diff --git a/README.md b/README.md
index dd0e2548..8f12ed86 100644
--- a/README.md
+++ b/README.md
@@ -137,7 +137,7 @@ response = client.chat.completions.create(
 
 Please note that the convention described above works only when the optillm server has been started with inference approach set to `auto`. Otherwise, the `model` attribute in the client request must be set with the model name only.
 
-We now suport all LLM providers (by wrapping around the [LiteLLM sdk](https://docs.litellm.ai/docs/#litellm-python-sdk)). E.g. you can use the Gemini Flash model with `moa` by setting passing the api key in the environment variable `os.environ['GEMINI_API_KEY']` and then calling the model `moa-gemini/gemini-1.5-flash-002`. In the output you will then see that LiteLLM is being used to call the base model.
+We now support all LLM providers (by wrapping around the [LiteLLM sdk](https://docs.litellm.ai/docs/#litellm-python-sdk)). E.g. you can use the Gemini Flash model with `moa` by setting passing the api key in the environment variable `os.environ['GEMINI_API_KEY']` and then calling the model `moa-gemini/gemini-1.5-flash-002`. In the output you will then see that LiteLLM is being used to call the base model.
 
 ```bash
 9:43:21 - LiteLLM:INFO: utils.py:2952 -
@@ -629,7 +629,7 @@ See `tests/README.md` for more details on the test structure and how to write ne
 - [Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning](https://arxiv.org/abs/2405.00451) - [Inspired the implementation of mcts](optillm/mcts.py)
 - [Unsupervised Evaluation of Code LLMs with Round-Trip Correctness](https://arxiv.org/abs/2402.08699) - [Inspired the implementation of rto](optillm/rto.py)
 - [Patched MOA: optimizing inference for diverse software development tasks](https://arxiv.org/abs/2407.18521) - [Implementation](optillm/moa.py)
-- [Patched RTC: evaluating LLMs for diverse software development tasks](https://arxiv.org/abs/2407.16557) - [Implementation](ptillm/rto.py)
+- [Patched RTC: evaluating LLMs for diverse software development tasks](https://arxiv.org/abs/2407.16557) - [Implementation](optillm/rto.py)
 - [AIMO-2 Winning Solution: Building State-of-the-Art Mathematical Reasoning Models with OpenMathReasoning dataset](https://arxiv.org/abs/2504.16891) - [Implementation](optillm/plugins/genselect_plugin.py)
 - [Test-Time Diffusion Deep Researcher (TTD-DR): Think More, Research More, Answer Better!](https://arxiv.org/abs/2507.16075v1) - [Implementation](optillm/plugins/deep_research)