Recursive Self-Correction via Latent Symbolic Traces (LS-Trace)

1|--- 2|title: Recursive Self-Correction via Latent Symbolic Traces (LS-Trace) Analysis 3|created: 2026-05-29 4|updated: 2026-05-29 5|type: concept 6|tags: [research, whitepaper] 7|sources: /root/wiki/raw/papers/latent-symbolic-traces-reasoning-2026.md 8|--- 9| 10|# Recursive Self-Correction via Latent Symbolic Traces (LS-Trace) 11| 12|## 🎯 The Core Thesis 13|Eliminating error propagation in autoregressive reasoning by implementing an internal verification loop based on latent symbolic traces. 14| 15|## 💡 The Innovation 16|The model generates “symbolic traces” in latent space and cross-references them against learned axiomatic constraints before decoding the final token stream. 17| 18|## 📈 Key Results 19|42% increase in accuracy on the MATH-Hard 2026 benchmark; significant reduction in logical hallucinations. 20| 21|## 🌍 Implications 22|Moves LLMs closer to system-2 reasoning, enabling reliable multi-step problem solving in critical domains like coding and mathematics. 23| 24|## ⚖️ Verdict 25|High. A major step toward verifiable AI reasoning. 26|