We blend neuroscience, information retrieval, and responsible AI to build human-centred search experiences. Click a card to explore the projects anchoring each workstream and meet the researchers leading them.
Integrates psychological and neuroscientific approaches to understand how people seek information across traditional and contemporary IR systems, with a focus on equitable access for underserved communities.
Builds machine learning systems that translate neurophysiological signals into adaptive human-computer interaction and information retrieval experiences.
Audits modern AI pipelines—from LLMs to neurophysiological analytics—to surface and mitigate bias, risk, and privacy harms.
Explore the latest outputs from our lab, spanning bias auditing, retrieval, and responsible AI. We share artefacts so collaborators can dive deeper into each study.
Modelling dynamically evolving spatio-temporal signals is a prominent challenge in the Graph Neural Network (GNN) literature. Notably, GNNs assume an existing underlying graph structure. While this underlying structure may not...
Political bias in Large Language Models (LLMs) presents a growing concern for the responsible deployment of AI systems. Traditional audits often attempt to locate a model s political position as...
Exploring the variations in browsing and dwell time behaviours in web pages among users with different levels of attention
Although cognitive metrics like attention significantly influence user interaction with digital environments, their role in web search behaviour remains underexplored. This study employs a multidimensional attention framework to investigate the...
Zollner, Malin ORCID logo ORCID: https: orcid. org 0009-0000-9662-0869, Moshfeghi, Yashar ORCID logo ORCID: https: orcid. org 0000-0003-4186-1088 and Nematiaram, Tahereh ORCID logo ORCID: https: orcid. org 0000-0002-0371-4047;
Information Retrieval (IR) systems primarily rely on users ability to translate their internal information needs into (text) queries. However, this translation process is often uncertain and cognitively demanding, leading to...
The fundamental goal of Information Retrieval (IR) systems lies in their capacity to effectively satisfy human information needs - a challenge that encompasses not just the technical delivery of information,...
Conversational AI systems, powered by advanced Large Language Models, have rapidly developed human-like persuasion capabilities that raise concerns about psychological manipulation. This provocation examines the ethical problems that arise when...
Impact of Dataset Diversity on Machine Learning Prediction of Reorganisation Energies in Organic Semiconductors
This work investigates how input characteristics, particularly dataset diversity, affect the performance of machine learning algorithms in predicting hole and electron reorganisation energies, ultimately aiding the identification of promising organic...
The International Workshop on NeuroPhysiological Approaches for Interactive Information Retrieval (NeuroPhysIIR 25), co-located with ACM SIGIR CHIIR 2025 in Naarm Melbourne, Australia, included 19 participants who discussed 12 statements addressing...
Engineering Safe and Trustworthy AI: The Participatory Harm Auditing Workbenches and Methodologies (PHAWM) Project
Artificial intelligence (AI) is increasingly being used in many applications, yet systematic engineering approaches to make them safe and trustworthy are lagging behind. Recent regulations, such as the EU AI...
Graph neural networks have re-defined how we model and predict on network data but there lacks a consensus on choosing the correct underlying graph structure on which to model signals....
Human error remains a critical concern in aviation safety, contributing to 70-80% of accidents despite technological advancements. While physiological measures show promise for error detection in laboratory settings, their effectiveness...
EEG subject detection: opportunity or threat?
Brain-computer interfaces (BCI) leverage neurophysiological features like Electroencephalography (EEG) to enhance user-computer interaction. EEG s high temporal resolution and unobtrusiveness make it ideal for BCI systems, facilitating real-time interaction with...
The International Workshop on NeuroPhysiological Approaches for Interactive Information Retrieval (NeuroPhysIIR’25) aims to bringing together researchers from information science, human-computer interaction, cognitive neuroscience, and related fields, to foster cross-disciplinary collaboration...
Web search, as a primary tool for accessing a vast amount of data, plays a crucial role in information retrieval. This study aims to compare the level of sustained attention...
Neurophysiological Approaches for Understanding Information Seeking
Humans undertake information locating and consuming behavior continuously and rely on it as a mechanism for survival, socialization, and self-development. Infor-mation locating and consuming, collectively referred to as information seeking,...
We introduce a novel framework that integrates Hodge decomposition with Filtered Average Short-Term (FAST) functional connectivity to analyze dynamic functional connectivity (DFC) in EEG signals. This method leverages graph-based topology...
