Spectral Theory Explains Why LLMs Miss Their Own Errors
Researchers introduce SPARC, a spectral-algebraic framework that shows an LLM’s self‑correction blind spot appears when the error‑propagation operator’s spectral radius exceeds one. The model predicts a precise activation threshold, matching an 89.3% reduction using a simple ‘Wait’ marker, and explains convergence limits for verifier‑corrector RL training. This gives a concrete handle on improving self‑verification and agentic pipelines.