Update README.md

README.md

@@ -26,7 +26,7 @@ LLM security, autonomous evaluation, and multi-agent reasoning systems.
 ### Paper 1 — AI In The Loop (AITL)
 
 **AI In The Loop: A Systems Taxonomy for Closed-Loop Autonomous Evaluation**
-*Sanskar Jajoo, NeurAlchemy Labs, 2026*
+*Sanskar Jajoo, Neuralchemy Labs, 2026*
 
 Establishes a formal taxonomy for autonomous AI evaluation systems, defining the layered architecture (Coder, Reviewer, Meta-Controller) that enables closed-loop ML engineering without human intervention.
 
@@ -37,7 +37,7 @@ Establishes a formal taxonomy for autonomous AI evaluation systems, defining the
 ### Paper 2 — The Autonomous Sunk-Cost Fallacy
 
 **The Autonomous Sunk-Cost Fallacy: Stopping Failures and Meta-Reasoning in LLMs Deployed within AEOS**
-*Sanskar Jajoo, NeurAlchemy Labs, 2026*
+*Sanskar Jajoo, Neuralchemy Labs, 2026*
 
 Discovers that LLM agents exhibit a computational analog of the human sunk-cost fallacy — continuing to invest compute into failing strategies rather than stopping. Introduces the AEOS (Autonomous Empirical Optimization System) framework and demonstrates that dual-agent architectures with asymmetric reviewer-coder roles eliminate this failure mode.