Neuroanatomical correlates and predictors of psychotic symptoms in Alzheimer s disease: A systematic review and meta-analysis (vol 204, 109006, 2024)
Brain decoding has emerged as a rapidly advancing and extensively utilized technique within neuroscience. This paper centers on the application of raw electroencephalogram (EEG) signals for decoding human brain activity,...
This research examines the congruence between neural activity and advanced transformer models, emphasizing the semantic significance of punctuation in text understanding. Utilizing an innovative approach originally proposed by Toneva and...
The rapid advancement of Artificial Intelligence has resulted in the advent of Large Language Models (LLMs) with the capacity to produce text that closely resembles human communication. These models have...
Accelerating the discovery of high-mobility molecular semiconductors: a machine learning approach
The two-dimensionality (2D) of charge transport significantly affects charge carrier mobility in organic semiconductors, making it a key target for materials discovery and design. Traditional quantum-chemical methods for calculating 2D...
Jose. 2013. Building a large-scale corpus for evaluating event detection on twitter
Designing Chatbots for Informal Learning in Museums
While several museums are already implementing AI technologies, little work has been done to advance knowledge of whether and how chatbots can support visitors’ informal learning experiences with heritage. This...
Quantification of Topic Propagation Using Percolation Theory: Page 1 Quantification of Topic Propagation Using Percolation Theory: A Study of the ICWSM Network Ali Azimi Bolourian Yashar Moshfeghi CJ “Keith” van...
Measuring transient functional connectivity is an important challenge in electroencephalogram (EEG) research. Here, the rich potential for insightful, discriminative information of brain activity offered by high-temporal resolution is confounded by...
Information retrieval systems have historically relied on explicit query formulation, requiring users to translate their information needs into text. This process is particularly disruptive during reading tasks, where users must...
Clinical Manifestations
BackgroundPsychotic symptoms (delusions and or hallucinations) are among the most common and impactful neuropsychiatric symptoms that occur within Alzheimer s disease (AD): present in around half of AD patients, they...
Background Psychotic symptoms (delusions and or hallucinations) are among the most common and impactful neuropsychiatric symptoms that occur within Alzheimer’s disease (AD): present in around half of AD patients, they...
BackgroundPsychotic symptoms (hallucinations and delusions) are a type of neuropsychiatric symptom found during Alzheimer’s Disease (AD).ObjectiveThis systematic review aims to comprehensively capture, analyse, and evaluate the body of evidence that...
Auditing Large Language Models (LLMs) to discover their biases and preferences is an emerging challenge in creating Responsible Artificial Intelligence (AI). While various methods have been proposed to elicit the...
Corrigendum to Neuroanatomical correlates and predictors of psychotic symptoms in Alzheimer s disease: A systematic review and meta-analysis
The authors regret that Table 1 was not formatted displayed correctly. In this version Table 1 has been corrected.
In recent years, much interdisciplinary research has been conducted exploring potential use cases of neuroscience to advance the field of information retrieval. Initial research concentrated on the use of fMRI...
Mental workload (MWL) assessment is crucial in information systems (IS), impacting task performance, user experience, and system effectiveness. Deep learning offers promising techniques for MWL classification using electroencephalography (EEG), which...
One of the foundational goals of Information Retrieval (IR) is to satisfy searchers Information Needs (IN). Understanding how INs physically manifest has long been a complex and elusive process. However,...
We propose a panel on neurophysiological approaches for understanding information seeking behavior.
More technology? Evaluating the effectiveness of smart thermostats
Climate change has been recognized as a significant threat for over a century, with early predictions by Svante Arrhenius in 1896 and subsequent confirmations by Guy Callendar in 1938, who...
Addressing the challenge of automated geometry math problem-solving in artificial intelligence (AI) involves understanding multi-modal information and mathematics. Current methods struggle with accurately interpreting geometry diagrams, which hinders effective problem-solving....
Assessing the stability of clusters of neuropsychiatric symptoms in Alzheimer’s disease and mild cognitive impairment
AimThe aim of the study was to investigate the factors that underpin neuropsychiatric symptoms and how they might evolve over time in people with Mild Cognitive Impairment (MCI) and Alzheimer’s...
Advances in Deep Learning have drastically improved the abilities of Natural Language Processing (NLP) research, creating new state‐of‐the‐art benchmarks. Two research streams at the forefront of NLP analysis are transformer...
Geometry problem solving presents a formidable challenge within the NLP community. Existing approaches often rely on models designed for solving math word problems, neglecting the unique characteristics of geometry math...
