相关论文: Threddy: An Interactive System for Personalized Th…
Understanding the current research trends, problems, and their innovative solutions remains a bottleneck due to the ever-increasing volume of scientific articles. In this paper, we propose NLPExplorer, a completely automatic portal for…
The number of research papers written has been growing at least linearly -- if not exponentially -- in recent years. In proportion, the amount of time a reader allocates per paper has been decreasing. While an accessible paper will be…
The present study proposes LitStoryTeller, an interactive system for visually exploring the semantic structure of a scientific article. We demonstrate how LitStoryTeller could be used to answer some of the most fundamental research…
Surveying prior literature to establish a foundation for new knowledge is essential for scholarly progress. However, survey articles are resource-intensive and challenging to create, and can quickly become outdated as new research is…
As the volume of published scholarly literature continues to grow, finding relevant literature becomes increasingly difficult. With the rise of generative Artificial Intelligence (AI), and particularly Large Language Models (LLMs), new…
The rapidly expanding corpus of medical research literature presents major challenges in the understanding of previous work, the extraction of maximum information from collected data, and the identification of promising research directions.…
We propose an automated pipeline for performing literature reviews using semantic similarity. Unlike traditional systematic review systems or optimization based methods, this work emphasizes minimal overhead and high relevance by using…
Scientific digital libraries play a critical role in the development and dissemination of scientific literature. Despite dedicated search engines, retrieving relevant publications from the ever-growing body of scientific literature remains…
Autonomous scientific discovery with large language model (LLM)-based agents has recently made substantial progress, demonstrating the ability to automate end-to-end research workflows. However, existing systems largely rely on…
Search engines leverage knowledge to improve information access. In order to effectively leverage knowledge, search engines should account for context, i.e., information about the user and query. In this thesis, we aim to support search…
While Large Language Models (LLMs) have shown significant potential in assisting peer review, current methods often struggle to generate thorough and insightful reviews while maintaining efficiency. In this paper, we propose TreeReview, a…
Scientific research is highly structured and some of that structure is reflected in research reports. Traditional scientific research reports are yielding to interactive documents which expose their internal structure and are richly linked…
Conversational interfaces are likely to become more efficient, intuitive and engaging way for human-computer interaction than today's text or touch-based interfaces. Current research efforts concerning conversational interfaces focus…
Systematic scientometric reviews, empowered by scientometric and visual analytic techniques, offer opportunities to improve the timeliness, accessibility, and reproducibility of conventional systematic reviews. While increasingly accessible…
Literature reviews are essential for any researcher trying to keep up to date with the burgeoning software engineering literature. FAST$^2$ is a novel tool for reducing the effort required for conducting literature reviews by assisting the…
The process of conducting literature reviews is often time-consuming and labor-intensive. To streamline this process, I present an AI Literature Review Suite that integrates several functionalities to provide a comprehensive literature…
The constantly increasing rate at which scientific papers are published makes it difficult for researchers to identify papers that currently impact the research field of their interest. Hence, approaches to effectively identify papers of…
We present a novel system providing summaries for Computer Science publications. Through a qualitative user study, we identified the most valuable scenarios for discovery, exploration and understanding of scientific documents. Based on…
Purpose: Finding scholarly articles is a time-consuming and cumbersome activity, yet crucial for conducting science. Due to the growing number of scholarly articles, new scholarly search systems are needed to effectively assist researchers…
Researchers usually come up with new ideas only after thoroughly comprehending vast quantities of literature. The difficulty of this procedure is exacerbated by the fact that the number of academic publications is growing exponentially. In…