Commonsense Understanding Research Articles

Language-based reasoning graph neural network for commonsense question answering

Language model (LM) has played an increasingly important role in the common-sense understanding and reasoning in the CSQA task (Common Sense Question Answering). However, due to the amount of model parameters, increasing training data helps little in further improving model performance. Introducing external knowledge through graph neural networks (GNNs) proves positive in boosting performance, but exploiting different knowledge sources and capturing contextual information between text and knowledge inside remains a challenge. In this paper, we propose LBR-GNN, a Language-Based Reasoning Graph Neural Network method to address these problems, by representing the question with each answer and external knowledge using a language model and predicting the reasoning score with a designed language-based GNN. Our LBR-GNN will first regulate external knowledge into a consistent textual form and encode it using a standard LM to capture the contextual information. Then, we build a graph neural network using the encoded information, especially the language-level edge representation. Finally, we design a novel edge aggregation method to select the edge information for GNN update and the language-guided GNN reasoning. We assess the performance of LBR-GNN across the CommonsenseQA, CommonsenseQA-IH, and OpenBookQA datasets. Our evaluation reveals a performance boost of more than 5% compared to the state-of-the-art methods on the CSQA dataset, achieved with a similar number of additional parameters.

COMMON SENSE IN FOLKLORE “ASAL USUL NAMA KELANTAN”: GAME BASED LEARNING APPLICATIONS IN TEACHING OF STUDENT PERSPECTIVE USING KAHOOT

Malay Folklore, traditionally transmitted, has long served as a vessel for imparting advice, teachings, and values that accentuate the identity of the Malay community. However, the tide of modernity has altered the delivery of folklore, transitioning it from oral tradition to various graphic media formats. Hence, this study aimed to explore and analyze commen sense in folklore “Asal Usul Nama Kelantan” as a game based learning applications in teaching of student perspective, utilizing the Kahoot application. Employing qualitative methods such as library research, fieldwork, and questionnaires, the study sought to enrich its findings. Additionally, Cultural Theory, as proposed by Chris Barker (2009), was adopted through an ethnographic approach. The Kahoot application was employed to gauge the understanding of common sense among to students at Universitiy Malaysia Kelantan. The findings revealed that the story of Asal Usul Kelantan significant relevance in reinvigorating its heritage for today’s younger generation.

ConvoSense: Overcoming Monotonous Commonsense Inferences for Conversational AI

Abstract Mastering commonsense understanding and reasoning is a pivotal skill essential for conducting engaging conversations. While there have been several attempts to create datasets that facilitate commonsense inferences in dialogue contexts, existing datasets tend to lack in-depth details, restate information already present in the conversation, and often fail to capture the multifaceted nature of commonsense reasoning. In response to these limitations, we compile a new synthetic dataset for commonsense reasoning in dialogue contexts using GPT, ℂonvoSense, that boasts greater contextual novelty, offers a higher volume of inferences per example, and substantially enriches the detail conveyed by the inferences. Our dataset contains over 500,000 inferences across 12,000 dialogues with 10 popular inference types, which empowers the training of generative commonsense models for dialogue that are superior in producing plausible inferences with high novelty when compared to models trained on the previous datasets. To the best of our knowledge, ℂonvoSense is the first of its kind to provide such a multitude of novel inferences at such a large scale.

The behavior economy: The creation of behavior as an object of online surveillance

While it’s well known that behavior is the target of systems of online surveillance, explanations of what behavior actually is are much harder to come by. This article provides a brief account of behavior’s twentieth century appearance and journey to a position of centrality in common-sense understandings of who we are. Given that traditional understandings of the right to privacy and self-determination are founded on a liberal humanist understanding of the subject, dominant critiques of online surveillance are seriously compromised by the fact that behavior cannot, strictly speaking, be accommodated within this intellectual framework.

