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Token Sugar: Making Source Code Sweeter for LLMs through Token-Efficient Shorthand
Zhensu Sun, Chengran Yang, Xiaoning Du +3
Large language models (LLMs) have shown exceptional performance in code generation and understanding tasks, yet their high computational costs hinder broader adoption. One importan…
BigCodeArena: Unveiling More Reliable Human Preferences in Code Generation via Execution
Terry Yue Zhuo, Xiaolong Jin, Hange Liu +37
Crowdsourced model evaluation platforms, such as Chatbot Arena, enable real-time evaluation from human perspectives to assess the quality of model responses. In the coding domain,…
Extending Fill-In-the-Middle with Instructions for Steerable Code Completion
Zhensu Sun, Chengran Yang, Chao Peng +4
Code completion models often fail when the developer's intent is under-specified in the code context. To mitigate this, developers frequently use natural language comments to clari…
The Hidden Cost of Readability: How Code Formatting Silently Consumes Your LLM Budget
Dangfeng Pan, Zhensu Sun, Cenyuan Zhang +2
Source code is usually formatted with elements like indentation and newlines to improve readability for human developers. However, these visual aids do not seem to be beneficial fo…