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From the 1 of 5 linked papers with an AI index.

activity
20242026
collaborators

5 papers

cs.SE2026

ExplainBench: Evaluating Code Explanations from Agents

Zhiyuan Pan, Sungmin Kang, Imam Nur Bani Yusuf +1

The paper introduces ExplainBench, a benchmark that automatically evaluates how trustworthy the explanations generated by code‑writing LLM agents are, by checking if the explanatio…

cs.SE2026

Code Review Agent Benchmark

Yuntong Zhang, Zhiyuan Pan, Imam Nur Bani Yusuf +3

Software engineering agents have shown significant promise in writing code. As AI agents permeate code writing, and generate huge volumes of code automatically -- the matter of cod…

cs.SE2025

BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions

Terry Yue Zhuo, Minh Chien Vu, Jenny Chim +30

Task automation has been greatly empowered by the recent advances in Large Language Models (LLMs) via Python code, where the tasks ranging from software engineering development to…

cs.SE2025

RustMap: Towards Project-Scale C-to-Rust Migration via Program Analysis and LLM

Xuemeng Cai, Jiakun Liu, Xiping Huang +6

Migrating existing C programs into Rust is increasingly desired, as Rust offers superior memory safety while maintaining C's high performance. However, vastly different features be…

cs.SE2024

Transducer Tuning: Efficient Model Adaptation for Software Tasks Using Code Property Graphs

Imam Nur Bani Yusuf, Lingxiao Jiang

Large language models have demonstrated promising performance across various software engineering tasks. While fine-tuning is a common practice to adapt these models for downstream…