Tag
This paper introduces ORCA, a comprehensive benchmark for evaluating Large Language Models on data science code translation tasks, highlighting challenges and proposing an intent-augmented method to improve performance.
This paper proposes a reinforcement learning method for bootstrapping niche multilingual code translation with execution-based supervision, introducing a new benchmark HumanEval-X++ and demonstrating significant improvements over baselines using Qwen-3.5 models.
Cpp2Rust is an open-source tool that automatically translates C++ code to safe Rust using clang's AST and a runtime library, enabling safe memory-safe conversion with support for both safe and unsafe output modes.
This paper introduces SwiftTrans, a framework that addresses the overlooked issue of runtime efficiency in LLM-based code translation, achieving consistent improvements in both correctness and efficiency across benchmarks.
This paper proposes CTO, a method that improves code translation by combining syntax-guided and semantic-aware preference optimization through contrastive learning and direct preference optimization, achieving significant improvements over existing baselines in C++, Java, and Python translations.