Gotcha! Don't trick me with unanswerable questions! Self-aligning Large Language Models for Responding to Unknown Questions

Despite the remarkable abilities of Large Language Models (LLMs) to answer questions, they often display a considerable level of overconfidence even when the question does not have a definitive answer. To avoid providing hallucinated answers to these unknown questions, existing studies typically investigate approaches to refusing to answer these questions. In this work, we propose a novel and scalable self-alignment method to utilize the LLM itself to enhance its response-ability to different types of unknown questions, being capable of not only refusing to answer but also providing explanation to the unanswerability of unknown questions. Specifically, the Self-Align method first employ a two-stage class-aware self-augmentation approach to generate a large amount of unknown question-response data. Then we conduct disparity-driven self-curation to select qualified data for fine-tuning the LLM itself for aligning the responses to unknown questions as desired. Experimental results on two datasets across four types of unknown questions validate the superiority of the Self-Align method over existing baselines in terms of three types of task formulation

Robust Prompt Optimization for Large Language Models Against Distribution Shifts

Large Language Model (LLM) has demonstrated significant ability in various Natural Language Processing tasks. However, their effectiveness is highly dependent on the phrasing of the task prompt, leading to research on automatic prompt optimization using labeled task data. We reveal that these prompt optimization techniques are vulnerable to distribution shifts such as subpopulation shifts, which are common for LLMs in real-world scenarios such as customer reviews analysis. In this light, we propose a new problem of robust prompt optimization for LLMs against distribution shifts, which requires the prompt optimized over the labeled source group can simultaneously generalize to an unlabeled target group. To solve this problem, we propose Generalized Prompt Optimization framework, which incorporates the unlabeled data from the target group into prompt optimization. Extensive experimental results demonstrate the effectiveness of the proposed framework with significant performance improvement on the target group and comparable performance on the source group

Willingness of people living with HIV to receive a second COVID-19 booster dose: a multicenter cross-sectional study in China

BackgroundThe coronavirus disease 2019 (COVID-19) pandemic has significantly affected the global population, with People Living with HIV (PLWH) being particularly vulnerable due to their compromised immune systems. Although vaccination is a crucial preventative measure against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, little is understood about the willingness of PLWH to receive a second COVID-19 booster dose and the factors that may influence this decision. This study investigates the willingness of PLWH in China to receive a second COVID-19 booster dose and its influencing factors, comparing these with a group of healthy individuals.MethodsA multicenter cross-sectional study was conducted across five Chinese cities, namely, Beijing, Tianjin, Zhengzhou, Hohhot, and Harbin. Participants were recruited through five community-based organizations. Data were collected via participant self-administered questionnaires included demographic information, willingness to receive a second COVID-19 booster dose, and knowledge about HIV and COVID-19 vaccination. Factors influencing vaccination willingness were identified using multivariable logistic regression analyzes.ResultsA total of 156 PLWH and 151 healthy individuals were included in the study. After adjusting for potential confounders, it was found that PLWH demonstrated a lower willingness to receive a second COVID-19 booster dose compared to healthy individuals (77.6% vs. 88.7%, p = 0.009). Lower willingness was associated with HIV positive status (Adjusted Odds Ratio [AOR]: 0.39, 95%CI: 0.20, 0.75), perceived barriers (AOR: 0.05, 95%CI: 0.01, 0.26), and perceived severity (AOR: 0.32, 95%CI: 0.12, 0.90).ConclusionPLWH in China demonstrated a lower willingness to receive a second COVID-19 booster dose compared to healthy individuals. The findings suggest that perceptions and understanding of the COVID-19 vaccination and its necessity for protection against SARS-CoV-2 could influence this willingness. Efforts should be made to strengthen and disseminate knowledge about HIV and COVID-19 vaccinations among this population. In addition, developing interventions and policies that target specific subgroups and address misconceptions about vaccination could be instrumental in improving vaccination rates among PLWH

Progress in diagnosis and treatment of strabismus based on artificial intelligence technology

