BigVideo: A Large-scale Video Subtitle Translation Dataset for Multimodal Machine Translation

We present a large-scale video subtitle translation dataset, BigVideo, to facilitate the study of multi-modality machine translation. Compared with the widely used How2 and VaTeX datasets, BigVideo is more than 10 times larger, consisting of 4.5 million sentence pairs and 9,981 hours of videos. We also introduce two deliberately designed test sets to verify the necessity of visual information: Ambiguous with the presence of ambiguous words, and Unambiguous in which the text context is self-contained for translation. To better model the common semantics shared across texts and videos, we introduce a contrastive learning method in the cross-modal encoder. Extensive experiments on the BigVideo show that: a) Visual information consistently improves the NMT model in terms of BLEU, BLEURT, and COMET on both Ambiguous and Unambiguous test sets. b) Visual information helps disambiguation, compared to the strong text baseline on terminology-targeted scores and human evaluation. Dataset and our implementations are available at https://github.com/DeepLearnXMU/BigVideo-VMT.Comment: Accepted to ACL 2023 Finding

Prevotella genus and its related NOD-like receptor signaling pathway in young males with stage III periodontitis

BackgroundAs periodontitis progresses, the oral microbiota community changes dynamically. In this study, we evaluated the dominant bacteria and their roles in the potential pathway in young males with stage III periodontitis.Methods16S rRNA sequencing was performed to evaluate variations in the composition of oral bacteria between males with stage I and III periodontitis and identify the dominant bacteria of each group. Function prediction was obtained based on 16S rRNA sequencing data. The inhibitor of the predominant pathway for stage III periodontitis was used to investigate the role of the dominant bacteria in periodontitis in vivo and in vitro.ResultsChao1 index, Observed Species and Phylogenetic Diversity (PD) whole tree values were significantly higher in the stage III periodontitis group. β-diversity suggested that samples could be divided according to the stages of periodontitis. The dominant bacteria in stage III periodontitis were Prevotella, Prevotella_7, and Dialister, whereas that in stage I periodontitis was Cardiobacterium. KEGG analysis predicted that variations in the oral microbiome may be related to the NOD-like receptor signaling pathway. The inhibitor of this pathway, NOD-IN-1, decreased P. intermedia -induced Tnf-α mRNA expression and increased P. intermedia -induced Il-6 mRNA expression, consistent with the ELISA results. Immunohistochemistry confirmed the down-regulation of TNF-α and IL-6 expressions by NOD-IN-1 in P. intermedia–induced periodontitis.ConclusionThe composition of the oral bacteria in young males varied according to the stage of periodontitis. The species richness of oral microtia was greater in young males with stage III periodontitis than those with stage I periodontitis. Prevotella was the dominant bacteria in young males with stage III periodontitis, and inhibition of the NOD-like receptor signaling pathway can decrease the periodontal inflammation induced by P. intermedia

Individual Differences in the Accuracy of Judgments of Learning Are Related to the Gray Matter Volume and Functional Connectivity of the Left Mid-Insula

The judgment of learning (JOL) is an important form of prospective metamemory judgment, and the biological basis of the JOL process is an important topic in metamemory research. Although previous task-related functional magnetic resonance imaging (MRI) studies have examined the brain regions underlying the JOL process, the neural correlates of individual differences in JOL accuracy require further investigation. This study used structural and resting-state functional MRI to investigate whether individual differences in JOL accuracy are related to the gray matter (GM) volume and functional connectivity of the bilateral insula and medial Brodmann area (BA) 11, which are assumed to be related to JOL accuracy. We found that individual differences in JOL accuracy were related to the GM volume of the left mid-insula and to the functional connectivity between the left mid-insula and various other regions, including the left superior parietal lobule/precuneus, bilateral inferior parietal lobule/intraparietal sulcus, right frontal pole and left parahippocampal gyrus/fusiform gyrus/cerebellum. Further analyses indicated that the functional connectivity related to individual differences in JOL accuracy could be divided into two factors and might support information integration and selective attention processes underlying accurate JOLs. In addition, individual differences in JOL accuracy were not related to the GM volume or functional connectivity of the medial BA 11. Our findings provide novel evidence for the role of the left mid-insula and its functional connectivity in the JOL process

How Much Do Metamemory Beliefs Contribute to the Font-Size Effect in Judgments of Learning?

<div><p>Evidence shows that the font size of study items significantly influences judgments of learning (JOLs) and that people’s JOLs are generally higher for larger words than for smaller words. Previous studies have suggested that font size influences JOLs in a belief-based way. However, few studies have directly examined how much people’s beliefs contribute to the font-size effect in JOLs. This study investigated the degree to which font size influenced JOLs in a belief-based way. In Experiment 1, one group of participants (learners) studied words with different font sizes and made JOLs, whereas another group of participants (observers) viewed the learners' study phase and made JOLs for the learners. In Experiment 2, participants made both JOLs and belief-based recall predictions for large and small words. Our results suggest that metamemory beliefs play an important role in the font-size effect in JOLs.</p></div

Recall performance and relative accuracy from Experiments 1–2.

<p>Recall performance and relative accuracy from Experiments 1–2.</p

Confidence ratings increase response thresholds in decision making

Many mental processes are reactive - they are altered as a result of introspection and monitoring. It has been documented that soliciting trial-by-trial confidence ratings (CRs) reactively improves decision accuracy and lengthens response times (RTs), but the cognitive mechanisms underlying CR reactivity in decision-making remain unknown. The current study conducted two experiments and employed the drift-diffusion model (DDM) to explore why reporting confidence reactively alters the decision-making process. The results showed that CRs led to enhanced decision accuracy, longer RTs, and higher response thresholds. The findings are consistent with an increased conservatism hypothesis which asserts that soliciting CRs provokes feelings of uncertainty and makes individuals more cautious in their decision making

How font size affects judgments of learning: Simultaneous mediating effect of item-specific beliefs about fluency and moderating effect of beliefs about font size and memory

<div><p>Numerous studies have provided experience-based or theory-based frameworks for the basis of judgment of learning (JOL). However, few studies have directly measured processing experience and beliefs related to the same cue in one experiment and examined their joint contribution to JOLs. The present study focused on font-size effects and aimed to examine the simultaneous contribution of processing fluency and beliefs to the effect of font size on JOLs. We directly measured processing fluency via self-paced study time. We also directly measured participants’ beliefs via two approaches: pre-study global differentiated predictions (GPREDs) as an indicator of preexisting beliefs about font size and memory and ease of learning judgments (EORs) as online generated item-specific beliefs about fluency. In Experiment 1, EORs partially mediated the font-size effect, whereas self-paced study time did not. In Experiments 2a and 2b, EORs mediated the font-size effect; at the same time, beliefs about font size and memory moderated the font-size effect. In summary, the present study demonstrates a major role of beliefs underlying the font-size effect.</p></div

Mean JOL magnitude as a function of font size and group in Experiment 1.

<p>Error bars represent standard errors.</p

Studies supporting processing experience and/or beliefs as the basis for JOLs.

<p><b>Note</b>. ST = self-paced study time, EORs = ease of reading judgments, TTA = numbers of trials to acquisition, GPREDs = global differentiated predictions.</p