The rapid growth of biomedical literature has rendered traditional systematic reviews unsustainable. Although large language models (LLMs) offer automation potential, citation fabrication and unreliable evidence discrimination remain critical barriers. Here, using PubChat as a PubMed E-utilities-grounded retrieval fram...
Xuenan Zhuang, Dan Cao, Ruoyu Chen et al.· npj Digital Medicine· 0 citations
This paper introduces IdeaSearchFitter, a framework that employs Large Language Models (LLMs) as semantic operators within an evolutionary search that achieves competitive, noise-robust performance on the Feynman Symbolic Regression Database (FSReD), outperforming several strong baselines.
Zhuo-Yang Song, Ze-Yu Cai, Shu-Tao Zhang et al.· Communications in Theoretica...· 0 citations
Large language models (LLMs) increasingly repair software vulnerabilities, but most evaluations judge only similarity to a developer fix or removal of the weakness, leaving no single judge trustworthy.
Patrick Deininger, Wolfgang Slany· Journal of Cybersecurity and...· 1 citation
Automated analysis for engineering structures offers considerable potential for boosting efficiency by minimizing repetitive tasks. Although AI-driven methods are increasingly common, no systematic framework yet leverages Large Language Models (LLMs) for automatic structural analysis. This paper proposes a framework th...
Haoran Liang, Mohammad Talebi-Kalaleh, Qi-Pei Mei· Automation in Construction· 3 citations
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Results indicate that near-optimal performance can be achieved even when rationales are provided for only a subset of the training data, and that shorter explanations are often sufficient.
Lukas Vöge, Vincent Gurgul, Stefan Lessmann· Management & Marketing· 0 citations
The increasing adoption of Large Language Models (LLMs) as a text analysis method in social science presents a critical yet under-examined trade-off between model performance and environmental sustainability. This research provides a systematic evaluation comparing the performance, energy consumption, processing time...
Sean Hamilton-Palicki, Isaac Bravo, Clint Claessen· Social science computer revi...· 0 citations
Neurocritical care focuses on patients with actual or impending organ dysfunction that arises from, or accompanies, primary or secondary neurological injury and necessitates intensive care (1). As a subspecialty, neurocritical care continues to face unresolved and controversial questions in both clinical practice and r...
Linlin Zhang, Jian-Xin Zhou· Frontiers in Medicine· 0 citations
A leak-aware cross-dataset evaluation framework is presented to examine the robustness of classical machine learning and Transformer-based prompt injection detection models in the face of data source changes, and shows that internal validation results are not enough for prompt injection detection.
Oğuzhan Kilim· Yalvaç akademi dergisi· 0 citations
Large language model (LLM)-based artificial intelligence is increasingly used in ethically consequential human decision-making, yet fully autonomous machine ethics remains unrealistic, motivating architectures that support rather than replace human ethical judgment. This study introduces the Cognitive–Reflective Equili...
Chulmin Kim, Seongjin Ahn· Journal of Intelligence· 0 citations
Organisations collect large amounts of safety data concerning safety events. However, many organisations are still in their infancy in this regard, especially when it comes to utilising large datasets containing textual safety data to support their safety management. Fast-developing Artificial Intelligence (AI) and mac...
Maria Tiikkaja, Henriikka Kannisto, A. Nurmi et al.· Safety Science· 0 citations
This experiment exposes an extremely fruitful usage pattern for AI in science: translating results between different communities and application domains, accelerating the process by which serendipitous discoveries in a field become paradigm-shifting breakthroughs in another.
M. Domina, Michele Ceriotti· arXiv.org· 0 citations
This exploratory study aims to investigate how humans and CLLMs can collaborate as peers through vibe coding, an approach that integrates principles from prompt engineering, agile design, and human-AI co-creation to enhance collaboration.
Moritz Mock, Barbara Russo· arXiv.org· 0 citations