Overview of knowledge reasoning for knowledge graph

Knowledge graphs are large-scale semantic networks that considerably impact knowledge representation. Mining hidden knowledge from existing data, including triplet knowledge reasoning, is a primary objective of knowledge graphs. With the development of Neural Network (NN) and Deep Learning (DL), the interpretability of triplet knowledge reasoning gradually decreases; furthermore, what machines learn is not actual reasoning but digital reasoning shortcuts. To solve this problem, more background knowledge needs to be introduced into knowledge graphs: causal graphs can offer valuable causal logic knowledge for reasoning; temporal quadruples can provide essential temporal distribution details; and commonsense graphs can furnish pertinent commonsense understanding to support reasoning. In recent years, many scholars have incorporated additional background knowledge into knowledge graphs to construct more complex reasoning mechanisms. This paper reviews the basic concepts and definitions of knowledge reasoning and the reasoning methods used for knowledge graphs. Specifically, we dissect the reasoning methods into four categories: triplet reasoning, causal inference, temporal inference, and commonsense reasoning. Finally, we discuss the remaining challenges and research opportunities related to knowledge graph reasoning.

Can Robots Be Smarter than Human Beings?

The rapid advancements in artificial intelligence (AI) and robotics have fuelled speculation about the possibility of machines surpassing human intelligence. This abstract explores the question of whether robots can become smarter than human beings. By analyzing the capabilities of contemporary AI technologies and understanding the fundamental characteristics of human intelligence, we assess the potential for machines to outpace human cognitive abilities. To address this question, we examine the current state of AI development, including machine learning, deep learning, and neural networks. We discuss how these technologies enable robots to process vast amounts of data, learn from it, and make autonomous decisions. Additionally, we explore the concept of "general intelligence" and its significance in comparing human intelligence to AI. While machines excel in narrow domains and specific tasks, achieving true human-like general intelligence remains an ongoing challenge. Furthermore, the abstract delves into the unique aspects of human intelligence that set it apart from current AI capabilities. Human cognition encompasses various complex abilities such as creativity, emotional intelligence, moral reasoning, and common sense understanding, which have proven difficult to replicate in machines. We examine the limitations and challenges faced by AI in these areas and explore the philosophical and ethical implications of creating machines that surpass human cognitive capacities. Ultimately, the abstract concludes that while robots have shown remarkable progress in specific domains, surpassing human intelligence in its entirety is a complex and elusive goal. Human intelligence encompasses a multitude of intricacies that extend beyond pure computational power. However, the abstract acknowledges the potential for future advancements in AI and robotics to challenge the boundaries of human cognitive abilities, warranting continued research and thoughtful consideration of their societal impact.

Youth, Pornography, and Addiction: A Critical Review

Abstract Purpose of Review In this article, we dig more deeply into the assumptions underpinning common-sense understandings about youth “exposure” to pornography and the ostensible “effects” of this exposure, specifically “pornography addiction”. We trace the emergence of the notion of “pornography addiction”, highlighting how cultural conditions have allowed for its realisation as a socially recognisable and intelligible narrative. Recent Findings Media effects research on the issue of youth “exposure” to pornography is not conclusive, nor is pornography addiction officially recognised as a diagnosable disorder. Moreover, an emerging body of multidisciplinary qualitative research, which, importantly, includes the perspectives and experiences of young people themselves, raises questions about some of the assumptions and conclusions of effects-focused research. Summary Despite inconclusive and contrasting findings, the social narrative of pornography addiction persists both within and beyond academe. We make sense of this persistence in relation to the broader problematisation of youth sexuality, which includes unease and moral objection to young people viewing pornography. It is important to recognise the broader socio-cultural systems supporting the cultural narrative of pornography addiction, and the social functions that this narrative serves, that is, the need for adult intervention into the sexual lives of youth.

Group differences and factors influencing obesity -- based on CFPS2020 data analysis

To understand the current status of obesity prevalence among Chinese adults and to target high-risk groups for obesity, in order to provide guidance for obesity prevention and intervention. The required data were extracted from the China Family Panel Studies 2020 (CFPS 2020) and statistically processed using SPSS 29.0 statistical software. Group differences in obesity were tested using Mann-Whitney U test for ranking variables and the chi-square test for dichotomous variables. The test of factors influencing obesity was performed using multifactorial logistic regression. In the study sample of 2613 cases, the percentage of obesity was 32.57%. The innovation of this paper is the use of the most recent data, the CFPS2020 database has not been used to do a study before. In addition, another novelty of this study is the discovery of the current influence of obesity on the internet usage, in addition to gender, which is a common sense understanding of obesity. New findings were also made on how different incomes and different marital status affect the prevalence of obesity. The prevalence of obesity was statistically significant in the group distribution across gender (P<0.001), age (P<0.001), current marital status (P<0.001), internet usage (P<0.001), and annual income from work (P<0.001). Accurate and effective obesity interventions should: (1) Adapt health and fitness programs to address different metabolic, hormonal, and social influences on diet and exercise for men and women. (2) Provide affordable or subsidized weight management programs for low-income groups to ensure that low-income groups can participate. (3) Implement nutrition counseling and fitness programs for couples or families to create a supportive environment that recognizes the impact of marital status on eating and activity habits.

