PEFTDebias : Capturing debiasing information using PEFTs

The increasing use of foundation models highlights the urgent need to address and eliminate implicit biases present in them that arise during pretraining. In this paper, we introduce PEFTDebias, a novel approach that employs parameter-efficient fine-tuning (PEFT) to mitigate the biases within foundation models. PEFTDebias consists of two main phases: an upstream phase for acquiring debiasing parameters along a specific bias axis, and a downstream phase where these parameters are incorporated into the model and frozen during the fine-tuning process. By evaluating on four datasets across two bias axes namely gender and race, we find that downstream biases can be effectively reduced with PEFTs. In addition, we show that these parameters possess axis-specific debiasing characteristics, enabling their effective transferability in mitigating biases in various downstream tasks. To ensure reproducibility, we release the code to do our experiments.Comment: EMNLP 202

Factors influencing control of convulsive status epilepticus in children

Background: Convulsive status epilepticus (CSE) is an important cause of morbidity and mortality in pediatrics. Objectives: The objectives of the study were to examine the influence of any clinical factor on control of CSE in children. Methods: Cases of CSE in the age group of 1 month–12 years, admitted to the emergency ward of a tertiary care hospital, over a period of 1 year, were studied, prospectively. Only those cases that were actively convulsing at arrival were enrolled. Difficult cases were shifted pediatric intensive care unit and were put on mechanical ventilator as needed. After initial stabilization, detailed case-work up and appropriate investigations to find the etiology were done. The data were analyzed statistically and p<0.05 was considered as statistically significant. Results: The data of 50 cases that fulfilled the enrolment criteria were analyzed. Convulsions in the majority of the cases could be controlled within 30 min. Out of the study patients, 39 cases (78%) needed >1 drug for controlling the convulsive episodes. Control was extremely difficult in 10 (20%) of the cases while 3 (6%) cases died. The time needed to control the episodes showed significant correlation with several clinical factors, namely focal seizure with impaired consciousness, multiple episodes of convulsion (discrete type), focal deficit, Glasgow Coma Scale score <9, abnormal neuroimaging finding, central nervous system infections (meningitis and encephalitis together), and prolonged duration of convulsions before arrival at the emergency ward. However, on multivariate analysis prolonged duration of convulsion before arrival at emergency was found to be the most significant predictor of time needed to control the episodes. Conclusion: Prolonged duration of convulsion before arriving at the hospital can be considered to be a predictor of difficult control of CSE in children

Prechemotherapy Levels of Plasma Dehydroepiandrosterone and Its Sulfated Form as Predictors of Cancer-Related Cognitive Impairment in Patients with Breast Cancer Receiving Chemotherapy.

Study objectiveDehydroepiandrosterone (DHEA) and its sulfated form (DHEAS)-jointly referred to as DHEA(S)-are neurosteroids known to regulate brain development and function that have been found to be positively correlated with cognitive function. It is unknown whether prechemotherapy plasma DHEA(S) levels are associated with the onset of cancer-related cognitive impairment (CRCI). The objective of this study was to evaluate whether an association exists between prechemotherapy plasma DHEA(S) levels and onset of CRCI in patients with breast cancer receiving chemotherapy.DesignMulticenter, prospective cohort study.SettingTwo specialized cancer centers in Singapore.PatientsEighty-one patients with early-stage breast cancer (stages I-III) who had no prior exposure to chemotherapy and/or radiotherapy and were scheduled to receive anthracycline-based or taxane-based chemotherapy treatment with curative intent.Measurements and main resultsPatients completed assessments for self-perceived and objective cognitive function at three time points: prechemotherapy (T1), during chemotherapy (T2), and after chemotherapy (T3). Plasma samples were collected prior to chemotherapy, and DHEA(S) levels were quantified by using ultra-high-performance liquid chromatography-tandem mass spectrometry. Multivariable logistic regression was used to adjust for clinically important factors and to evaluate the association between prechemotherapy plasma DHEA(S) levels and CRCI. Mean ± SD age was 48.9 ± 9.3 years, with 27.8% of patients experiencing clinically significant cognitive impairment based on global Functional Assessment of Cancer Therapy-Cognitive Function scores. The mean ± SD prechemotherapy plasma DHEAS and DHEA levels were 1.61 ± 0.91 μmol/L and 19.21 ± 13.13 nmol/L, respectively. Prechemotherapy DHEAS levels were found to be associated with impairment in the self-perceived cognitive domains of verbal fluency (adjusted odds ratio [OR] 0.27, 95% confidence interval [CI] 0.08-0.96) and mental acuity (adjusted OR 0.25, 95% CI 0.08-0.74). Conversely, DHEA levels were not associated with impairment in any cognitive subdomains.ConclusionOur findings suggest that patients with higher prechemotherapy DHEAS levels had lower odds of developing self-perceived cognitive impairment. Future studies are required to further investigate the effect of DHEA(S) on specific cognitive domains and to validate our findings in independent cohorts

