shared task. First, our model separately encodes a pair of sentences into variable-length representations by using a bidirectional LST…

General Classification Natural Language Inference Sentence