Language Detoxification with Attribute-Discriminative Latent Space

Transformer-based Language Models (LMs) have achieved impressive results on natural language understanding tasks, but they can also generate toxic text such as insults, threats, and profanity, limiting their real-world applications. To overcome this issue, a few text generation approaches aim to detoxify toxic texts using additional LMs or perturbations. However, previous methods require excessive memory, computations, and time which are serious bottlenecks in their real-world application. To address such limitations, we propose an effective yet efficient method for language detoxification using an attribute-discriminative latent space. Specifically, we project the latent space of an original Transformer LM onto a discriminative latent space that well-separates texts by their attributes using a projection block and an attribute discriminator. This allows the LM to control the text generation to be non-toxic with minimal memory and computation overhead. We validate our model, Attribute-Discriminative Language Model (ADLM) on detoxified language and dialogue generation tasks, on which our method significantly outperforms baselines both in performance and efficiency.Comment: ACL 2023; *Equal contribution. Author ordering determined by coin fli

Context-dependent Instruction Tuning for Dialogue Response Generation

Recent language models have achieved impressive performance in natural language tasks by incorporating instructions with task input during fine-tuning. Since all samples in the same natural language task can be explained with the same task instructions, many instruction datasets only provide a few instructions for the entire task, without considering the input of each example in the task. However, this approach becomes ineffective in complex multi-turn dialogue generation tasks, where the input varies highly with each turn as the dialogue context changes, so that simple task instructions cannot improve the generation performance. To address this limitation, we introduce a context-based instruction fine-tuning framework for each multi-turn dialogue which generates both responses and instructions based on the previous context as input. During the evaluation, the model generates instructions based on the previous context to self-guide the response. The proposed framework produces comparable or even outstanding results compared to the baselines by aligning instructions to the input during fine-tuning with the instructions in quantitative evaluations on dialogue benchmark datasets with reduced computation budget.Comment: Work in Progres

Knowledge Graph-Augmented Language Models for Knowledge-Grounded Dialogue Generation

Language models have achieved impressive performances on dialogue generation tasks. However, when generating responses for a conversation that requires factual knowledge, they are far from perfect, due to an absence of mechanisms to retrieve, encode, and reflect the knowledge in the generated responses. Some knowledge-grounded dialogue generation methods tackle this problem by leveraging facts from Knowledge Graphs (KGs); however, they do not guarantee that the model utilizes a relevant piece of knowledge from the KG. To overcome this limitation, we propose SUbgraph Retrieval-augmented GEneration (SURGE), a framework for generating context-relevant and knowledge-grounded dialogues with the KG. Specifically, our SURGE framework first retrieves the relevant subgraph from the KG, and then enforces consistency across facts by perturbing their word embeddings conditioned by the retrieved subgraph. Then, we utilize contrastive learning to ensure that the generated texts have high similarity to the retrieved subgraphs. We validate our SURGE framework on OpendialKG and KOMODIS datasets, showing that it generates high-quality dialogues that faithfully reflect the knowledge from KG.Comment: Preprint. Under revie

The current capacity and quality of colonoscopy in Korea

Background/Aims Little is known for the capacity and quality of colonoscopy, and adherence to colonoscopy surveillance guidelines in Korea. This study aimed to investigate the present and potential colonoscopic capacity, colonoscopic quality, and adherence to colonoscopy surveillance guidelines in Korea. Methods We surveyed representative endoscopists of 72 endoscopy units from June to August 2015, using a 36-item questionnaire regarding colonoscopic capacity, quality, and adherence to colonoscopy surveillance guidelines of each hospitals. Results Among the 62 respondents who answered the questionnaire, 51 respondents were analyzed after exclusion of 11 incomplete answers. Only 1 of 3 of endoscopy units can afford to perform additional colonoscopies in addition to current practice, and the potential maximum number of colonoscopies per week was only 42. The quality of colonoscopy was variable as reporting of quality indicators of colonoscopy were considerably variable (29.4%–94.1%) between endoscopy units. Furthermore, there are substantial gaps in the adherence to colonoscopy surveillance guidelines, as concordance rate for guideline recommendation was less than 50% in most scenarios. Conclusions The potential capacity and quality of colonoscopy in Korea was suboptimal. Considering suboptimal reporting of colonoscopic quality indicators and low adherence rate for colonoscopy surveillance guidelines, quality improvement of colonoscopy should be underlined in Korea

Implantable Cardioverter-Defibrillator Implantation in a Patient with Atrial Standstill

We report a 55-year-old female patient who presented with no P waves but with a wide QRS complex escape rhythm at 44 beats/min and prolonged QTc of 0.55 seconds on ECG. The patient had recurrence of ventricular fibrillations and loss of consciousness, and underwent defibrillation and cardiopulmonary resuscitation (CPR) several times because of cardiac arrest. The transthoracic echocardiography showed dilated cardiomyopathy and enlargement of both atria. The Doppler echocardiography documented the absence of A wave in the tricuspid and mitral valve flow. An electrophysiologic study demonstrated electrical inactivity in the right and left atria. Atrial pacing with maximum output did not capture the atria. These findings together with her electrocardiographic finding indicated atrial standstill. Sudden cardiac death was her first clinical manifestation of ventricular arrhythmia. The patient remained asymptomatic after receiving a single chamber implantable cardioverter-defibrillator (ICD) with VVI pacemaker function

Prognostic value of routine blood tests along with clinical risk factors in predicting ischemic stroke in non-valvular atrial fibrillation: a prospective cohort study

