Weakly Supervised Semantic Parsing with Execution-based Spurious Program Filtering

The problem of spurious programs is a longstanding challenge when training a semantic parser from weak supervision. To eliminate such programs that have wrong semantics but correct denotation, existing methods focus on exploiting similarities between examples based on domain-specific knowledge. In this paper, we propose a domain-agnostic filtering mechanism based on program execution results. Specifically, for each program obtained through the search process, we first construct a representation that captures the program's semantics as execution results under various inputs. Then, we run a majority vote on these representations to identify and filter out programs with significantly different semantics from the other programs. In particular, our method is orthogonal to the program search process so that it can easily augment any of the existing weakly supervised semantic parsing frameworks. Empirical evaluations on the Natural Language Visual Reasoning and WikiTableQuestions demonstrate that applying our method to the existing semantic parsers induces significantly improved performances.Comment: EMNLP 202

Optimal Harvesting for an Age-Spatial-Structured Population Dynamic Model with External Mortality

We study an optimal harvesting for a nonlinear age-spatial-structured population dynamic model, where the dynamic system contains an external mortality rate depending on the total population size. The total mortality consists of two types: the natural, and external mortality and the external mortality reflects the effects of external environmental causes. We prove the existence and uniqueness of solutions for the population dynamic model. We also derive a sufficient condition for optimal harvesting and some necessary conditions for optimality in an optimal control problem relating to the population dynamic model. The results may be applied to an optimal harvesting for some realistic biological models

Refining Generative Process with Discriminator Guidance in Score-based Diffusion Models

The proposed method, Discriminator Guidance, aims to improve sample generation of pre-trained diffusion models. The approach introduces a discriminator that gives explicit supervision to a denoising sample path whether it is realistic or not. Unlike GANs, our approach does not require joint training of score and discriminator networks. Instead, we train the discriminator after score training, making discriminator training stable and fast to converge. In sample generation, we add an auxiliary term to the pre-trained score to deceive the discriminator. This term corrects the model score to the data score at the optimal discriminator, which implies that the discriminator helps better score estimation in a complementary way. Using our algorithm, we achive state-of-the-art results on ImageNet 256x256 with FID 1.83 and recall 0.64, similar to the validation data's FID (1.68) and recall (0.66). We release the code at https://github.com/alsdudrla10/DG.Comment: International Conference on Machine Learning (ICML23

Target-Agnostic Gender-Aware Contrastive Learning for Mitigating Bias in Multilingual Machine Translation

Gender bias is a significant issue in machine translation, leading to ongoing research efforts in developing bias mitigation techniques. However, most works focus on debiasing bilingual models without much consideration for multilingual systems. In this paper, we specifically target the gender bias issue of multilingual machine translation models for unambiguous cases where there is a single correct translation, and propose a bias mitigation method based on a novel approach. Specifically, we propose Gender-Aware Contrastive Learning, GACL, which encodes contextual gender information into the representations of non-explicit gender words. Our method is target language-agnostic and is applicable to pre-trained multilingual machine translation models via fine-tuning. Through multilingual evaluation, we show that our approach improves gender accuracy by a wide margin without hampering translation performance. We also observe that incorporated gender information transfers and benefits other target languages regarding gender accuracy. Finally, we demonstrate that our method is applicable and beneficial to models of various sizes.Comment: Accepted to EMNLP 2023 Main Conferenc

Journey of Mesenchymal Stem Cells for Homing: Strategies to Enhance Efficacy and Safety of Stem Cell Therapy

Human mesenchymal stem cells (MSCs) communicate with other cells in the human body and appear to “home” to areas of injury in response to signals of cellular damage, known as homing signals. This review of the state of current research on homing of MSCs suggests that favorable cellular conditions and the in vivo environment facilitate and are required for the migration of MSCs to the site of insult or injury in vivo. We review the current understanding of MSC migration and discuss strategies for enhancing both the environmental and cellular conditions that give rise to effective homing of MSCs. This may allow MSCs to quickly find and migrate to injured tissues, where they may best exert clinical benefits resulting from improved homing and the presence of increased numbers of MSCs

The Effect of Obstructive Sleep Apnea on DNA Damage and Oxidative Stress

ObjectivesObstructive sleep apnea syndrome (OSAS) is associated with repeated hypoxia and re-oxygenation. This characteristic of OSAS may cause oxidative stress and DNA damage. However, the link of OSAS with oxidative stress and DNA damage is still controversial. In the current study, we investigated whether OSAS causes DNA damage using alkaline single-cell gel electrophoresis (comet assay) and measuring oxidative stress by monitoring serum malondialdehyde (MDA) levels.MethodsFrom March 2009 to August 2010, 51 patients who underwent polysomnography (PSG) during the night were enrolled in this study. We obtained serum from the patients at 6 AM. DNA damage and oxidative stress were evaluated using a comet assay and measuring serum MDA, respectively. We divided the patients into two groups according to the existence of comets appearing in the comet assay. Group 1 included 44 patients with negative assay results and group 2 consisted of seven patients with positive comet assay findings. We compared the age, gender proportion, PSG data (respiratory disturbance index [RDI], lowest O2 saturation level, and arousal index [AI]), time of disease onset, smoking habits, and serum MDA levels between the two groups.ResultsThe average age and gender proportion of the two groups were not statistically different (P>0.05). The average of RDI for group 1 was 30.4±18.4 and 8.0±7.7 (P0.05). No relationship between positive comet assay results and OSAS severity was identified.ConclusionResults of the current study showed that OSAS was not associated with DNA damage as measured by comet assays or oxidative stress according to serum MDA levels

Comparison of Component-Resolved Diagnosis by Using Allergen Microarray With the Conventional Tests in Allergic Rhinitis Patients: The First Using in Korea

ObjectivesThe aim of this study was to evaluate the component-resolved diagnosis using a microarray allergen chip (Immuno Solid-phase Allergen Chip, ImmunoCAP ISAC) and to compare this new diagnostic tool with the established ImmunoCAP methods for allergen-specific IgE detection in allergic rhinitis patients.MethodsOne hundred sixty-eight allergic rhinitis patients were included in this study. All the patients were diagnosed with allergic rhinitis according to their clinical symptoms, physical examination and a positive skin prick test. We analyzed their specific IgEs for house dust mites (Dermatophagoides farine [DF] and Dermatophagoides pteronyssinus [DP]), Alternaria alternata, birch, and mugwort using ImmunoCAP and ImmunoCAP ISAC in the same patient sample. We compared the sensitivity and correlation between the two tests.ResultsIn cases of allergies to DP and DF, the sensitivity of the specific IgE was 80% and that of the allergen microarray was 78.9%. The correlation between the two tests was significant for both DP and DF (P<0.001). For the A. alternata, birch and mugwort allergens, the sensitivity of ImmunoCAP ISAC was slightly lower than that of ImmunoCAP.ConclusionThese results suggest that the allergen microarray chip method is a reliable new method to diagnose the components of an allergen in patients with allergic rhinitis sensitive to house dust mites. Further study about the utility of the allergen microarray is needed

Optimal Harvesting for an Age-Spatial-Structured Population Dynamic Model with External Mortality

We study an optimal harvesting for a nonlinear age-spatial-structured population dynamic model, where the dynamic system contains an external mortality rate depending on the total population size. The total mortality consists of two types: the natural, and external mortality and the external mortality reflects the effects of external environmental causes. We prove the existence and uniqueness of solutions for the population dynamic model. We also derive a sufficient condition for optimal harvesting and some necessary conditions for optimality in an optimal control problem relating to the population dynamic model. The results may be applied to an optimal harvesting for some realistic biological models