‘Publicness of education’: framing possibilities for decolonising practices in Health and Physical Education

ABSTRACT Calls have been made for a public pedagogy that works at the intersection of education and politics to enact a concern for publicness. These are calls for pedagogy that values plurality in human togetherness and educational conditions in which all young people can flourish. In this paper my specific focus is exploring how publicness of education can be conceived in relation to encouraging inclusive, equitable and decolonial ‘ways of being doing and knowing' in HPE. I adopt a genealogical approach to explore ‘conditions of possibility' that have contributed to durability of a ‘white' Eurocentric norm for HPE. Selected reports, curriculum documents, newspaper and reference articles are drawn on to illuminate discourses, and power relations implicated in this dominant framing. This paper represents an attempt to disrupt common sense understandings and practices of HPE founded settler-colonialism and new forms of neo-liberal colonialism. Approaches premised on activist, culturally responsive pedagogies as well as affective, embodied, relational dimensions of human togetherness are suggested. I propose that questioning ‘why' ‘how' and ‘what' is taught in HPE is critical for reframing ‘thinking and feeling’ required for pedagogical and curricular practices that can enhance educational justice for Indigenous students.

Story Shaping: Teaching Agents Human-Like Behavior with Stories

Reward design for reinforcement learning agents can be difficult in situations where one not only wants the agent to achieve some effect in the world but where one also cares about how that effect is achieved. For example, we might wish for an agent to adhere to a tacit understanding of commonsense, align itself to a preference for how to behave for purposes of safety, or taking on a particular role in an interactive game. Storytelling is a mode for communicating tacit procedural knowledge. We introduce a technique, Story Shaping, in which a reinforcement learning agent infers tacit knowledge from an exemplar story of how to accomplish a task and intrinsically rewards itself for performing actions that make its current environment adhere to that of the inferred story world. Specifically, Story Shaping infers a knowledge graph representation of the world state from observations, and also infers a knowledge graph from the exemplar story. An intrinsic reward is generated based on the similarity between the agent's inferred world state graph and the inferred story world graph. We conducted experiments in text-based games requiring commonsense reasoning and shaping the behaviors of agents as virtual game characters.

سر سید احمد خان کے تفسیری اصول اور ان کا اطلاق:تفسیر القرآن کا خصوصی مطالعہ

Sir Sayyad Ahmad explores that commandment of Allah Almighty is never against human common-sense understanding. Hence, Sir Sayyad in his Tafsīr Al-Qurʻān follows following principles. God (Allah Almighty) is real and true, and the Holy Qurʻān is the authentic book of Allah Almighty. Everything described in Holy Qurʻān is based on reality and nobody can refuse authenticity of Holy Qurʻān. Sir Sayyad called work of nature as laws of nature and Word of God as Holy Qurʻān. He enforces that both work of nature (Nature's Laws) and Word of Nature (Holy Qurʻān) runs parallel and can't be different. Laws of nature and the Holy Qurʻān can never be against each other. Principle of universal truth is followed. Man has been created to worship God. We can say that Religion has been blessed to man. This highlights the importance of "Man's Wisdom”. Hence man has been named as best of all creatures (Ashraf al-Makhlūqāt). Sir Sayyad further explores that there is nothing in the Holy Qurʻān against principles of nature. Holy Qurʻān is complete and it is commandment of Allah Almighty full of reality and truth. However, interpretation of revelation (Wahī) is necessary for understanding. Sir Sayyad enriched his Tafsīr al-Qurʻān with requirements of modern thinking, theology and scientific facts. Hence, he describes his point of views to mold Tafsīr into scientific Tafsīr.

