Retrieve and Refine: Improved Sequence Generation Models For Dialogue

Sequence generation models for dialogue are known to have several problems: they tend to produce short, generic sentences that are uninformative and unengaging. Retrieval models on the other hand can surface interesting responses, but are restricted to the given retrieval set leading to erroneous replies that cannot be tuned to the specific context. In this work we develop a model that combines the two approaches to avoid both their deficiencies: first retrieve a response and then refine it -- the final sequence generator treating the retrieval as additional context. We show on the recent CONVAI2 challenge task our approach produces responses superior to both standard retrieval and generation models in human evaluations

Parent Resource Packet - A Guide for New Parents

PDF pages: 8

Science Courts, Evidentiary Procedures and Mixed Science-Policy Decisions

This paper analyzes the potential for science courts to address the social need to regulate human carcinogens and concludes that, on balance, it is not high. From this vantage point, Professor Cranor suggests desiderata for application in other areas where science courts might be used

Gender identity and breast cancer campaigns

Concerning itself with understanding how marketing methods and tools can be of benefit to healthcare professionals, health marketing is an area of research that has grown substantially in recent years. Of much interest to the sector is whether awareness campaigns are effective in increasing the public’s perceived vulnerability to any given disease

Vegetarians versus Vegans

There is a gap in literature related to studies that explicitly compare vegetarians to vegans, as existing studies typically group these diets together and examine carnivorous and omnivorous diets in order to identify similarities and differences. The purpose of this study is to look at vegetarian and vegan diets to see if differences in attitudes towards animals, perceptions of animal usage, consumption, and morality exist. Participants included vegetarian and vegan Liberty University students (graduate and undergraduate, online and residential) who were at least 18 years old. Overall, one hundred students took part in the study, 50 of them were vegetarian and 50 of them were vegan. They completed an anonymous online survey measuring demographics, attitudes towards animals, perceptions of animal usage, and morality. Overall, there was a statistically significant difference between vegans and vegetarians in attitudes toward animals as well as their perception of human and animal similarity. There was also a significant difference between one of the five domains regarding moral decision-making, the fairness/reciprocity domain. However, in the other four domains (harm/care, in-group/loyalty, authority/respect, and purity/sanctity), there was not a significant difference between the vegan and vegetarian group. Since past studies have grouped vegans and vegetarians as alike, these results seem support the importance of maintaining a separation between diets and subgroups in future studies since differences may exist between the groups

From Query to Usable Code: An Analysis of Stack Overflow Code Snippets

Enriched by natural language texts, Stack Overflow code snippets are an invaluable code-centric knowledge base of small units of source code. Besides being useful for software developers, these annotated snippets can potentially serve as the basis for automated tools that provide working code solutions to specific natural language queries. With the goal of developing automated tools with the Stack Overflow snippets and surrounding text, this paper investigates the following questions: (1) How usable are the Stack Overflow code snippets? and (2) When using text search engines for matching on the natural language questions and answers around the snippets, what percentage of the top results contain usable code snippets? A total of 3M code snippets are analyzed across four languages: C\#, Java, JavaScript, and Python. Python and JavaScript proved to be the languages for which the most code snippets are usable. Conversely, Java and C\# proved to be the languages with the lowest usability rate. Further qualitative analysis on usable Python snippets shows the characteristics of the answers that solve the original question. Finally, we use Google search to investigate the alignment of usability and the natural language annotations around code snippets, and explore how to make snippets in Stack Overflow an adequate base for future automatic program generation.Comment: 13th IEEE/ACM International Conference on Mining Software Repositories, 11 page

Deconstructing climate misinformation to identify reasoning errors

Misinformation can have significant societal consequences. For example, misinformation about climate change has confused the public and stalled support for mitigation policies. When people lack the expertise and skill to evaluate the science behind a claim, they typically rely on heuristics such as substituting judgment about something complex (i.e. climate science) with judgment about something simple (i.e. the character of people who speak about climate science) and are therefore vulnerable to misleading information. Inoculation theory offers one approach to effectively neutralize the influence of misinformation. Typically, inoculations convey resistance by providing people with information that counters misinformation. In contrast, we propose inoculating against misinformation by explaining the fallacious reasoning within misleading denialist claims. We offer a strategy based on critical thinking methods to analyse and detect poor reasoning within denialist claims. This strategy includes detailing argument structure, determining the truth of the premises, and checking for validity, hidden premises, or ambiguous language. Focusing on argument structure also facilitates the identification of reasoning fallacies by locating them in the reasoning process. Because this reason-based form of inoculation is based on general critical thinking methods, it offers the distinct advantage of being accessible to those who lack expertise in climate science. We applied this approach to 42 common denialist claims and find that they all demonstrate fallacious reasoning and fail to refute the scientific consensus regarding anthropogenic global warming. This comprehensive deconstruction and refutation of the most common denialist claims about climate change is designed to act as a resource for communicators and educators who teach climate science and/or critical thinking