Reducing Sensitivity on Speaker Names for Text Generation from Dialogues

Changing speaker names consistently throughout a dialogue should not affect its meaning and corresponding outputs for text generation from dialogues. However, pre-trained language models, serving as the backbone for dialogue-processing tasks, have shown to be sensitive to nuances. This may result in unfairness in real-world applications. No comprehensive analysis of this problem has been done in the past. In this work, we propose to quantitatively measure a model's sensitivity on speaker names, and comprehensively evaluate a number of known methods for reducing speaker name sensitivity, including a novel approach of our own. Extensive experiments on multiple datasets provide a benchmark for this problem and show the favorable performance of our approach in sensitivity reduction and quality of generation.Comment: findings of ACL'2

Inhibition of platelet-tumour cell interaction with ibrutinib reduces proliferation, migration and invasion of lung cancer cells

Purpose: To investigate the pharmacological role of the Bruton tyrosine kinase (BTK) inhibitor, ibrutinib, in tumour cell-platelet crosstalk in lung cancer.Methods: Human lung cancer cells A549 were treated with ibrutinib or DMSO. mRNA expression was assessed using reverse transcription-quantitative polymerase chain reaction (RT-PCR), and while western blotting was used to determine protein expression levels. Small interfering RNA (siRNA) transfection was performed to suppress the expression of galectin-3. Colony formation and Transwell® assays were used to determine cell viability, cell invasiveness and migratory ability.Results: Co-culture of A549 cells and platelets induced activation of BTK/PLCγ2 signalling and subsequent release of PDGF, VEGF and TGFβ1 from de-granulated platelets. However, knocking down of galectin-3 inhibited A549-induced platelet activation. Conversely, platelet activation upregulated the expression of galectin-3 via the release of PDGF. Moreover, ibrutinib significantly (p < 0.05) inhibited cell viability, migration, and invasion.Conclusion: These results suggest that ibrutinib may be a novel therapeutic treatment for lung cancer.Keywords: Bruton tyrosine kinase, Ibrutinib, Lung cancer, Platele

In-sample Curriculum Learning by Sequence Completion for Natural Language Generation

Curriculum learning has shown promising improvements in multiple domains by training machine learning models from easy samples to hard ones. Previous works which either design rules or train models for scoring the difficulty highly rely on task-specific expertise, and cannot generalize. Inspired by the ``easy-to-hard'' intuition, we propose to do in-sample curriculum learning for natural language generation tasks. Our learning strategy starts training the model to generate the last few words, i.e., do sequence completion, and gradually extends to generate the whole output sequence. Comprehensive experiments show that it generalizes well to different tasks and achieves significant improvements over strong baselines

Influence of casting temperature on microstructures and mechanical properties of Cu50Zr45.5Ti2.5Y2 metallic glass prepared using copper mold casting [+ Erratum]

We investigated the influence of casting temperatures on microstructures and mechanical properties of rapidly solidified Cu50Zr45.5Ti2.5Y2 alloy. With casting temperatures increasing, the content of the crystalline phase decreases. At high casting temperature, i.e., 1723 K, glass forming ability (GFA) of the present alloy enhanced. It is implied that adjusting casting temperatures could be used for designing the microstructures of bulk metallic glass matrix composite (BMGC). Nano-indentation tests indicated that CuZr phases is a little softer and can accommodate more plastic deformation than the amorphous matrix. Compression tests confirmed that this kind of the second phase (CuZr) precipitated under lower casting temperatures helps to initiate multiple shear bands, resulting in great improvement of mechanical properties of the samples. Our work indicate that casting temperatures lead a great influence on GFA, microstructures and mechanical properties of rapidly solidified alloy and controlling casting temperatures is crucial to the application of BMGs

Self-supervised remote sensing feature learning: Learning Paradigms, Challenges, and Future Works

Deep learning has achieved great success in learning features from massive remote sensing images (RSIs). To better understand the connection between feature learning paradigms (e.g., unsupervised feature learning (USFL), supervised feature learning (SFL), and self-supervised feature learning (SSFL)), this paper analyzes and compares them from the perspective of feature learning signals, and gives a unified feature learning framework. Under this unified framework, we analyze the advantages of SSFL over the other two learning paradigms in RSIs understanding tasks and give a comprehensive review of the existing SSFL work in RS, including the pre-training dataset, self-supervised feature learning signals, and the evaluation methods. We further analyze the effect of SSFL signals and pre-training data on the learned features to provide insights for improving the RSI feature learning. Finally, we briefly discuss some open problems and possible research directions.Comment: 24 pages, 11 figures, 3 table