Empathy is a vital factor that contributes to mutual understanding, and joint problem-solving.
In recent years, a growing number of studies have recognized the benefits of empathy and …

We provide the first exploration of sentence embeddings from text-to-text transformers (T5).
Sentence embeddings are broadly useful for language processing tasks. While T5 achieves …

While BERT is an effective method for learning monolingual sentence embeddings for
semantic similarity and embedding based transfer learning (Reimers and Gurevych, 2019) …

Pre-training models such as BERT have achieved great success in many natural language
processing tasks. However, how to obtain better sentence representation through these pre …

BERT (Devlin et al., 2018) and RoBERTa (Liu et al., 2019) has set a new state-of-the-art
performance on sentence-pair regression tasks like semantic textual similarity (STS) …

We present a novel language representation model enhanced by knowledge called ERNIE
(Enhanced Representation through kNowledge IntEgration). Inspired by the masking …

We present easy-to-use TensorFlow Hub sentence embedding models having good task
transfer performance. Model variants allow for trade-offs between accuracy and compute …

Language models (LMs) have recently been shown to generate more factual responses by
employing modularity (Zhou et al., 2021) in combination with retrieval (Adolphs et al., 2021) …

We introduce two pre-trained retrieval focused multilingual sentence encoding models,
respectively based on the Transformer and CNN model architectures. The models embed …

Abstract The Right to be Forgotten (RTBF) was first established as the result of the ruling of
Google Spain SL, Google Inc. v AEPD, Mario Costeja González, and was later included as …