On Exposure Bias, Hallucination and Domain Shift in Neural Machine Translation

The standard training algorithm in neural machine translation (NMT) suffers from exposure bias, and alternative algorithms have been proposed to mitigate this. However, the practical impact of exposure bias is under debate. In this paper, we link exposure bias to another well-known problem in NMT, namely the tendency to generate hallucinations under domain shift. In experiments on three datasets with multiple test domains, we show that exposure bias is partially to blame for hallucinations, and that training with Minimum Risk Training, which avoids exposure bias, can mitigate this. Our analysis explains why exposure bias is more problematic under domain shift, and also links exposure bias to the beam search problem, i.e. performance deterioration with increasing beam size. Our results provide a new justification for methods that reduce exposure bias: even if they do not increase performance on in-domain test sets, they can increase model robustness to domain shift.Comment: ACL 202

Exploring the Importance of Source Text in Automatic Post-Editing for Context-Aware Machine Translation

Accurate translation requires document-level information, which is ignored by sentence-level machine translation. Recent work has demonstrated that document-level consistency can be improved with automatic post-editing (APE) using only target-language (TL) information. We study an extended APE model that additionally integrates source context. A human evaluation of fluency and adequacy in English–Russian translation reveals that the model with access to source context significantly outperforms monolingual APE in terms of adequacy, an effect largely ignored by automatic evaluation metrics. Our results show that TL-only modelling increases fluency without improving adequacy, demonstrating the need for conditioning on source text for automatic post-editing. They also highlight blind spots in automatic methods for targeted evaluation and demonstrate the need for human assessment to evaluate document-level translation quality reliably

Drying Shrinkage of Hardened Cement Paste and Its Relationship to the Microstructure

The aim of the present study is to relate microstructure to the drying shrinkage of hardened cement paste. Three microstructural features, calcium silicate hydrate(C-S-H), calcium hydroxide(CH) and pore structure were studied. A new method to determine the C-S-H content of hardened cement paste is presented. Drying shrinkage behavior of cement pastes were investigated by drying specimens through successive steps of RH 100% to 7% RH and re-saturating the specimens. The total shrinkage of cement paste after drying to 7% RH and irreversible shrinkage were decreased with the increasing amount of C-S-H and CH. Prolonged curing resulted in a paste with finer pore structure and more weight loss when dried in lower humidity. For a certain paste, the same amount of weight loss induced less liner shrinkage in the 54-23% RH range than in the 100-54% RH range. The total shrinkage of cement paste after drying to 7% RH and irreversible shrinkage decreases with increasing amount of C-S-H and CH. The formation of C-S-H increase the resistance of cement paste to shrinkage rather than enhance drying shrinkage by providing more gel pores and empty of which would bring large stress on the solid skeleton

BPTF Is Essential for T Cell Homeostasis and Function

Bromodomain PHD Finger Transcription Factor (BPTF), a ubiquitously expressed ATP-dependent chromatin-remodeling factor, is critical for epigenetically regulating DNA accessibility and gene expression. While BPTF is important for the development of thymocytes, its function in mature T cells remains largely unknown. By specifically deleting BPTF from late DN3/DN4 stage of developing T cells, we found that BPTF was critical for the homeostasis of T cells via a cell intrinsic manner. In addition, BPTF was essential for the maintenance and function of Treg cells. Treg cell-specific BPTF deletion led to reduced Foxp3 expression, increased lymphocyte infiltration in the non-lymphoid organs and a systemic autoimmune syndrome. These findings therefore reveal a vital role for BPTF in T and Treg cell function and immune homeostasis

Face-based age estimation using improved Swin Transformer with attention-based convolution

Recently Transformer models is new direction in the computer vision field, which is based on self multihead attention mechanism. Compared with the convolutional neural network, this Transformer uses the self-attention mechanism to capture global contextual information and extract more strong features by learning the association relationship between different features, which has achieved good results in many vision tasks. In face-based age estimation, some facial patches that contain rich age-specific information are critical in the age estimation task. The present study proposed an attention-based convolution (ABC) age estimation framework, called improved Swin Transformer with ABC, in which two separate regions were implemented, namely ABC and Swin Transformer. ABC extracted facial patches containing rich age-specific information using a shallow convolutional network and a multiheaded attention mechanism. Subsequently, the features obtained by ABC were spliced with the flattened image in the Swin Transformer, which were then input to the Swin Transformer to predict the age of the image. The ABC framework spliced the important regions that contained rich age-specific information into the original image, which could fully mobilize the long-dependency of the Swin Transformer, that is, extracting stronger features by learning the dependency relationship between different features. ABC also introduced loss of diversity to guide the training of self-attention mechanism, reducing overlap between patches so that the diverse and important patches were discovered. Through extensive experiments, this study showed that the proposed framework outperformed several state-of-the-art methods on age estimation benchmark datasets

The role of prostate-specific antigen in the osteoblastic bone metastasis of prostate cancer: a literature review

Prostate cancer is the only human malignancy that generates predominantly osteoblastic bone metastases, and osteoblastic bone metastases account for more than 90% of osseous metastases of prostate cancer. Prostate-specific antigen (PSA) plays an important role in the osteoblastic bone metastasis of prostate cancer, which can promote osteomimicry of prostate cancer cells, suppress osteoclast differentiation, and facilitate osteoblast proliferation and activation at metastatic sites. In the meantime, it can activate osteogenic factors, including insulin-like growth factor, transforming growth factor β2 and urokinase-type plasminogen activator, and meanwhile suppress osteolytic factors such as parathyroid hormone-related protein. To recapitulate, PSA plays a significant role in the osteoblastic predominance of prostate cancer bone metastasis and bone remodeling by regulating multiple cells and factors involved in osseous metastasis