Asking Questions the Human Way: Scalable Question-Answer Generation from Text Corpus

The ability to ask questions is important in both human and machine intelligence. Learning to ask questions helps knowledge acquisition, improves question-answering and machine reading comprehension tasks, and helps a chatbot to keep the conversation flowing with a human. Existing question generation models are ineffective at generating a large amount of high-quality question-answer pairs from unstructured text, since given an answer and an input passage, question generation is inherently a one-to-many mapping. In this paper, we propose Answer-Clue-Style-aware Question Generation (ACS-QG), which aims at automatically generating high-quality and diverse question-answer pairs from unlabeled text corpus at scale by imitating the way a human asks questions. Our system consists of: i) an information extractor, which samples from the text multiple types of assistive information to guide question generation; ii) neural question generators, which generate diverse and controllable questions, leveraging the extracted assistive information; and iii) a neural quality controller, which removes low-quality generated data based on text entailment. We compare our question generation models with existing approaches and resort to voluntary human evaluation to assess the quality of the generated question-answer pairs. The evaluation results suggest that our system dramatically outperforms state-of-the-art neural question generation models in terms of the generation quality, while being scalable in the meantime. With models trained on a relatively smaller amount of data, we can generate 2.8 million quality-assured question-answer pairs from a million sentences found in Wikipedia.Comment: Accepted by The Web Conference 2020 (WWW 2020) as full paper (oral presentation

Improving Asynchronous Interview Interaction with Follow-up Question Generation

The user experience of an asynchronous video interview system, conventionally is not reciprocal or conversational. Interview applicants expect that, like a typical face-to-face interview, they are innate and coherent. We posit that the planned adoption of limited probing through follow-up questions is an important step towards improving the interaction. We propose a follow-up question generation model (followQG) capable of generating relevant and diverse follow-up questions based on the previously asked questions, and their answers. We implement a 3D virtual interviewing system, Maya, with capability of follow-up question generation. Existing asynchronous interviewing systems are not dynamic with scripted and repetitive questions. In comparison, Maya responds with relevant follow-up questions, a largely unexplored feature of irtual interview systems. We take advantage of the implicit knowledge from deep pre-trained language models to generate rich and varied natural language follow-up questions. Empirical results suggest that followQG generates questions that humans rate as high quality, achieving 77% relevance. A comparison with strong baselines of neural network and rule-based systems show that it produces better quality questions. The corpus used for fine-tuning is made publicly available

An examination of strategic leadership in a dynamic context: The case of the German automobile manufacturer, BMW

BMW was first founded in 1916 and has more than 100 years of history within the global automotive industry (Lechner, 2020). There have been many events that have presented the business with extraordinary challenges (Krüger, 2019), but the current challenges BMW face are different. Following an extensive period of prosperous development and flourishing commercial success, the business is fundamentally redefining BMW (Zetsche, 2019). Simultaneously, many changes are occurring from substantial application of new technologies to innovative competitors, investments for electrification of the cars, sustainability policies, and changing consumer preferences are forcing BMW to reconsider their business models and leadership approaches (Cornet et al., 2019; Donkin, Binvel, & Stemmler, 2016; Krüger, 2019; Mohr et al., 2013; Telang, 2018; Zetsche, 2019). It is essential to understand required adjustments to the traditional approach to leadership at BMW, which has its origin in a more command-and-control mentality. Now the role of senior executives has become a substantial critical success factor in the organisational transformation (Greer & Carter, 2013 Becker, 2019; Cornet et al., 2019). The apparent research question raised is how do BMW senior executives experience this unprecedented and challenging situation and choose to perform their role accordingly. This study examines strategic leadership by illuminating relevant contextual relationships which influence leaders’ actions within a specific context. The research offers a novel approach to studying leadership practice by employing a single case study drawing upon the philosophy of pragmatism. The attention is towards the description of the complexity and contextuality rather than decreasing or disconnecting it. By conducting eighteen interviews with BMW senior executives and nine interviews with external consultants the study captures multiple voices and perspectives. The examination provides a comprehensive and detailed description of the occurring problem and accordingly what practical solution can be applied. In this regard the recognition and conceptualisation of context and its dependencies have not been an essential part of most leadership research (Fairhurst, 2009; Iszatt-White, 2011; Johns, 2001, 2006; Oc, 2018; Porter & McLaughlin, 2006). Nevertheless, the focus on leadership in a specific context provides an advantageous insight into the leadership practice—because leadership and its effectiveness are in large part dependent upon the context (Osborn, Hunt & Jauch, 2002; Moir, 2018; Poser, 2017; Wang, 2018). The study shows how senior executives perceive the specific dynamic context within the changing automotive industry. The conclusion of the examination is that the senior executives consider the current business changes and employ a combination of ambidexterity and meaningful action towards an envisioned outcome. The examination of the strategic leadership shows that an approach to leadership in the dynamic context comprises of an application of this ambidextrous attitude. This approach deals with the critical organisational and business-related legacies and simultaneously implement a new way to lead—which copes with the dynamic changes in the industry