QV Suffices for LLM Attention Essence

What Changed

Derives QKV essence via POS and syntactic analysis.

Why It Matters

This theoretical framework could simplify attention mechanisms, enabling more efficient LLM designs with fewer parameters. It guides future optimizations, potentially reducing training and inference costs for Transformer-based models.

What To Do Next

Implement QV projections in PyTorch Transformer to test parameter reduction on your benchmarks.