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 * Couler is a system designed for unified machine learning workflow optimization in the cloud. Couler endeavors to provide a unified interface for constructing and optimizing workflows across various workflow engines, such as [Argo Workflows](https://github.com/argoproj/argo-workflows), [Tekton Pipelines](https://tekton.dev/), and [Apache Airflow](https://airflow.apache.org/). Couler enhances workflow efficiency through features like Autonomous Workflow Construction, Automatic Artifact Caching Mechanisms, Big Workflow Auto Parallelism Optimization, and Automatic Hyperparameters Tuning.
 * Couler is included in [CNCF Cloud Native Landscape](https://landscape.cncf.io/) and [LF AI Landscape](https://landscape.lfai.foundation).
-* The technical report for Couler can be found at the following link: [Techinal-Report](https://github.com/couler-proj/couler/tree/master/docs/Technical-Report-of-Couler)
+* Check out our technical report published on ICDE 2024 [here](https://arxiv.org/abs/2403.07608).
 
 > Note that while one of ambitious goals of Couler is to support multiple workflow engines, Couler currently only supports Argo Workflows as the workflow orchestration backend. An ambitious goal of Couler is to provide support for multiple workflow engines. While it initially supported only Argo Workflows for workflow orchestration, efforts are now underway to extend support to other workflow engines such as Tekton Pipelines and Apache Airflow.
 > In addition, if you are looking for a Python SDK that provides access to all the available features from Argo Workflows, you might want to check out [the low-level Python SDK maintained by the Argo Workflows team](https://argoproj.github.io/argo-workflows/client-libraries/).