Shinsō Receives The Distinguished Paper of the Year Award at Alware 2025

Seoul, South Korea – Shinsō, the AI (artificial intelligence)-powered translation layer for blockchain source code, announced today it was the recipient of the highly coveted ACM SIGSOFT Distinguished Paper Award, given to the best full-length papers accepted in the research track.

The paper, ‘Securing the Multi-Chain Ecosystem: A Unified, Agent-Based Framework for Vulnerability Repair in Solidity and Move’, was bestowed the award after receiving a plethora of nominations from reviewers and high reviewer scores for its groundbreaking and high-quality research likely to shape the field of AI.

Authored by Dr. Rabimba Karanjai, Shinsō’s CAIO and world renowned AI language translation researcher, the paper explores the training of AI models to detect bad code patterns or potential vulnerabilities in smart contracts at the source code level. The breakthrough research will prove fundamental in evolving code-to-code translation across blockchain networks, helping guide users by not only identifying issues, but also leading to the generation of patches without human intervention for Move and Solidity code.

“This award from ACM is more than an academic recognition,” said Sam Beni, CEO of Shinsō. “It’s a signal to the blockchain industry that secure, AI-driven code translation is no longer experimental, it has arrived, is proven with Shinsō, and is ready to eliminate the barriers that have fragmented the blockchain ecosystem for far too long. Dr. Karanjai’s research brings us closer to a world where developers can build only once, deploy everywhere, and above all, do so securely.”
 

Receiving the ACM Distinguished Paper Award validates Shinsō’s research method and helps the company promote findings as open access, demonstrating to the larger scientific community the value and importance of their research. 

Most of the papers receiving the Distinguished Paper Award eventually become highly cited, meaning Shinsō’s contributions to the AI-powered source-code to source-code translation will further establish the company as a leader in the field.

About Shinsō 

Shinsō is the AI-powered source-code to source-code translation layer for Solidity, Move, Rust, and many other blockchain code infrastructures, that maintains functionality, security, and intent. The company’s abstraction layer allows end users to interact with one interface across all blockchain networks, exponentially reducing time and cost for protocol development.

Shinso will be launching soon to the public. Visit www.shinso.ai for more information or go to register interest on the official website

​​Disclaimer: This content is provided by the sponsor. The statements, views, and opinions expressed in this content are solely those of the content provider and do not necessarily reflect the views of this media platform or its publisher. We do not endorse, verify, or guarantee the accuracy, completeness, or reliability of any information presented. We do not guarantee any claims, statements, or promises made in this article. This content is for informational purposes only and should not be considered financial, investment, or trading advice. Investing in crypto and mining-related opportunities involves significant risks, including the potential loss of capital. It is possible to lose all your capital. These products may not be suitable for everyone, and you should ensure that you understand the risks involved. Seek independent advice if necessary. Speculate only with funds that you can afford to lose. Readers are strongly encouraged to conduct their own research and consult with a qualified financial advisor before making any investment decisions.Neither the media platform nor the publisher shall be held responsible for any fraudulent activities, misrepresentations, or financial losses arising from the content of this press release. In the event of any legal claims or charges against this article, we accept no liability or responsibility. 

Legal Disclaimer: This media platform provides the content of this article on an "as-is" basis, without any warranties or representations of any kind, express or implied. We assume no responsibility for any inaccuracies, errors, or omissions. We do not assume any responsibility or liability for the accuracy, content, images, videos, licenses, completeness, legality, or reliability of the information presented herein. Any concerns, complaints, or copyright issues related to this article should be directed to the content provider mentioned above.