Relational legal consciousness in the punitive welfare state: How Dutch welfare officials shape clients' perceptions of law

AbstractWith a growing number of strict obligations and harsh sanctions for welfare recipients, the Netherlands has increasingly become a punitive welfare state. This article looks at what this means for welfare clients and their commonsense understandings of the law. To analyze how welfare officials shape clients' legal consciousness, I draw on an online survey among Dutch welfare clients (N = 1305) and a correlation analysis. The findings show that there is a clear relationship between welfare clients' own legal consciousness and their assessment of welfare officials' beliefs about the law. However, not all elements of their legal consciousness are relationally influenced by the same factors. Also, clients' self-reported compliance behavior is less relationally influenced than other elements of their legal consciousness. This study adds to our understanding of the mechanisms that constitute the production of relational and second-order legal consciousness and it contributes to the development of new research methods to study people's perceptions of law.

Common sense and the difference between natural and human sciences

ABSTRACT This article proposes a new account of the relation between the sciences and common sense. A debate between Alfred North Whitehead and Arthur S. Eddington highlighted both the tendency of the natural sciences to repudiate commonsense conceptions of the world and the greater closeness of the human sciences to common sense. While analytic writers have mostly regarded these features as self-evident, I offer an explanation of them by appealing to Wilhelm Dilthey and the phenomenological tradition. Dilthey suggested that, whereas the natural sciences could individuate their phenomena purely from empirical data, human sciences were compelled to refer to commonsense understanding in order to individuate mental phenomena. I apply this insight to episodes from the history of science, and use it to contrast the work of Alfred Schutz and Carl G. Hempel in philosophy of social and natural science. In the final section, I argue that Dilthey’s framework also offers resources to challenge present-day reductionism about mental phenomena.

CRIC: A VQA Dataset for Compositional Reasoning on Vision and Commonsense.

Alternatively inferring on the visual facts and commonsense is fundamental for an advanced visual question answering (VQA) system. This ability requires models to go beyond the literal understanding of commonsense. The system should not just treat objects as the entrance to query background knowledge, but fully ground commonsense to the visual world and imagine the possible relationships between objects, e.g., "fork, can lift, food". To comprehensively evaluate such abilities, we propose a VQA benchmark, Compositional Reasoning on vIsion and Commonsense(CRIC), which introduces new types of questions about CRIC, and an evaluation metric integrating the correctness of answering and commonsense grounding. To collect such questions and rich additional annotations to support the metric, we also propose an automatic algorithm to generate question samples from the scene graph associated with the images and the relevant knowledge graph. We further analyze several representative types of VQA models on the CRIC dataset. Experimental results show that grounding the commonsense to the image region and joint reasoning on vision and commonsense are still challenging for current approaches. The dataset is available at https://cricvqa.github.io.

Mechanical Choices: A Compatibilist Libertarian Response

Michael S. Moore defends the ideas of free will and responsibility, especially in relation to criminal law, against several challenges from neuroscience. I agree with Moore that morality and the law presuppose a commonsense understanding of humans as rational agents, who make choices and act for reasons, and that to defend moral and legal responsibility, we must show that this commonsense understanding remains viable. Unlike Moore, however, I do not think that classical compatibilism, which is based on a conditional understanding of the ability to do otherwise, provides a sufficiently robust account of free will, even when it is amended as Moore suggests. I argue that free will and responsibility can be defended more robustly by observing that, at the level of agency, there can be alternative possibilities and mental causation in a stronger sense than recognized by classical compatibilism, even if physical determinism is true. Moore’s arguments could thus be strengthened by embracing this compatibilist libertarian position. At the same time, I note that, although the idea of responsibility is robustly defensible, there are independent reasons for rejecting a retributivist approach to punishment.

Talking about the experiences of racism: A study of reporting racism in broadcast interviews.

This study examines how experiences of racism are talked about during broadcast interviews. Inspired by discursive-psychological and conversation-analytic investigations on experience in interactions, this study approaches experience as a 'loose term' and as a participant's issue in the unfolding sequence of talks. The analysis documents a range of interactional moments wherein experiences are invoked and negotiated over the course of reporting racism in the interviews. The findings align with the existing discursive-psychological and conversation-analytic research on experiences, and provide further evidence on how speakers jointly orient to and manage the issues of who knows and owns an experience, and has the premier authority to claim an experience, in relation to reporting racism. The analysis unveils the intricacy of inquiring and talking about a victim's experience of racism. People's (use of) common sense understanding of the detrimental nature of racism is met and complicated by an orientation to our unlevelled access to an experience of racism, which is a category-based societal problem.