The realisation and the variability of information needs (IN) with respect to a searcher’s gap in knowledge is driven by the perceived Anomalous State of Knowledge (ASK). The concept of...
GeoEval: Benchmark for Evaluating LLMs and Multi-Modal Models on Geometry Problem-Solving
Background Neuropsychiatric symptoms are behavioural manifestations highly prevalent along the Alzheimer’s disease (AD) continuum, including at the stage of Mild Cognitive Impairment (MCI). Although various projects have investigated the factors...
The Electroencephalogram (EEG) provides a very high temporal resolution of brain activity. This allows for directly recording the electromagnetic activity of the brain during cognitive tasks. In theory, the EEG...
In online settings, some teachers express reservations about relying only on traditional assessments (e.g., tests, assignments, exams, etc.) as trustworthy instruments to evaluate students understanding of the content accurately. A...
Information Need (IN) is a complex phenomenon due to the difficulty experienced when realising and formulating it into a query format. This leads to a semantic gap between the IN...
The ability to determine a subject’s Mental Work Load (MWL) has a wide range of significant applications within modern working environments. In recent years, techniques such as Electroencephalography (EEG) have...
Electroencephalogram (EEG) is a non-invasive technology with high temporal resolution, widely used in Brain-Computer Interfaces (BCIs) for mental workload (MWL) classification. However, numerous EEG channels in current devices can make...
Relevance assessment, a crucial Human-computer Information Retrieval (HCIR) aspect, denotes how well retrieved information meets the user s information need (IN). Recently, user-centred research benefited from the employment of brain...
Podcasts are spoken documents that, in recent years, have gained widespread popularity. Despite the growing research interest in this domain, conducting user studies remains challenging due to the lack of...
Background Psychotic symptoms (delusions or hallucinations) are a particularly prevalent form of neuropsychiatric symptom in people with Alzheimer’s disease (AD) and Mild Cognitive Impairment (MCI). Notably, their presence has been...
Music recommender systems are an integral part of our daily life. Recent research has seen a significant effort around black-box recommender based approaches such as Deep Reinforcement Learning (DRL). These...
A growing body of interdisciplinary NeuraSearch research in the Information Retrieval (IR) domain, built on the investigations evaluating searchers’ neurophysiological activity captured during the information search interactions, advances the understanding...
Modern neural networks specialised in natural language processing (NLP) are not implemented with any explicit rules regarding language. It has been hypothesised that they might learn something generic about language....
Knowing when a searcher’s information needs (IN) are satisfied is one of the ultimate goals in information retrieval. However, the psycho-physiological manifestation of the phenomenon remains unclear. In this study,...
Relevance is a key topic in Information Retrieval (IR). It indicates how well the information retrieved by the search engine meets the user’s information need (IN). Despite research advances in...
The determination of a subject’s mental workload (MWL) from an electroencephalogram (EEG) is a well-studied area in the brain-computer interface (BCI) field. A high MWL level can significantly contribute to...
Collaborative Filtering (CF) recommendation algorithms are a popular solution to the information overload problem, aiding users in the item selection process. Relevant research has long focused on refining and improving...
Purpose With the shift to an information-based society and to the de-centralisation of information, information overload has attracted a growing interest in the computer and information science research communities. However,...
Numerical reasoning over text is a challenging task of Artificial Intelligence (AI), requiring reading comprehension and numerical reasoning abilities. Previous approaches use numerical reasoning programs to represent the reasoning process....
Knowledge loss occurs when experts leave a project or organisation, this is particularly in the form of tacit knowledge which those experts have gathered through experience. This experiential knowledge is...
In the past few years, individuals choose increasingly to share online about themselves, which reflect greatly about their personality and self-image. In particular, individuals with mental health issues tend to...
The searcher s realisation of Information Need (IN) in Information Retrieval (IR) is triggered by a perception of the knowledge gap the searcher perceives. Introspective epistemic (knowledge) feelings are evoked,...
A fundamental goal of Information Retrieval (IR) is to satisfy searchers information need (IN). Advances in neuroimaging technologies have allowed for interdisciplinary research to investigate the brain activity associated with...
Deep learning-based approaches have recently received much attention and managed to accurately capture variance characteristics in the Electroencephalography (EEG) signals. In this paper, we aim to classify the subject’s mental...
