This dissertation develops a framework for UAV trajectory design that bridges theoretical coverage guarantees and practical implementation constraints. The research introduces stochastic trajectory processes as a unifying paradigm, departing from deterministic optimization approaches that require precise user locations...
As large language models (LLMs) are increasingly used in education, there is a growing need to quickly verify and steer LLM-generated content for the benefit of students. In particular, it is important to ensure that educational AI systems improve learning outcomes and engagement while minimizing potential harms. While...
Alexander Scarlatos· ScholarWorks@UMassAmherst (U...· 0 citations
We construct a finite-spin, orientation-resolved four-simplex vertex amplitude that retains the full tetrahedral intertwiner algebra. Orientation is selected by restricting the history integration to the domain on which a native Spin(4)-invariant pseudoscalar has fixed sign. Because the restriction acts on the integrat...
Data-driven systems that use machine learning are now embedded in high-stakes domains including healthcare, hiring, and the criminal justice system, yet they routinely exhibit biases that cause real harm, generate stigmatizing language about marginalized groups, and encode discrimination into consequential decisions. A...
Recent advances in natural language processing (NLP), and in generative large language models (LLMs) in particular, have created new opportunities to develop scalable educational AI systems that support assessment, feedback, and personalized learning. Realizing this promise, however, requires more than applying general...
The rapid adoption of Neural Ranking Models (NRMs) in Information Retrieval (IR) underscores the urgent need for robust interpretability methods to ensure their reliability and transparency. Despite their widespread use, how NRMs model query-document relevance remains poorly understood, limiting their application in hi...
Social media platforms often operate on extractive security logics that prioritize frictionless data sharing, leaving users disempowered and prone to oversharing sensitive information, without fully recognizing the associated privacy implications. We present WAIT-A-SEC (Warnings About Information Transfer And Sharing:...
Timoteo Kelly, Praveen R. Rao· ACM International Conference...· 0 citations
Abstract Large Language Models (LLMs) are being employed widely to automate tasks across the software development life-cycle. It is, however, unclear whether these tasks are performed consistently with respect to the semantics of the artefacts being handled. This question is particularly under-researched concerning arc...
Mohammad Reza Mousavi· Lecture notes in computer sc...· 0 citations
The FAIR principles have transformed how computational materials data and workflows are shared, yet existing repositories can only serve pre-computed entries — their coverage is perpetually incomplete and cannot adapt to new questions on demand. We built OptiMat Alloys, a large-language-model-powered conversational age...
Yang Hu, Vladyslav Turlo· NCCR MARVEL· 0 citations
Large Language Models (LLMs) struggle with knowledge-intensive tasks due to hallucinations and fragmented reasoning over dispersed information. While Retrieval-Augmented Generation (RAG) grounds generation in external sources, existing methods often treat evidence as isolated units, failing to reconstruct the logical c...
Cheng-Yen Li, Xuanjun Chen, Claire Lin et al.· ACM Transactions on Intellig...· 0 citations
Abstract Large language models (LLMs) show promise for extracting clinically meaningful information from unstructured health records, yet real-world deployment is constrained by limited scalable, trustworthy validation approaches. Conventional evaluation relies on annotation-intensive reference standards and incomplete...
Maria Mahbub, Gregory M. Dams, Josh Arnold et al.· npj Digital Medicine· 0 citations
Activation steering, or direct manipulation of internal activations to guide large language model (LLM) responses toward specific semantic concepts, is emerging as a promising avenue for both understanding how semantic concepts are stored within LLMs and advancing LLM capabilities. Yet, existing steering methods are re...
Parmida Davarmanesh, Ashia Wilson, Adityanarayanan Radhakrishnan· Proceedings of the National...· 0 citations
A model developed by researchers at MIT and Boston Children's Hospital adjusts scans on the fly to track fetal movement, potentially sparing families repeat hospital visits.
