Update README.md

README.md

@@ -8,7 +8,7 @@ pinned: false
 ---
 
 # **Introduction**
-We aim to advance LLM reasoning with autoregressive search capabilities, i.e., a single LLM performs an extended reasoning process with self-reflection and self-exploration of new strategies.
+We aim to advance LLM reasoning to enable LLMs with autoregressive search capabilities, where a single LLM performs an extended reasoning process with self-reflection and self-exploration of new strategies.
 We achieve this through our proposed Chain-of-Action-Thought (COAT) reasoning and a new post-training paradigm: 1) a small-scale format tuning (FT) stage to internalize the COAT reasoning format and 2) a large-scale self-improvement
 stage leveraging reinforcement learning (RL). Our approach results in Satori, a 7B LLM trained on open-source model (Qwen-2.5-Math-7B) and open-source data (OpenMathInstruct-2 and NuminaMath). Key features of Satori include:
  - Capable of self-reflection and self-exploration without external guidance.