Evaluating natural language processing models with generalization metrics that do not need access to any training or testing data

The search for effective and robust metrics has been the focus of recent theoretical and empirical work on generalization of deep neural networks (NNs). In this paper, we discuss the performance of natural language processing (NLP) models, and we evaluate various existing and novel generalization metrics. Compared to prior studies, we (i) focus on NLP instead of computer vision (CV), (ii) focus on generalization metrics that predict test error instead of the generalization gap, (iii) focus on generalization metrics that do not need the access to data, and (iv) focus on the heavy-tail (HT) phenomenon that has received comparatively less attention in the study of NNs. We extend recent HT-based work which focuses on power law (PL) distributions, and we study exponential and exponentially truncated power law (E-TPL) fitting to the empirical spectral densities (ESDs) of weight matrices. Our empirical studies are carried on (i) hundreds of Transformers trained in different settings, in which we systematically vary different hyperparameters, (ii) a total of 51 pretrained Transformers from eight families of Huggingface NLP models, including BERT, GPT2, etc., and (iii) a total of 28 existing and novel generalization metrics. From our empirical analyses, we show that shape metrics, or the metrics obtained from fitting the shape of the ESDs, perform uniformly better at predicting generalization performance than scale metrics commonly studied in the literature, as measured by the rank correlations with the generalization performance. We also show that among the three HT distributions considered in our paper, the E-TPL fitting of ESDs performs the most robustly when the models are trained in experimental settings, while the PL fitting achieves the best performance on well-trained Huggingface models, and that both E-TPL and PL metrics (which are both shape metrics) outperform scale metrics

Religious Identity, Religious Attendance, and Parental Control

Using a national sample of adolescents aged 10–18 years and their parents (N = 5,117), this article examines whether parental religious identity and religious participation are associated with the ways in which parents control their children. We hypothesize that both religious orthodoxy and weekly religious attendance are related to heightened levels of three elements of parental control: monitoring activities, normative regulations, and network closure. Results indicate that an orthodox religious identity for Catholic and Protestant parents and higher levels of religious attendance for parents as a whole are associated with increases in monitoring activities and normative regulations of American adolescents

The SEC\u27s Misguided Climate Disclosure Rule Proposal

The following article adapts and consolidates two comment letters submitted last spring by a group of twenty-two professors of finance and law on the SEC’s proposed climate change disclosure rules. The professors reiterate their recommendation that the SEC withdraw its proposal as legally misguided, while outlining some of the issues that the proposal will face when challenged in court

Cross-Species Analyses Identify Dlgap2 as a Regulator of Age-Related Cognitive Decline and Alzheimer\u27s Dementia.

Genetic mechanisms underlying age-related cognitive decline and dementia remain poorly understood. Here, we take advantage of the Diversity Outbred mouse population to utilize quantitative trait loci mapping and identify Dlgap2 as a positional candidate responsible for modifying working memory decline. To evaluate the translational relevance of this finding, we utilize longitudinal cognitive measures from human patients, RNA expression from post-mortem brain tissue, data from a genome-wide association study (GWAS) of Alzheimer\u27s dementia (AD), and GWAS results in African Americans. We find an association between Dlgap2 and AD phenotypes at the variant, gene and protein expression, and methylation levels. Lower cortical DLGAP2 expression is observed in AD and is associated with more plaques and tangles at autopsy and faster cognitive decline. Results will inform future studies aimed at investigating the cross-species role of Dlgap2 in regulating cognitive decline and highlight the benefit of using genetically diverse mice to prioritize novel candidates

The Demographics, Stellar Populations, and Star Formation Histories of Fast Radio Burst Host Galaxies: Implications for the Progenitors

We present a comprehensive catalog of observations and stellar population properties for 23 highly secure host galaxies of fast radio bursts (FRBs). Our sample comprises six repeating FRBs and 17 apparent non-repeaters. We present 82 new photometric and eight new spectroscopic observations of these hosts. Using stellar population synthesis modeling and employing non-parametric star formation histories (SFHs), we find that FRB hosts have a median stellar mass of $\approx 10^{9.9}\,M_{\odot}$, mass-weighted age $\approx 5.1$ Gyr, and ongoing star formation rate $\approx 1.3\,M_{\odot}$ yr$^{-1}$ but span wide ranges in all properties. Classifying the hosts by degree of star formation, we find that 87% (20/23 hosts) are star-forming, two are transitioning, and one is quiescent. The majority trace the star-forming main sequence of galaxies, but at least three FRBs in our sample originate in less active environments (two non-repeaters and one repeater). Across all modeled properties, we find no statistically significant distinction between the hosts of repeaters and non-repeaters. However, the hosts of repeating FRBs generally extend to lower stellar masses, and the hosts of non-repeaters arise in more optically luminous galaxies. While four of the galaxies with the most clear and prolonged rises in their SFHs all host repeating FRBs, demonstrating heightened star formation activity in the last $\lesssim 100$ Myr, one non-repeating host shows this SFH as well. Our results support progenitor models with short delay channels (i.e., magnetars formed via core-collapse supernova) for most FRBs, but the presence of some FRBs in less active environments suggests a fraction form through more delayed channels.Comment: 52 pages, 32 figures, 6 tables, submitte