Update README.md

Author: codelion

README.md

@@ -468,6 +468,16 @@ Authorization: Bearer your_secret_api_key
 
 ## SOTA results on benchmarks with optillm
 
+### AutoThink on GPQA-Diamond & MMLU-Pro (May 2025)
+
+| **Model**     | **GPQA-Diamond**            |                          | **MMLU-Pro**               |                          |
+|----------------|-----------------------------|--------------------------|----------------------------|--------------------------|
+|                | Accuracy (%)                | Avg. Tokens              | Accuracy (%)               | Avg. Tokens              |
+| DeepSeek-R1-Distill-Qwen-1.5B    | 21.72                       | 7868.26                  | 25.58                      | 2842.75                  |
+| with Fixed Budget | 28.47                     | 3570.00                  | 26.18                      | 1815.67                  |
+| **with AutoThink**  | **31.06**                   | **3520.52**              | **26.38**                  | **1792.50**              |
+
+
 ### LongCePO on LongBench v2 (Apr 2025)
 
 | Model¹                             | Context window | Short samples (up to 32K words) | Medium samples (32–128K words) |
@@ -552,6 +562,7 @@ called patchflows. We saw huge performance gains across all the supported patchf
 ![Results showing optillm mixture of agents approach used with patchflows](https://raw.githubusercontent.com/codelion/optillm/main/moa-patchwork-results.png)
 
 ## References
+- [AutoThink: efficient inference for reasoning LLMs](https://dx.doi.org/10.2139/ssrn.5253327) - [Implementation](optillm/autothink)
 - [CePO: Empowering Llama with Reasoning using Test-Time Compute](https://cerebras.ai/blog/cepo) - [Implementation](optillm/cepo)
 - [LongCePO: Empowering LLMs to efficiently leverage infinite context](https://cerebras.ai/blog/longcepo) - [Implementation](optillm/plugins/longcepo)
 - [Chain of Code: Reasoning with a Language Model-Augmented Code Emulator](https://arxiv.org/abs/2312.04474) - [Inspired the implementation of coc plugin](optillm/plugins/coc_plugin.py)