Strabismus, misalignment of the eyes arising from central nervous system dysregulation and extraocular muscles imbalance, commonly manifests in childhood, leading to amblyopia, binocular vision dysfunction, torticollis and other developmental and psychological disorders. This exerts a negative impact on individuals, families and society. Timely diagnosis and intervention are crucial to prevent permanent damage to vision and stereopsis. Presently, strabismus diagnosis is reliant on the ophthalmologists′ evaluations which results in a lack of efficiency and coverage. However, routine school screening proves inadequate in assessing strabismus degree with low accuracy. Therefore, how to improve the efficiency of strabismus screening is an issue of great importance. This paper delves into the present landscape of strabismus diagnosis and treatment, considering both local and global research advancements. It focuses on the evolution of artificial intelligence technology, illuminating the utilization of artificial intelligence models and algorithms in strabismus. By pinpointing and exploring their strengths and limitations, it offers valuable insights, paving the way for future investigations into artificial intelligence-assisted strabismus diagnosis and treatment

Abnormal attentional bias in individuals with suicidal ideation during an emotional Stroop task: an event-related potential study

IntroductionThere is increasing evidence that suicidal individuals exhibit an attentional bias toward negative or suicide-related stimuli, but the underlying neural mechanism remains unclear. This study aimed to investigate the neural mechanism of attentional bias toward emotional stimuli using a modified emotional Stroop task (EST) and to further explore the influencing factor of abnormal attention processing by identifying whether mental disorders or suicidal ideation contributes to attention processing disruptions.MethodsFourteen students with suicidal ideation and mental disorders (SIMDs), sixteen students with suicidal ideation but no mental disorders (SINMDs), and fourteen sex- and age-matched healthy controls (HCs) were recruited. Moreover, 64-channel electroencephalography (EEG) data and behavioral responses were recorded simultaneously during the EST. Participants were instructed to respond to the ink color for various types of words (positive, neutral, negative, and suicide) while ignoring their meanings. Event-related potentials (ERPs) were analyzed to evaluate attention to the stimuli. Spearman correlations between clinical psychological assessment scales and ERP signatures were analyzed to determine the risk factors for suicide.ResultsThe results showed that the SIMD group exhibited longer early posterior negativity (EPN) latency compared to the SINMD and HC groups, indicating that early attention processing was affected during the EST, and the automatic and rapid processing of emotional information decreased. Furthermore, P300 latency for positive words was positively correlated with current suicidal ideation in the SINMD group, suggesting that delayed responses or additional processing to positive information may lead individuals with suicidal ideation to an incorrect interpretation of external events.ConclusionsGenerally, our findings suggest that the neural characteristics of the SIMD group differed from those of the SINMD and HC groups. EPN latency and P300 latency during the EST may be suicide-related neurophysiological indicators. These results provide neurophysiological signatures of suicidal behavior

Influencing factors for pediatric eye disorders and health related quality of life: a cross-sectional study in Shanghai, China

BackgroundMyopia, strabismus, and ptosis are common pediatric eye diseases, which have a negative impact on children and adolescents in terms of visual function, mental health, and health-related quality of life (HRQoL). Therefore, this study focused on those pediatric eye diseases by analyzing their risk factors and HRQoL for the comprehensive management of myopia, strabismus, and ptosis.MethodsA total of 363 participants (2–18 years old) were included in this study for risk factors analysis of myopia, strabismus, and ptosis. We collected demographic characteristics, lifestyle habits and eye care habits of these children and analyzed them by using univariable and multivariable logistic regression. In addition, we applied the Chinese version of Pediatric Quality of Life Inventory-Version 4.0 (PedsQL 4.0) to assess HRQoL in 256 children with strabismus and ptosis. Univariable and multivariable linear regression models were applied to evaluate potential influencing factors of HRQoL.ResultsOf all the participants, 140 had myopia, 127 had strabismus, and 145 had ptosis. Based on the multivariable logistic regression analysis model, we found that the history of parental myopia and daily average near-distance eye usage time were risk factors for myopia, and increased body mass index (BMI) was identified as a risk factor for strabismus and ptosis. Individuals with ptosis possessed decreased HRQoL. The multivariable linear regression model suggested that daily average near-distance eye usage time, light intensity during visual tasks, and daily average sleep duration had potential influences on HRQoL.ConclusionThis is the first study to assess the risk factors and HRQoL of myopia, strabismus, and ptosis together. We identified risk factors for these common pediatric eye diseases to help doctors, parents, and teachers better manage them. Our study discovered that children with eye disorders exhibit a notably diminished HRQoL. Consequently, it emphasizes the necessity for increased social attention and mental health assistance for these children

