LLMs Hit a Wall: Einstein's Riddle Exposes Limits of Transformer-Based AI
2025-02-02
Researchers have discovered fundamental limitations in the ability of current transformer-based large language models (LLMs) to solve compositional reasoning tasks. Experiments involving Einstein's logic puzzle and multi-digit multiplication revealed significant shortcomings, even after extensive fine-tuning. These findings challenge the suitability of the transformer architecture for universal learning and are prompting investigations into alternative approaches, such as improved training data and chain-of-thought prompting, to enhance LLM reasoning capabilities.