14 papers · ranked by Valyu relevance
Quanzhi Fu, Qiyu Wu, Dan Williams
With the significant increase in enrollment in computing-related programs over the past 20 years, lecture sizes have grown correspondingly. In large lectures, instructors face challenges on identifying students' knowledge gaps timely, which is critical for effective teaching. Existing classroom response systems rely on…
Salem, Nourah M, White, Elizabeth + 4 more
Scientific progress is driven by the deliberate articulation of what remains unknown. This study investigates the ability of large language models (LLMs) to identify research knowledge gaps in the biomedical literature. We define two categories of knowledge gaps: explicit gaps, clear declarations of missing knowledge…
Yujing Wang, Yuanbang Liang, Yukun Lai, Hainan Zhang + 1 more
Detecting whether a model's internal knowledge is sufficient to correctly answer a given question is a fundamental challenge in deploying responsible LLMs. In addition to verbalising the confidence by LLM self-report, more recent methods explore the model internals, such as the hidden states of the response tokens to…
Luisa Frede, Lisa Bardach, Younes Strittmatter, Eileen Richter + 2 more
Knowledge gaps elicit curiosity and increase people’s willingness to invest resources in seeking information to close them. While previous research used confidence ratings to implicitly infer knowledge gaps, the impact of making these gaps explicitly salient to people on their information-seeking behavior remains…
Yuxin Liu, Chaojie Gu, Yihang Zhang, Qian + 2 more
Large Language Models (LLMs) have demonstrated remarkable capabilities in various reasoning tasks, yet they often struggle with problems involving missing information, exhibiting issues such as incomplete responses, factual errors, and hallucinations. While forward reasoning approaches like Chain-of-Thought (CoT) [1]…
Sruti Mallik, Ahana Gangopadhyay
The education sector has benefited enormously through integrating digital technology driven tools and platforms. In recent years, artificial intelligence based methods are being considered as the next generation of technology that can enhance the experience of education for students, teachers, and administrative staff…
Christopher A. Was
accuracy Authors: ['Christopher A. Was'] Knowledge monitoring predicts academic outcomes in many contexts. However, measures of knowledge monitoring accuracy are often incomplete. In the current study, a measure of students’ ability to discriminate known from unknown information as a component of knowledge monitoring…
Lasse Osterhagen, K. Jannis Hildebrandt
Age-related hearing loss (presbycusis) is caused by damage to the periphery as well as deterioration of central auditory processing. Gap detection is a paradigm to study age-related temporal processing deficits, which is assumed to be determined primarily by the latter. However, peripheral hearing loss is a strong…
Arun Sharma, Shashi Shekhar
Given trajectories with gaps (i.e., missing data), we investigate algorithms to identify abnormal gaps in trajectories which occur when a given moving object did not report its location, but other moving objects in the same geographic region periodically did. The problem is important due to its societal applications…
Alexa Booras, Tanner Stevenson, Connor N. McCormack, Marie E. Rhoads + 1 more
In order to behave appropriately in a rapidly changing world, individuals must be able to detect when changes occur in that environment. However, at any given moment, there are a multitude of potential changes of behavioral significance that could occur. Here we investigate how knowledge about the space of possible…
Mohamed Reda Bouadjenek, Karin Verspoor, Justin Zobel
We investigate and analyse the data quality of nucleotide sequence databases with the objective of automatic detection of data anomalies and suspicious records. Specifically, we demonstrate that the published literature associated with each data record can be used to automatically evaluate its quality, by…
Oleg Solozobov
Machine learning systems in fraud detection, credit scoring, and clinical risk assessment operate under delayed ground truth: outcome labels arrive days to months after the decision they evaluate. During this blind period, governance evidence degrades through mechanisms that neither drift detection methods nor…
Galadriel Brière, Thomas Stosskopf, Benjamin Loire, Anaïs Baudot
In recent years, Knowledge Graphs (KGs) have gained significant attention for their ability to organize complex biomedical knowledge into entities and relationships. Knowledge Graph Embedding (KGE) models facilitate efficient exploration of KGs by learning compact data representations. These models are increasingly…
Marianna Massimilla Rusche, Matthias Ziegler
Along with crystallized intelligence (Gc), domain-specific knowledge (Gkn) is an important ability within the nomological net of acquired knowledge. Although Gkn has been shown to predict important life outcomes, only a few standardized tests measuring Gkn exist, especially for the adult population. Complicating…