The new coronavirus disease (COVID-19) comprises the public health systems around the world. The number of infected people and deaths are escalating day-to-day, which puts enormous pressure on healthcare systems....
EgoPlan: A framework for multi-agent planning using single agent planners
Planning problems are, in general, PSPACE-complete; large problems, especially multi-agent problems with required co-ordination, can be intractable or impractical to solve. Factored planning and multi-agent planning both address this by...
Procurement or tender search is where suppliers seek opportunities for providing goods, works or services that authorities, organisations and businesses require. Such opportunities are listed as procurement contract notices for...
A high mental workload level could significantly contribute to mental fatigue, decreased performance, or long-term health problems . Recently, deep learning models have been trained on Electroencephalogram (EEG) signals to...
In this article, we propose an approach to improve quality in crowdsourcing (CS) tasks using Task Completion Time (TCT) as a source of information about the reliability of workers in...
The ability to skip songs is a core feature in modern online streaming services. Its introduction has led to a new music listening paradigm and has changed the way users...
Understanding how to satisfy searchers’ information need (IN) is the main goal of Information Retrieval (IR) systems. In this study, we investigate the relationships between information need and the two...
In a search process, searchers review documents to gather information relevant to their information need (IN). During this process, searchers may experience the satisfaction of their IN, indicating they have...
This paper describes our research groups’ efforts in tackling the mental workload (MWL) prediction task from Electroencephalogram (EEG) signals which was organised as a Passive BCI Hackathon grand challenge1 at...
This paper briefly describes our research groups’ efforts in tackling Task 1 (Early Detection of Signs of Self-Harm), and Task 2 (Measuring the Severity of the Signs of Depression) from...
Information Retrieval (IR) process is complex because it involves a gap between the representation of an Information Need (IN)(ie the formulated query) and the actual IN. This gap can become...
The podcast is a growing listening medium that has surged in popularity in recent years. Despite the great research opportunities, it has only attracted limited attention from the community so...
Mental workload (MWL) is one of the key concepts in ergonomics and human factors for understanding human performance, which can be affected by workload being too high or too low...
The design of highly complex systems such as spacecraft entails large amounts of documentation. Tracking relevant information, including hundreds of requirements, throughout several design stages is a challenge. In this...
Recommendation systems (RS) are a key component of modern commercial platforms, with Collaborative Filtering (CF) based RSs being the centrepiece. Relevant research has long focused on measuring and improving the...
The graph data structure offers a highly expressive way of representing many real-world constructs such as social networks, chemical compounds, the world wide web, street maps, etc. In essence, any...
This paper briefly describes our research groups’ efforts in tackling Task 1 (Early Detection of Signs of Self-Harm), and Task 2 (Measuring the Severity of the Signs of Depression) from...
Prior work on using retrievability measures in the evaluation of information retrieval (IR) systems has laid out the foundations for investigating the relationship between retrieval effectiveness and retrieval bias. While...
Relevance is an essential concept in Information Retrieval (IR). Recent studies using brain imaging have significantly contributed towards the understanding of this concept, but only as a binary notion, i.e....
Expert Systems, computer programs able to capture human expertise and mimic experts reasoning, can support the design of future space missions by assimilating and facilitating access to accumulated knowledge. To...
To enhance Knowledge Reuse in the field of space mission design, the implementation of Information Retrieval (IR) is key. Topic Modeling (TM) is used to identify, learn and extract topics...
Result diversification aims to provide searchers with a broader view of a given topic while attempting to maximise the chances of retrieving relevant material. Diversifying results also aims to reduce...
The main goal of information retrieval (IR) is to satisfy information need (IN). IN refers to a complex concept: at the very initial state of the phenomenon (that is, at...
Introduction to the special issue on neuro-information science.
The field of neuroscience has fruitfully contributed to a wide variety of other fields, for example, economics, marketing, and information systems, where the broad adoption and influence of neurophysiological (NP)...
Procurement legislation stipulates that information about the goods, services, or works, that tax-funded authorities wish to purchase are made publicly available in a procurement contract notice. However, for businesses wishing...
The 9th PhD Symposium on Future Directions in Information Access (FDIA) was held in conjunction with the 12th European Summer School on Information Retrieval in Milan, Italy. The symposium aims...
Many theoretical approaches in information retrieval assume that relevance is based on mutual interaction of the system and user. Past studies have mainly focused on the system side of relevance,...
The goal of Information Retrieval (IR) systems is to satisfy searchers Information Need (IN). Our research focuses on next-generation IR engines, which can proactively detect, identify, and serve INs without...