Degrowth and International Law: Assessing the Compatibility of Degrowth and the Principle of Sustainable Development

This article explores whether the international law principle of sustainable development is compatible with the degrowth development framework. Sustainable development is a guiding and binding principle of international law which calls for development that meets the needs of the current generation without compromising the ability of future generations to meet their own needs. This article is grounded in the international law principle of sustainable development because of the significant position it occupies in international law as a guiding principle of the United Nations. Degrowth calls for the intentional downscaling of production and consumption at all levels to bring human activity back within planetary boundaries while securing decent levels of human well-being. It challenges the common-sense understanding that economic growth is an indispensable part of development and instead relies on policies which redistribute already existing wealth to fund social development projects. An approach to social concerns in this way ensures that less environmental capital is needed to develop States. This article takes a broad approach to sustainable development and degrowth and argues that they are complementary because they share the same base, namely the intersection between economic development, social development, and environmental protection. This article ultimately concludes that the principle of sustainable development is compatible with and is most purely manifested within a degrowth framework.

The Ability of an English Language Model to Understand of World Knowledge with Backshift

This study evaluated whether an English language models using artificial intelligence represent world knowledge, focusing on the backshift phenomenon. Backshift refers to the past tense being used in indirect speech, with direct speech being in the present tense. This study argued that language models capture grammatical phenomena that interact with world knowledge and can represent knowledge beyond mere grammatical knowledge. This study used BERT and mBERT models to measure the surprisals of verbs in indirect speech. Surprisal is a measurement that increase in proportion to the difficulty of language processing. Experimental results demonstrated that BERT and mBERT models were sensitive to the backshift phenomenon, revealing that the artificial intelligence language model captured backshift in indirect speech. As backshift requires an understanding of truth, knowledge, and commonsense, these results indicated that the language model understood world knowledge. (Korea University).

From Charitable Inference to Active Credence

Young children routinely display a naturalistic understanding of the world. When asked for explanations, they rarely invoke supernatural or religious explanations even when confronted by puzzling or unexpected phenomena. Nevertheless, depending on the surrounding culture, children are eventually prone to accept God as a creator, to believe in the power of prayer and to expect there to be an afterlife. A plausible interpretation of this dual stance is that children adopt two different cognitive routes to understanding: one grounded in empirical observation and in trusted testimony about the observable world. Based on this route, children gradually build up a common-sense understanding of various natural domains, including the physical, the biological and the psychological. The second route is grounded in children’s early emerging ability to engage in shared pretense. As members of a religious community, children will routinely observe community members engage in activities, such as prayer, which cannot be readily understood in terms of their standard, common-sense framework. Nevertheless, children can charitably interpret prayer as special form of communication, directed at an imagined interlocutor. Cumulative exposure to such belief-based activities is likely to encourage children to transition from charitable interpreters of religious activities to participant believers.

Encountering the Civil Sphere Through Cinema: The Cinematic Gap as a Pathway to Civil Evaluation and Repair

Despite being one of the most influential forms of media, cinema has yet to be theorized as a communicative institution of the civil sphere. Contrary to commonsense understandings of cinema as a medium for purifying representations of civil sphere ideals, this paper proposes a theoretical framework that opens up the black box of cinematic performance and theorizes processes of civil interpretation and evaluation: the cinematic gap. The cinematic gap describes an experiential space afforded by the medium’s fictional nature. Because cinema is ‘just fiction’, viewers are distanced from the ‘real civil sphere’ and permitted a space for thoughtful rumination on a cinematic performance’s presentation of civil sphere matters that is less reductive, more thoughtful, and more empathetic. As viewers can then apply these insights on the real civil sphere, the cinematic gap provides a space for thoughtful civil engagement and pathways to civil repair. This paper also identifies components of the cinematic gap which determine its ‘size’ – i.e., degree of distancing from the real civil sphere – as genre treatment and grounding in social reality. This theory is generated from responses to the 2019 Korean film Parasite, a highly successful black comedy-thriller that deploys and subverts commentary on class inequality.