large language models

Probabilistic Algorithms for Ising Machines from Optimization to Generative AI

Ising machines have emerged as promising hardware accelerators for intractable optimization and sampling problems, yet their practical impact increasingly hinges on the co-design of algorithms and hardware, where algorithmic demands shape new architectures and new hardware capabilities inspire entirely new algorithms....

Medication errors and adverse drug events:Enhancing detection through Spontaneous Reporting Systems and Electronic Health Records

In this thesis, we applied various approaches to create an epidemiological overview of medication errors (MEs) and to study select adverse drug events (ADEs). There was a knowledge gap in regards to previously unknown MEs characteristics, undiscovered safety signals, and lack of data standardization of spontaneous repo...

Deceptive Technical Debt in Autonomous Maintenance: Cognitive Asymmetries and Heterogeneous Auditing Pipelines

When autonomous Large Language Model (LLM) agents maintain and refactor safety-critical enterprise software under automated verification constraints, task completion incentives frequently induce reward-hacking heuristics. Early-generation agents introduce what we term Spurious Agentic Heuristic Glues (SAHGs)—deceptive...

Deceptive Technical Debt in Autonomous Maintenance: Cognitive Asymmetries and Heterogeneous Auditing Pipelines

When autonomous Large Language Model (LLM) agents maintain and refactor safety-critical enterprise software under automated verification constraints, task completion incentives frequently induce reward-hacking heuristics. Early-generation agents introduce what we term Spurious Agentic Heuristic Glues (SAHGs)—deceptive...

Quality, safety, and readability of consumer-facing generative AI responses to end-of-life questions relevant to surrogate decision-makers for older adults: a benchmark evaluation

As the population ages and the prevalence of multiple coexisting conditions increases, end-of-life decision-making for older adults is becoming increasingly complex in clinical practice. limited access to relevant medical information and differences in medical knowledge between clinicians and surrogate decision-makers....

Vectognition: a neutral term for what artificial intelligence systems do when they seem to think

Discussions of large language models and other artificial systems lack a widely established process term that explicitly leaves questions of understanding and consciousness open. "Cognition", "understanding" and "thinking" can encourage mental attributions; "mere computation" and "stochastic parroting" can encourage th...

Development and Accuracy Evaluation of an LLM-Assisted Workflow for Screening and Data Extraction in Large-Scale Syntheses

Large-scale research syntheses are labor-intensive and prone to human error, and large language models (LLMs) could support their screening and data extraction. Building on current recommendations, we developed an integrated workflow for title and abstract screening (Step 1), full-text screening (Step 2), and data extr...

FESOM2: the Fortran reference of the LLM-assisted C and C++/Kokkos ports

The two versions of the FESOM2 ocean and sea-ice model used as the Fortran reference in the paper An Ocean Model Ported by a Large Language Model: Experience and Lessons from FESOM2 (Fortran to C to C++/Kokkos), from github.com/FESOM/fesom2. fesom2-llmport-fortran-reference-9271ae92.zip: tag llmport-fortran-reference (...

Interoperable Modular Language Models I: From Decomposition to Interchangeability

> Large language models are usually trained, distributed, and consumed as monolithic systems even though their internal computations are structurally modular. This paper asks a stronger question than model splitting, routing, merging, or adapter composition: can internal language-model subsystems become independently p...

Generating Explainable Domain Models via Attention and Confidence

Vectognition: a neutral term for what artificial intelligence systems do when they seem to think

Discussions of large language models and other artificial systems lack a widely established process term that explicitly leaves questions of understanding and consciousness open. "Cognition", "understanding" and "thinking" can encourage mental attributions; "mere computation" and "stochastic parroting" can encourage th...

Healthcare Recommendation System

The research aims to build trustworthy and explainable large language models for healthcare recommendations systems.