Some LLMs, particularly ChatGPT and Kimi, showed moderate alignment with human examiners, but the alignemnet was not consistently stable across repeated sessions or operational settings.
Asgeir Brevik, H. Jerpseth, S. Lafontan· Frontiers in Education· 0 citations
This article discusses the challenges of testing software systems with increasingly integrated AI and LLM functionalities. LLMs are powerful but unreliable, and labeled ground truth for testing rarely scales. Metamorphic Testing solves this by turning relations among multiple test executions into executable test oracle...
BADD is a human-annotated Bangla social-media dataset for arrogance detection and fine-grained arrogance analysis. The current release contains 22,427 comments based on three independent human annotation files. No AI system or model-derived signal was used as an annotator or for human consensus. The original annotation...
A novel taxonomy to categorize advanced techniques into non-interactive reasoning, interactive collaboration, and efficiency-oriented decoding strategies is proposed and serves as a strategic roadmap to foster further innovation in parallel reasoning.
Zi-Qi Wang, Bo-Ye Niu, Zi-Peng Gao et al.· National Science Review· 0 citations
Replication package for the paper "Evaluating LLMs for Single-File Modernization of Legacy PHP: Source Modernization versus Behavioral Preservation." The study evaluates five large language models (Claude Sonnet 4, Gemini 2.5 Pro, Gemini 2.5 Flash, GPT-5 Codex, and Llama 3.3 70B Instruct) on modernizing 100 WordPress 4...
Anonymous· Zenodo (CERN European Organi...· 0 citations
This record documents a pre-results, pre-freeze public study protocol and reproducibility harness for an empirical study of tool-using large-language-model agents under prompt-injection exposure and externally narrowed authority. The artifact specifies the threat model, authority narrowing and evidence-gated restoratio...
Burak Oktenli· Zenodo (CERN European Organi...· 0 citations
Prefix adders are fundamental arithmetic circuits, but their design space grows exponentially with bit-width, posing significant optimization challenges. Previous works face limitations in performance, generalization, and scalability. To address these challenges, we propose PrefixAgent , a large language model (LLM)-po...
Dongsheng Zuo, Jiadong Zhu, Yang Luo et al.· ACM Transactions on Design A...· 0 citations
Before organisations can successfully manage to coordinate their complex supply chains, a long distance still lies ahead before they can become more responsive, efficient and resilient. A new use of AI that is possible with the integration of Large Language Models (LLMs) into Multi-Agent Systems (MAS) is intelligent, r...
Mayur Sen, S. Poornima, Sreejith R. et al.· Materials, Mechanics, Mechat...· 0 citations
Background Healthy lifestyle management is essential for chronic disease prevention and long-term care. However, evidence linking lifestyle behaviors, biological mechanisms, and health outcomes is dispersed across diverse biomedical sources. This fragmentation makes it difficult for health professionals to efficiently...
Hong-Yu Kang, Xiao-Wei Xu, Ning Xiao et al.· Frontiers in Public Health· 0 citations
In this paper, we present a latency-aware scheduler for large-language-model (LLM) inference across mobile devices, edge servers, and a remote cloud. Our fine-grained delay model captures OFDMA uplink/downlink rates, KV-cache backhaul serialization, and profiled GPU planning-chunk resource constraints, enabling per-req...
Xinghan Wang, Xiao-Xiong Zhong, Wei-Hong Yang et al.· IEEE Transactions on Paralle...· 0 citations
Microbial genomes encode non-coding RNAs (ncRNAs) and nucleic-acid-interacting proteins essential to biology and biotechnology. However, discovery of these systems remains protein-centric and based on similarity to known sequences. Here, we introduce Minerva, a framework for coevolutionary mining that uses genome langu...
David B. Li, G. Brixi, Alexandra S. Kim et al.· bioRxiv· 1 citation