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Intelligent assistants that follow commands or answer simple questions, such as Siri and Google search, are among the most economically important applications of AI. Future conversational AI assistants promise even greater capabilities and…
Document Question Answering (DocQA) focuses on answering questions grounded in given documents, yet existing DocQA agents lack effective tool utilization and largely rely on closed-source models. In this work, we introduce DocDancer, an…
The financial services industry perpetually processes an overwhelming amount of complex data. Digital reports are often created based on tedious manual analysis as well as visualization of the underlying trends and characteristics of data.…
Artificial Intelligence (AI) faces persistent challenges in terms of transparency and accountability, which requires rigorous documentation. Through a literature review on documentation practices, we provide an overview of prevailing…
The development of Natural Language Generation models has led to the creation of powerful Artificial Intelligence-assisted writing tools. These tools are capable of predicting users' needs and actively providing suggestions as they write.…
The rise of large language models (LLMs) has accelerated the development of automated techniques and tools for supporting various software engineering tasks, e.g., program understanding, code generation, software testing, and program…
AI for supporting designers needs to be rethought. It should aim to cooperate, not automate, by supporting and leveraging the creativity and problem-solving of designers. The challenge for such AI is how to infer designers' goals and then…
This article presents earlier results of our research works in the area of modeling Business Intelligence Systems. The basic idea of this research area is presented first. We then show the necessity of including certain users' parameters in…
Large Language Models (LLMs) enable a future in which certain types of legal documents may be generated automatically. This has a great potential to streamline legal processes, lower the cost of legal services, and dramatically increase…
Organizations handling sensitive documents face a critical dilemma: adopt cloud-based AI systems that offer powerful question-answering capabilities but compromise data privacy, or maintain local processing that ensures security but…
We introduce a general-purpose, human-in-the-loop dual dialogue system to support mental health care professionals. The system, co-designed with care providers, is conceptualized to assist them in interacting with care seekers rather than…
The increasing integration of AI-powered tools into expert workflows, such as medicine, law, and finance, raises a critical question: how does AI involvement influence a user's trust in the human expert, the AI system, and their…
Despite the increasing presence of AI assistants in Integrated Development Environments (IDEs), it remains unclear what different groups of developers actually need from these tools and which features are likely to be implemented in…
This study investigates the impact of Large Language Models (LLMs) generating follow-up questions in response to user requests for short (1-page) text documents. Users interacted with a novel web-based AI system designed to ask follow-up…
As the capabilities of Large Language Models (LLMs) expand, more researchers are studying their adoption in newsrooms. However, much of the research focus remains broad and does not address the specific technical needs of investigative…
Data storytelling plays an important role in data workers' daily jobs since it boosts team collaboration and public communication. However, to make an appealing data story, data workers spend tremendous efforts on various tasks, including…
As software engineering moves toward SE3.0, AI agents are increasingly used to carry out development tasks and contribute changes to software projects. It is therefore important to understand the extent of these contributions and how human…
Despite widespread interests in reinforcement-learning for task-oriented dialogue systems, several obstacles can frustrate research and development progress. First, reinforcement learners typically require interaction with the environment,…
Novice and expert users have different systematic preferences in task-oriented dialogues. However, whether catering to these preferences actually improves user experience and task performance remains understudied. To investigate the effects…
AI-based decision support tools (ADS) are increasingly used to augment human decision-making in high-stakes, social contexts. As public sector agencies begin to adopt ADS, it is critical that we understand workers' experiences with these…