Abstract Background In patients with atrial fibrillation (AF), most biomarkers are still of limited use due to cost-effectiveness and complexity in clinical practice. Hypotheses Biomarkers from routine blood tests improve the current risk stratification in AF patients. Methods This prospective study enrolled 600 patients diagnosed with non-valvular AF, of whom 537 were analyzed. Platelet count; platelet distribution width (PDW); red cell distribution width (RDW); and creatinine, D-dimer, and troponin I levels were measured at enrollment. Results During the mean follow-up period (2.2 ± 0.6years), 1.9% patients developed ischemic stroke. According to the optimal cutoff of each biomarker, the risk of ischemic stroke was higher in patients with RDW ≥ 13.5%, creatinine ≥ 1.11mg/dL, or PDW ≥ 13.2% (significant biomarkers; P value: < 0.01, 0.04, or 0.07, respectively). These 3 significant biomarkers had higher information gain than clinical risk factors in predicting ischemic stroke. The cumulative incidence of ischemic stroke was 1.2%, 1.1%, 8.4%, and 40.0% in patients with 0, 1, 2, and 3 significant biomarkers, respectively (P-for-trend < 0.001). Patients with  ≥ 2 significant biomarkers had a significantly higher risk of ischemic stroke than those with  < 2 significant biomarkers (adjusted hazard ratio 11.5, 95% confidence interval 3.3–40.2, P < 0.001). The predictability for ischemic stroke was significantly improved when  ≥ 2 significant biomarkers were added to the CHA2DS2–VASc score (area under the curve 0.790 vs. 0.620, P = 0.043). Conclusion Routine blood tests can provide better risk stratification of AF along with clinical risk factors

Relationship between insulin resistance, obesity and serum prostate-specific antigen levels in healthy men

Abstract The purpose of this study was to determine the relationship between insulin resistance, obesity and serum prostate-specific antigen (PSA) levels in healthy men with serum PSA level below 4 ng mL -1 . The men included in the study cohort were 11 827 healthy male employees of the Korea Hydro and Nuclear Power Co., LTD who had undergone medical checkups including fasting glucose, fasting insulin and serum PSA between January 2003 and December 2008. Insulin resistance was calculated by homeostasis model assessment (HOMA [fasting glucose × fasting insulin]/22.5) and quantitative insulin sensitivity check index (QUICKI; 1/[log (fasting insulin) + log (fasting glucose)]). Age-adjusted body mass index (BMI) was significantly increased according to increasing quartile of insulin resistance as determined by HOMA and QUICKI, respectively, in analysis of variance (ANOVA) test and Duncan&apos;s multiple comparison test (P &lt; 0.001), but age-adjusted serum PSA concentration was significantly decreased according to increasing quartile of insulin resistance as determined by HOMA and QUICKI (P &lt; 0.001). Age, BMI, insulin resistance by HOMA or QUICKI were significantly independent variables to serum PSA level in a multivariate linear regression analysis (P &lt; 0.001). Insulin resistance was a significant independent variable to serum PSA level along with BMI. Insulin resistance and BMI were negatively correlated with serum PSA level in healthy men. Insulin resistance was positively correlated with BMI

Sensitization to Aeroallergens in Korean Children: A Population-based Study in 2010

We performed this study to assess the prevalence of sensitization to aeroallergens and to analyze the difference between prevalence rates according to children's ages and residential areas. In this nationwide cross-sectional study, first grade students of 45 elementary schools and 40 middle schools were randomly selected, and skin prick tests were performed for 18 inhalant allergens between October and November 2010. Of 7,829 analyzed subjects, 3,753 (47.9%) were sensitized to at least one aeroallergen. Sensitization to Dermatophagoides farinae was found to be the most prevalent in elementary schoolchildren (32.4%), followed by Dermatophagoides pteronyssinus, Tyrophagus putrescentiae, Japanese hop, and oak. In middle schoolchildren, D. pteronyssinus yielded the highest prevalence (42.7%), followed by D. farinae, T. putrescentiae, Japanese hop, and cat. In middle schoolchildren, the sensitization rate to aeroallergens in metropolitan, urban, and rural areas was 57.2%, 54.3%, and 49.8%, respectively (P = 0.019). In this age group, the sensitization rate in low, middle, high, and very high income groups was 53.8%, 51.8%, 59.0%, and 59.6%, respectively (P = 0.002). In conclusion, the sensitization rate is 47.9% and house dust mite is the most prevalent allergen in the pediatric population in Korea. The rate is higher in metropolitan areas and the highest income group than in rural areas and low income groups

Metodologias alternativas no ensino de física

Screening a compound library of quinolinone derivatives identified compound 11a as a new P2X7 receptor antagonist. To optimize its activity, we assessed structure-activity relationships (SAR) at three different positions, R_1, R_2 and R_3, of the quinolinone scaffold. SAR analysis suggested that a carboxylic acid ethyl ester group at the R_1 position, an adamantyl carboxamide group at R_2 and a 4-methoxy substitution at the R_3 position are the best substituents for the antagonism of P2X7R activity. However, because most of the quinolinone derivatives showed low inhibitory effects in an IL-1β ELISA assay, the core structure was further modified to a quinoline skeleton with chloride or substituted phenyl groups. The optimized antagonists with the quinoline scaffold included 2-chloro-5-adamantyl-quinoline derivative (16c) and 2-(4-hydroxymethylphenyl)-5-adamantyl-quinoline derivative (17k), with IC_(50) values of 4 and 3 nM, respectively. In contrast to the quinolinone derivatives, the antagonistic effects of the quinoline compounds (16c and 17k) were paralleled by their ability to inhibit the release of the pro-inflammatory cytokine, IL-1β, from LPS/IFN-γ/BzATP-stimulated THP-1 cells (IC_(50) of 7 and 12 nM, respectively). In addition, potent P2X7R antagonists significantly inhibited the sphere size of TS15-88 glioblastoma cells