Bias or Diversity? Unraveling Semantic Discrepancy in U.S. News Headlines

There is a broad consensus that news media outlets incorporate ideological biases in their news articles. However, prior studies on measuring the discrepancies among media outlets and further dissecting the origins of semantic differences suffer from small sample sizes and limited scope. In this study, we collect a large dataset of 1.8 million news headlines from major U.S. media outlets spanning from 2014 to 2022 to thoroughly track and dissect the semantic discrepancy in U.S. news media. We employ multiple correspondence analysis (MCA) to quantify the semantic discrepancy relating to four prominent topics - domestic politics, economic issues, social issues, and foreign affairs. Additionally, we compare the most frequent n-grams in media headlines to provide further qualitative insights into our analysis. Our findings indicate that on domestic politics and social issues, the discrepancy can be attributed to a certain degree of media bias. Meanwhile, the discrepancy in reporting foreign affairs is largely attributed to the diversity in individual journalistic styles. Finally, U.S. media outlets show consistency and high similarity in their coverage of economic issues

GPT-4V(ision) as A Social Media Analysis Engine

Recent research has offered insights into the extraordinary capabilities of Large Multimodal Models (LMMs) in various general vision and language tasks. There is growing interest in how LMMs perform in more specialized domains. Social media content, inherently multimodal, blends text, images, videos, and sometimes audio. Understanding social multimedia content remains a challenging problem for contemporary machine learning frameworks. In this paper, we explore GPT-4V(ision)'s capabilities for social multimedia analysis. We select five representative tasks, including sentiment analysis, hate speech detection, fake news identification, demographic inference, and political ideology detection, to evaluate GPT-4V. Our investigation begins with a preliminary quantitative analysis for each task using existing benchmark datasets, followed by a careful review of the results and a selection of qualitative samples that illustrate GPT-4V's potential in understanding multimodal social media content. GPT-4V demonstrates remarkable efficacy in these tasks, showcasing strengths such as joint understanding of image-text pairs, contextual and cultural awareness, and extensive commonsense knowledge. Despite the overall impressive capacity of GPT-4V in the social media domain, there remain notable challenges. GPT-4V struggles with tasks involving multilingual social multimedia comprehension and has difficulties in generalizing to the latest trends in social media. Additionally, it exhibits a tendency to generate erroneous information in the context of evolving celebrity and politician knowledge, reflecting the known hallucination problem. The insights gleaned from our findings underscore a promising future for LMMs in enhancing our comprehension of social media content and its users through the analysis of multimodal information

NEOLAF, an LLM-powered neural-symbolic cognitive architecture

This paper presents the Never Ending Open Learning Adaptive Framework (NEOLAF), an integrated neural-symbolic cognitive architecture that models and constructs intelligent agents. The NEOLAF framework is a superior approach to constructing intelligent agents than both the pure connectionist and pure symbolic approaches due to its explainability, incremental learning, efficiency, collaborative and distributed learning, human-in-the-loop enablement, and self-improvement. The paper further presents a compelling experiment where a NEOLAF agent, built as a problem-solving agent, is fed with complex math problems from the open-source MATH dataset. The results demonstrate NEOLAF's superior learning capability and its potential to revolutionize the field of cognitive architectures and self-improving adaptive instructional systems

Extracranial Artery Stenosis Is Associated With Total MRI Burden of Cerebral Small Vessel Disease in Ischemic Stroke Patients of Suspected Small or Large Artery Origins

Background and Purpose: Extracranial artery stenosis (ECAS) is related to individual imaging markers of cerebral small vessel disease (cSVD). However, little has been reported on the association between ECAS and the total burden of cSVD as assessed by magnetic resonance imaging (MRI). The purpose of this study was to investigate the relationship between ECAS and cSVD burden in patients with ischemic stroke of suspected small or large artery origin.Methods: We reviewed consecutive patients with ischemic stroke of suspected small or large artery origin who underwent color Doppler ultrasonography and brain MRI. Bilateral extracranial cerebral arteries including common carotid artery, internal carotid artery (ICA), and proximal vertebral artery (VA, ostium, V2–3 segments) were assessed using color Doppler ultrasonography. ECAS severity was classified as no/mild stenosis, moderate stenosis, severe stenosis, or occlusion. The total cSVD score was assessed by awarding one point according to the load of each of these cSVD markers as determined using MRI; lacunar infarction, white matter hyperintensities, cerebral microbleeds, and enlarged perivascular spaces. The relationship between ECAS severity and cSVD burden according to MRI was examined.Results: Two hundred and twenty one patients were included in this study (mean age 61 ± 12 years, 75.6% male). Hypertension, current smoking, hyperlipidaemia, and diabetic mellitus were frequent among the patients (67.4, 45.7, 43.9, and 36.7%, respectively), while the other vascular risk factors including previous stroke or TIA and alcohol excess were less frequent (19.0 and 15.4%, respectively). Patients with higher total cSVD burden was significantly older and had severer ECAS. The frequency of hypertension was significantly higher in patients with higher total cSVD burden. This analysis indicated that that increasing ECAS severity (from no stenosis through to 100%) was independently associated with increasing total cSVD score after adjusting for other vascular risk factors (odds ratio 1.76, 95% CI [1.16–2.69]).Conclusions: In this study, high levels of ECAS from ultrasound evidence were associated with coexisting advanced cerebral cSVD in ischemic stroke patients of suspected small or large artery origin. Further studies are required to determine if and how extracranial arterial imaging helps reduce cSVD burden or improves cognitive function

Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)

In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure fl ux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defi ned as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (inmost higher eukaryotes and some protists such as Dictyostelium ) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the fi eld understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation it is imperative to delete or knock down more than one autophagy-related gene. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways so not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field