I think it's better to enhance you agent so it get better results. Sending your paper without final results it's not a good idea :) (my opinion).

I agree with previous answer, transparency is paramount.

Absolutely include a detailed, honest note addressing the agent’s incomplete refinement – explicitly stating its current capabilities and limitations. It's better to present a partially functional but rigorously evaluated system than a potentially misleading, polished facade. Frame it as a work-in-progress, outlining future development pathways. Rigorous evaluation despite limitations demonstrates sound methodology.

Dear Asuka Inoshita ,

Code completion serves as a fundamental aspect of modern software development, improving developers' coding processes. Integrating code completion tools into an Integrated Development Environment (IDE) or code editor enhances the coding process and boosts productivity by reducing errors and speeding up code writing while reducing cognitive load. This is achieved by predicting subsequent tokens, such as keywords, variable names, types, function names, operators, and more. Different techniques can achieve code completion, and recent research has focused on Deep Learning methods, particularly Large Language Models (LLMs) utilizing Transformer algorithms.

Article Large Language Models for Code Completion: A Systematic Lite...

Regards,

Shafagat

Auka Inoshita,

Complete the code using you debug functioning inorder to isolate the issues and remember that building a function that alleviates the GenAI's output process struggle. parameters are always key for testing but utilize different methods to figure the issue out and reattempt testing and finalize it properly