AbstractThis paper investigates EFL students’ perceptions of ethical acceptability judgments of using Large Language Models (LLMs) into academic writing. In contrast to the simplistic view of acceptable/unacceptable use of LLMs, the present study models how specific contextual justifications shape students’ moral evalu...
Mohamed SEDDIKI, Souhila Korichi· Zenodo (CERN European Organi...· 0 citations
This work introduces LLM-based compressors deploying two novel symbol-ranking variants that bound predictions to the top-$T$ ranks, and conducts the first large-scale evaluation of LLM-based source code compression across 30 LLMs, including general-domain, code-specialized, and quantized models.
Angelo Nardone, P. Ferragina· arXiv.org· 0 citations
While LLM-based multi-agent systems show potential for large-scale software development, successful integration requires addressing challenges such as memory limitations, hallucinations, and code smells, alongside a practitioner-centric perspective.
Z. Rasheed, Muhammad Waseem, Kai-Kristian Kemell et al.· 31 citations
The proposed LLM-based multi-agent system automates qualitative data analysis process, creating opportunities for researchers and practitioners, and future improvements focus on enhancing multilingual performance and integrating continuous expert feedback.
Z. Rasheed, Muhammad Waseem, Aakash Ahmad et al.· arXiv.org· 41 citations
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A Multi-Vocal Literature Review is conducted, combining insights from both academia and industry, including peer-reviewed studies and grey literature to systematically synthesize and analyze existing knowledge on LLM-based multi-agent systems for code generation.
Z. Rasheed, Muhammad Waseem, Kai-Kristian Kemell et al.· arXiv.org· 2 citations
This study provides the first large-scale empirical comparison of agentic frameworks for reasoning-intensive software engineering tasks and shows that framework selection should prioritize orchestration quality, especially memory control, failure handling, and cost management.
Z. Rasheed, Malik Abdul Sami, Muhammad Waseem et al.· arXiv.org· 1 citation
The vision is to leverage the capabilities of multiple GPT agents to contribute to SE tasks and to propose an initial road map for future work, arguing that multiple G PT agents can perform creative and demanding tasks far beyond coding and debugging.
Z. Rasheed, Muhammad Waseem, Kai-Kristian Kemell et al.· XP Workshops· 34 citations· ⚡2
This work proposes a two-stage framework to assess the severity of false claims during disasters, and investigates false claim severity assessment as a human-AI alignment problem, evaluating whether models can reproduce human judgments under a shared evaluation rubric rather than merely predicting severity labels.
Ruichen Yao, Tejna Dasari, G. Baispay et al.· Proceedings of the 2026 ACM...· 0 citations
A minimal seven-field curatable record is derived and complementary responsibilities for model hubs, scholarly indexes, and digital libraries are derived, providing practical guidance for improving the preservation and bibliographic control of open LLM artifacts.
The results indicate that current MLLMs can process visually clear English and structured numeric content, but reliable native Khmer document understanding remains an open challenge.
This work introduces a generalizable large language model (LLM)-powered pipeline for automated extraction and structuring of materials data from unstructured scientific literature, using concrete materials as a representative and particularly challenging example.
Zhanzhao Li, Kengran Yang, Qi-Yao He et al.· npj Computational Materials· 0 citations
Political Violence Targeting Women (PVTW) has reached record highs in fragile, low-resource settings. This paper presents a structural analysis integrating both theory and empirical evidence to examine how a rapidly evolving hybrid public sphere—where the intertwined logics of traditional news and social media create a...
Shaocheng Huang, Daniel Barkoczi· Zenodo (CERN European Organi...· 0 citations