Improved Hybrid Model of HMM/GMM for Speech Recognition

In this paper, we propose a speech recognition engine using hybrid model of Hidden Markov Model (HMM) and Gaussian Mixture Model (GMM). Both the models have been trained independently and the respective likelihood values have been considered jointly and input to a decision logic which provides net likelihood as the output. This hybrid model has been compared with the HMM model. Training and testing has been done by using a database of 20 Hindi words spoken by 80 different speakers. Recognition rates achieved by normal HMM are 83.5% and it gets increased to 85% by using the hybrid approach of HMM and GMM

CyCLIP: Cyclic Contrastive Language-Image Pretraining

Recent advances in contrastive representation learning over paired image-text data have led to models such as CLIP that achieve state-of-the-art performance for zero-shot classification and distributional robustness. Such models typically require joint reasoning in the image and text representation spaces for downstream inference tasks. Contrary to prior beliefs, we demonstrate that the image and text representations learned via a standard contrastive objective are not interchangeable and can lead to inconsistent downstream predictions. To mitigate this issue, we formalize consistency and propose CyCLIP, a framework for contrastive representation learning that explicitly optimizes for the learned representations to be geometrically consistent in the image and text space. In particular, we show that consistent representations can be learned by explicitly symmetrizing (a) the similarity between the two mismatched image-text pairs (cross-modal consistency); and (b) the similarity between the image-image pair and the text-text pair (in-modal consistency). Empirically, we show that the improved consistency in CyCLIP translates to significant gains over CLIP, with gains ranging from 10%-24% for zero-shot classification accuracy on standard benchmarks (CIFAR-10, CIFAR-100, ImageNet1K) and 10%-27% for robustness to various natural distribution shifts. The code is available at https://github.com/goel-shashank/CyCLIP.Comment: 19 pages, 13 tables, 6 figures, Oral at NeuRIPS 202

A Bibliometric Overview of the Field of Type-2 Fuzzy Sets and Systems [Discussion Forum]

© 2005-2012 IEEE. Fuzzy Sets and Systems is an area of computational intelligence, pioneered by Lotfi Zadeh over 50 years ago in a seminal paper in Information and Control. Fuzzy Sets (FSs) deal with uncertainty in our knowledge of a particular situation. Research and applications in FSs have grown steadily over 50 years. More recently, we have seen a growth in Type-2 Fuzzy Set (T2 FS) related papers, where T2 FSs are utilized to handle uncertainty in realworld problems. In this paper, we have used bibliometric methods to obtain a broad overview of the area of T2 FSs. This method analyzes information on the bibliographic details of published journal papers, which includes title, authors, author address, journals and citations, extracted from the Science and Social Science Citation Indices in the Web of Science (WoS) database for the last 20 years (1997-2017). We have compared the growth of publications in the field of FSs, and its subset T2 FSs, identified highly cited papers in T2 FSs, highly cited authors, key institutions, and main countries with researchers involved in T2 FS related research

Evaluation of prescribing pattern of antidiabetic drugs in medicine outpatient clinic of a tertiary care teaching hospital

Background: Diabetes is rapidly gaining the status of a potential epidemic in India with more than 62 million diabetics currently diagnosed with the disease. Drug utilization studies are of paramount importance for the optimization of drug therapy and promote rational drug use among health care providers. The aim of this study was to investigate the drug utilization pattern in type-2 diabetic patients. The objective of the study was to analyse the prescribing pattern of anti-diabetic drugs in a tertiary care hospital.Methods: A prospective, cross-sectional study was carried out in medicine outpatient clinic of tertiary care hospital, RIMS Ranchi for a period of 7 months. The data was analysed using WHO core indicators and Microsoft Excel 2013.Results: The total number of encounters surveyed was 94. Avg no of drugs per prescription was 3.04. Percentage of drugs prescribed by generic name was found to be 34.2%. Percentage of prescriptions was a) with antibiotics was 27.6%, b) with insulin was 14.89%, c) from essential drugs list 44.05%. Most common co morbid disease was found to be hypertension present in 27.6% cases.Most commonly use drug was found to be metformin followed by glimepiride.Conclusions: Implementation of WHO core prescribing indicators by the prescribers would help us to reduce the cost, to recognize and prevent potentially dangerous drug- drug interaction and antibiotic resistance