The Future of LLM Architectures
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Artificial Intelligence".
Deadline for manuscript submissions: 15 August 2026 | Viewed by 583
Special Issue Editors
Interests: large language models; sentiment analysis; quantum cognition; sarcasm detection; affective computing; natural language processing
Interests: affective computing; time series mining
Special Issue Information
Dear Colleagues,
This Special Issue, entitled “The Future of LLM Architectures”, aims to gather cutting-edge research and visionary perspectives on the rapidly evolving landscape of large language models (LLMs). As LLMs continue to redefine the boundaries of artificial intelligence, this Special Issue will explore the full spectrum of theoretical, methodological, and applied advances shaping the next generation of intelligent systems.
Recent years have witnessed significant enhancements in the scale, capability, and impact of LLMs. Innovations such as multi-modal architectures, agent-based reasoning frameworks, System I and System II task modeling, and value alignment techniques are transforming how machines perceive, reason, and interact with the world. The integration of advanced fine-tuning strategies, reinforcement learning, and human feedback has transformed LLMs from static knowledge repositories to dynamic decision-makers that are capable of complex inference, adaptation, and creativity.
However, new challenges have arisen: How can we ensure that LLMs exhibit robust reasoning, fairness, and transparency across diverse applications? What are the best practices for evaluating capabilities such as logical reasoning, ethical value alignment, and multi-modal understanding? How can agent-based and modular architectures unlock new levels of intelligence and collaboration? This Special Issue provides a platform for the latest breakthroughs, emerging paradigms, and innovative discussions in the field.
We welcome original research articles, surveys, and position papers on topics including, but not limited to, the following:
- System I vs. System II task modelling in LLMs;
- Scalable architectures for advanced reasoning and planning;
- Fine-tuning and reinforcement learning with human or multi-agent feedback;
- Multi-modal large models: vision, language, audio, and beyond;
- Value alignment, ethical and cultural considerations in LLMs;
- Benchmarking, evaluation, and emergent capabilities analysis;
- Agent-based LLM frameworks and compositional intelligence;
- Robustness, interpretability, and trustworthiness of next-generation LLMs;
- New training methods for efficiency, safety, and continual learning;
- Application case studies in science, engineering, business, and education.
We invite researchers to contribute and share insights that will shape the future trajectory of LLM architectures and their transformative impact on society.
Dr. Yazhou Zhang
Dr. Xiang Li
Dr. Yao Zhang
Guest Editors
Manuscript Submission Information
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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- Large Language Models (LLMs)
- System I and System II reasoning
- multi-modal LLMs
- value alignment
- reinforcement learning
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