BLEURT: Learning robust metrics for text generation
Text generation has made significant advances in the last few years. Yet, evaluation metrics
have lagged behind, as the most popular choices (eg, BLEU and ROUGE) may correlate …
have lagged behind, as the most popular choices (eg, BLEU and ROUGE) may correlate …
Learning general purpose distributed sentence representations via large scale multi-task learning
A lot of the recent success in natural language processing (NLP) has been driven by
distributed vector representations of words trained on large amounts of text in an …
distributed vector representations of words trained on large amounts of text in an …
tBERT: Topic models and BERT joining forces for semantic similarity detection
Semantic similarity detection is a fundamental task in natural language understanding.
Adding topic information has been useful for previous feature-engineered semantic similarity …
Adding topic information has been useful for previous feature-engineered semantic similarity …
Paraphrase identification with deep learning: A review of datasets and methods
C Zhou, C Qiu, DE Acuna - arXiv preprint arXiv:2212.06933, 2022 - arxiv.org
The rapid advancement of AI technology has made text generation tools like GPT-3 and
ChatGPT increasingly accessible, scalable, and effective. This can pose serious threat to the …
ChatGPT increasingly accessible, scalable, and effective. This can pose serious threat to the …
Simple and effective text matching with richer alignment features
In this paper, we present a fast and strong neural approach for general purpose text
matching applications. We explore what is sufficient to build a fast and well-performed text …
matching applications. We explore what is sufficient to build a fast and well-performed text …
Lcqmc: A large-scale chinese question matching corpus
The lack of large-scale question matching corpora greatly limits the development of
matching methods in question answering (QA) system, especially for non-English …
matching methods in question answering (QA) system, especially for non-English …
Semantic sentence matching with densely-connected recurrent and co-attentive information
Sentence matching is widely used in various natural language tasks such as natural
language inference, paraphrase identification, and question answering. For these tasks …
language inference, paraphrase identification, and question answering. For these tasks …
Neural network models for paraphrase identification, semantic textual similarity, natural language inference, and question answering
In this paper, we analyze several neural network designs (and their variations) for sentence
pair modeling and compare their performance extensively across eight datasets, including …
pair modeling and compare their performance extensively across eight datasets, including …
The bq corpus: A large-scale domain-specific chinese corpus for sentence semantic equivalence identification
This paper introduces the Bank Question (BQ) corpus, a Chinese corpus for sentence
semantic equivalence identification (SSEI). The BQ corpus contains 120,000 question pairs …
semantic equivalence identification (SSEI). The BQ corpus contains 120,000 question pairs …
Gaussian transformer: a lightweight approach for natural language inference
Abstract Natural Language Inference (NLI) is an active research area, where numerous
approaches based on recurrent neural networks (RNNs), convolutional neural networks …
approaches based on recurrent neural networks (RNNs), convolutional neural networks …