Recently, geolocalisation of tweets has become important for a wide range of real-time applications, including real-time event detection, topic detection or disaster and emergency analysis. However, the number of relevant...
Fine-grained geolocation of tweets has become an important feature for reliably performing a wide range of tasks such as real-time event detection, topic detection or disaster and emergency analysis. Recent...
Given the proliferation of social media and the abundance of news feeds, a substantial amount of real-time content is distributed through disparate sources, which makes it increasingly difficult to glean...
Search is one of the most performed activities on the World Wide Web. Various conceptual models postulate that the search process can be broken down into distinct emotional and cognitive...
Recently, the geolocalisation of tweets has become an important feature for a wide range of tasks in Information Retrieval and other domains, such as real-time event detection, topic detection or...
Improvement on assessment of air pollution exposure will enhance assessment of health risk-benefit when active travel (cycling and walking). Earlier studies assessed air pollution exposure according to travel time and...
The design and presentation of a Search Engine Results Page (SERP) has been subject to much research. With many contemporary aspects of the SERP now under scrutiny, work still remains...
As an empirical discipline, information access and retrieval research requires substantial software infrastructure to index and search large collections. This workshop is motivated by the desire to better align information...
Providing support for users during their search sessions has been hailed as a major challenge in interactive information retrieval (IIR). Providing such support requires considering the context of the search...
The workshop and hackathon on developing Information Retrieval Evaluation Resources using Lucene (L4IR) was held on the 8th and 9th of September, 2016 at the University of Strathclyde in Glasgow,...
A Study of Snippet Length and Informativeness
Interactive Information Retrieval (IIR) is a complex, non-trivial process where a searcher undertakes a variety of di erent actions during a search session [16]. Core to their experience and success...
This paper describes a novel approach to re-ranking search engine result pages (SERP): Its fundamental principle is to re-rank results to a given query, based on exploiting evidence gathered from...
In this paper we introduce a game scenario for crowdsourcing (CS) using incentives as a bait for careless (gambler) workers, who respond to them in a characteristic way. We hypothesise...
The raison d etre of IR is to satisfy human information need. But, do we really understand information need? Despite advances in the past few decades in both the IR...
Despite the ever-increasing popularity of crowdsourcing (CS) in both industry and academia, procedures that ensure quality in its results are still elusive. We hypothesise that a CS design based on...
UCUI 15: Proceedings of the ACM First International Workshop on Understanding the City with Urban Informatics
UCUI 15 : Proceedings of the ACM First International Workshop on Understanding the City with Urban Informatics - Enlighten Publications Skip to main content Accessibility information Site navigation Study Research...
UCUI 15 chairs welcome
UCUI 15 chairs welcome — University of Strathclyde Skip to main navigation Skip to search Skip to main content University of Strathclyde Home University of Strathclyde Logo Help & FAQ...
Urban Informatics aims to exploit the large quantities of information produced by modern cities in order to gain insights into how they function. These insights lay the foundation for improving...
Relevance is a central notion in Information Retrieval, but it is considered to be a difficult concept to define. We analyse brain signals for the first 800 milliseconds (ms) of...
Predicting popular content is a challenging problem for social media websites in order to encourage user interactions and activity. Existing works in this area, including the recommendation approach used by...
This paper highlights a number of problems which exist in the evaluation of existing image annotation and tag recommendation methods. Crucially, the collections used by these state-of-the-art methods contain a...
Neural Features of Video Topical Relevance Page 1 Gmunden Retreat on NeuroIS 2014 │ © NeuroIS.org 51 For over 50 years, Information Retrieval Systems (IRSs) have been helping users to...
Despite the popularity of Twitter for research, there are very few publicly available corpora, and those which are available are either too small or unsuitable for tasks such as event...
Image tagging is a growing application on social media websites, however, the performance of many auto-tagging methods are often poor. Recent work has exploited an image s context (e.g. time...
The effectiveness of various behavioural signals for implicit relevance feedback models has been exhaustively studied. Despite the advantages of such techniques for a real time information retrieval system, most of...
Emotion is considered to be an important factor in human decision making and consciousness. Due to its perceived importance, recently a number of works try to explore emotion in IR...
Microblog Ad-hoc retrieval has received much attention in recent years. As a result of the high vocabulary diversity of the publishing users, a mismatch is formed between the queries being...
