Empirical Research in Autonomous Intelligence
NovaX AI Research publishes peer-reviewed, open-access papers, datasets, and systems dedicated to making AI self-directing, reliable, and capable of executing verifiable outcomes.
Latest Publication
The Evolution, Capabilities, Limitations, and Future of Large Language Models (2026): A Comprehensive Review
Featured Publication
The Evolution, Capabilities, Limitations, and Future of Large Language Models (2026): A Comprehensive Review
This preprint presents a comprehensive review of the evolution, capabilities, limitations, and future directions of Large Language Models (LLMs). The paper surveys transformer architectures, scaling laws, reasoning capabilities, coding perf...
Research Directions
Three core paradigms guiding our empirical investigation into the frontier of autonomous AI systems.
Large Language Models
Scaling laws, retrieval augmentation, reasoning engines, and context extension across frontier model families.
Autonomous AI Agents
Goal planning, self-correction, execution sandboxes, and multi-agent collaborative networks.
Open Datasets & Benchmarks
High-quality instruction corpora, human feedback alignment datasets, and agent benchmark suites.
Research Timeline
NovaX AI Research Lab Established
A dedicated research division within NovaX AI was launched with a mission to publish empirical, open-access AI research indexed in global academic registries.
The Evolution, Capabilities, Limitations, and Future of Large Language Models (2026): A Comprehensive Review
Published open-access on Zenodo (DOI: 10.5281/zenodo.20553933). Research area: Large Language Models.