large language models

Advances, Risks, And Implementation Challenges of Artificial Intelligence as A Force Multiplier for Clinical Decision Making and Health System Efficiency

The central argument is that the value of clinical artificial intelligence is determined less by model accuracy in isolation than by the quality of the sociotechnical system into which a model is placed: governance, workflow integration, monitoring, and the preservation of meaningful human oversight.

An Empirical Investigation of Whether Role Asymmetry Can Overcome Reasoning Blind Spots in Homogeneous Models through Adaptive Routing and Local Repair

These findings provide reproducible empirical evidence for systematic reasoning blind spots in self-criticism by homogeneous models, and indicate that role asymmetry implemented only through prompting cannot reliably overcome cognitive homogeneity.

Risk and Return under Open-Source LLM Shocks: A CAPM Analysis of U.S. AI-Related Sector ETFs

This paper examines the impact of two landmark open-source releases—DeepSeek-R1 and Kimi K3—on the returns and risk of five U.S. AI-related sector ETFs, finding that both shocks were highly concentrated in the computing-power layer, while the application layer remained relatively resilient.

From transformer to large language models for automated generation of hospital discharge summaries: a systematic review

Neurosymbolic code auditing

Code auditing examines whether an implementation satisfies target properties such as reliability, security, performance, and design intent. Classical static analysis provides rigorous foundations for automated auditing, but it remains difficult to apply broadly in real-world software. The emergence of large language mo...

Attack Chain Reconstruction Method Based on LLM Prior-Knowledge Guidance and Heterogeneous Graph Reasoning

In the face of multi-stage and cross-device complex network attacks, reconstructing the complete attack link from massive heterogeneous security logs is the core problem of security operation. In the existing methods, the traditional graph model lacks a deep understanding of the semantics of alerts, and large language...

History of Algorithmic Music Generation: From Mozart to Modern AI

Algorithmic Music Generation is an old topic. From very basic systems of controlled randomness to advanced data-driven systems. This paper summarizes the general history of algorithmic music generation, as well as three key eras: the random combination era, the rule-based algorithm generation era and the deep learning...

Consistent Explainers or Unreliable Narrators: Systematic Differences in Consistency and Sensitivity Across Large Language Models for Group Recommendations

Group Recommender Systems (GRS) face the challenge of combining conflicting individual preferences. While Large Language Models (LLMs) are increasingly integrated into GRS, they may introduce risks regarding output inconsistency or sensitivity to group characteristics. In this paper, we analyze LLMs acting as both deci...

Do we carry the false belief that LLMs have a theory of mind?

Reprezentacja informacji proweniencyjnych w internetowych katalogach muzealnych a wykorzystanie dużych modeli językowych

The article analyses how the representation of provenance information in online museum catalogues affects its identification and extraction by modern large language models (LLMs). The study examined 60 painting records from four Polish museums using the GPT-5.5 model. Six basic methods of representing provenance inform...

An interpretable large language model framework with the cokemaking-oriented prompt and fuzzy-enhanced explanation for coke quality prediction

Politeness to ChatGPT Reconsidered: Structural Injustice and Respect for Rational Agents

The widespread interaction between humans and large language models has sparked normative debates regarding user politeness toward artificial intelligence. This paper explores the ethical rationality of maintaining polite linguistic norms in human-LLM interaction, arguing against the normative obligation of being polit...