Mouse Strain– and Charge-Dependent Vessel Permeability of Nanoparticles at the Lower Size Limit

Remarkable advancement has been made in the application of nanoparticles (NPs) for cancer therapy. Although NPs have been favorably delivered into tumors by taking advantage of the enhanced permeation and retention (EPR) effect, several physiological barriers present within tumors tend to restrict the diffusion of NPs. To overcome this, one of the strategies is to design NPs that can reach lower size limits to improve tumor penetration without being rapidly cleared out by the body. Several attempts have been made to achieve this, such as selecting appropriate nanocarriers and modifying surface properties. While many studies focus on the optimal design of NPs, the influence of mouse strains on the effectiveness of NPs remains unknown. Therefore, this study aimed to assess whether the vascular permeability of NPs near the lower size limit differs among mouse strains. We found that the vessel permeability of dextran NPs was size-dependent and dextran NPs with a size below 15 nm exhibited leakage from postcapillary venules in all strains. Most importantly, the leakage rate of 8-nm fluorescein isothiocyanate dextran was significantly higher in the BALB/c mouse strain than in other strains. This strain dependence was not observed in slightly positive TRITC-dextran with comparable sizes. Our results indicate that the influence on mouse strains needs to be taken into account for the evaluation of NPs near the lower size limit

Learning Sense Representation from Word Representation for Unsupervised Word Sense Disambiguation (Student Abstract)

Unsupervised WSD methods do not rely on annotated training datasets and can use WordNet. Since each ambiguous word in the WSD task exists in WordNet and each sense of the word has a gloss, we propose SGM and MGM to learn sense representations for words in WordNet using the glosses. In the WSD task, we calculate the similarity between each sense of the ambiguous word and its context to select the sense with the highest similarity. We evaluate our method on several benchmark WSD datasets and achieve better performance than the state-of-the-art unsupervised WSD systems

Neural responses to social decision-making in suicide attempters with mental disorders

Abstract Background Decision-making deficits have been reported in suicide attempters and may be a neuropsychological trait of vulnerability to suicidal behavior. However, little is known about how neural activity is altered in decision-making. This study aimed to investigate the neural responses in suicide attempters with mental disorders during social decision-making. Electroencephalography (EEG) were recorded from 52 patients with mental disorders with past suicide attempts (SAs = 26) and without past suicide attempts (NSAs = 26), as well as from 22 age- and sex- matched healthy controls (HCs) during the Ultimatum Game (UG), which is a typical paradigm to investigate the responses to fair and unfair decision-making. Methods MINI 5.0 interview and self report questionnaire were used to make mental diagnosis and suicide behavior assessment for individuals. Event-related potential (ERP) and phase-amplitude coupling (PAC) were extracted to quantify the neural activity. Furthermore, Spearman correlation and logistic regression analyses were conducted to identify the risk factors of suicidal behavior. Results ERP analysis demonstrated that SA patients had decreased P2 amplitude and prolonged P2 latency when receiving unfair offers. Moreover, SA patients exhibited greater negative-going feedback-related negativity (FRN) to unfair offers compared to fair ones, whereas such a phenomenon was absent in NSA and HC groups. These results revealed that SA patients had a stronger fairness principle and a disregard toward the cost of punishment in social decision-making. Furthermore, theta-gamma and beta-gamma PAC were involved in decision-making, with compromised neural coordination in the frontal, central, and temporal regions in SA patients, suggesting cognitive dysfunction during social interaction. Statistically significant variables were used in logistic regression analysis. The area under receiver operating characteristic curve in the logistic regression model was 0.91 for SA/HC and 0.84 for SA/NSA. Conclusions Our findings emphasize that suicide attempts in patients with mental disorders are associated with abnormal decision-making. P2, theta-gamma PAC, and beta-gamma PAC may be neuro-electrophysiological biomarkers associated with decision-making. These results provide neurophysiological signatures of suicidal behavior