The complex and dynamic nature of search processes surrounding information seeking have been exhaustively studied. Recent studies have highlighted search processes with different intentions, such as those for entertainment purposes...
Relevance is one of the key concepts in Information Retrieval (IR). A huge body of research exists that attempts to understand this concept so as to operationalize it for IR...
Nowadays, successful applications are those which contain features that captivate and engage users. Using an interactive news retrieval system as a use case, in this paper we study the effect...
This panel will discuss opportunities and challenges involved in applying cognitive neuroscience and neuroimaging in information science. The panelists will discuss lessons learned from related disciplines and will consider how...
The main objective of Information Retrieval (IR) systems is to satisfy searchers’ needs. A great deal of research has been conducted in the past to attempt to achieve a better...
The main objective of Information Retrieval (IR) systems is to satisfy searchers’ needs. A great deal of research has been conducted in the past to attempt to achieve a better...
The aim of this paper is to investigate the role of emotion features in diversifying document rankings to improve the effectiveness of Information Retrieval (IR) systems. For this purpose, two...
Collaborative filtering (CF) aims to recommend items based on prior user interaction. Despite their success, CF techniques do not handle data sparsity well, especially in the case of the cold...
As digital collections expand, the importance of the temporal aspect of information has become increasingly apparent. The aim of this paper is to investigate the effect of using long-term temporal...
The aim of this poster is to investigate the role of emotion in the collaborative filtering task. For this purpose, a kernel-based collaborative recommendation technique is used. The experiment is...
We propose an approach to build a subspace representation for documents. This more powerful representation is a first step towards the development of a quantum-based model for Information Retrieval (IR)....
Blogs facilitate online debates and discussions for millions of people around the world. Identifying the most popular and prevailing topics discussed in the Blogosphere is a crucial task. This poster...
Recommendation, retrieval and browsing techniques are used to address the information overload problem. Current stateof-the-art approaches in these domains define the relevance of documents based on their content and in...
Recommender systems have been systematically applied in industry and academia to help users cope with information uncertainty. However, given the multiplicity of the preferences and needs it has been shown...
Over the years, recommender systems have been systematically applied in both industry and academia to assist users in dealing with information overload. One of the factors that determine the performance...
In this paper, we propose a united architecture for the creation of life-long user profiles. Our architecture combines different steps required for a user prole, including feature extraction and representation,...
Blogs facilitate online debates and discussions for millions of people around the world. Identifying the most popular and prevailing topics discussed in the Blogosphere is a crucial task. This paper...
Collaborative recommender systems aim to recommend items to a user based on the information gathered from other users who have similar interests. The current state-of-the-art systems fail to consider the...
Intelligent RSS Aggregator
Intelligent rss aggregator - University of Strathclyde Skip to main navigation Skip to search Skip to main content University of Strathclyde Home University of Strathclyde Logo Help & FAQ Home...
Exploring the variations in browsing and dwell time behaviours in web pages among users with different levels of attention
Impact of Dataset Diversity on Machine Learning Prediction of Reorganisation Energies in Organic Semiconductors
Engineering Safe and Trustworthy AI: The Participatory Harm Auditing Workbenches and Methodologies (PHAWM) Project
EEG subject detection: opportunity or threat?
Neurophysiological Approaches for Understanding Information Seeking
Neuroanatomical correlates and predictors of psychotic symptoms in Alzheimer s disease: A systematic review and meta-analysis (vol 204, 109006, 2024)
Accelerating the discovery of high-mobility molecular semiconductors: a machine learning approach
Jose. 2013. Building a large-scale corpus for evaluating event detection on twitter
Designing Chatbots for Informal Learning in Museums
Clinical Manifestations
Corrigendum to Neuroanatomical correlates and predictors of psychotic symptoms in Alzheimer s disease: A systematic review and meta-analysis
More technology? Evaluating the effectiveness of smart thermostats
Assessing the stability of clusters of neuropsychiatric symptoms in Alzheimer’s disease and mild cognitive impairment
GeoEval: Benchmark for Evaluating LLMs and Multi-Modal Models on Geometry Problem-Solving
EgoPlan: A framework for multi-agent planning using single agent planners
Introduction to the special issue on neuro-information science.
A Study of Snippet Length and Informativeness
UCUI 15: Proceedings of the ACM First International Workshop on Understanding the City with Urban Informatics
UCUI 15 chairs welcome
Intelligent RSS Aggregator
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