14 citations · 87 across the 46 of their papers we have counts for
4 papers · 1 filter
ScaleBox: Enabling High-Fidelity and Scalable Code Verification for Large Language Models
Jiasheng Zheng, Xin Zheng, Boxi Cao +8
Code sandboxes have emerged as a critical infrastructure for advancing the coding capabilities of large language models, providing verifiable feedback for both RL training and eval…
EmbedAgent: Benchmarking Large Language Models in Embedded System Development
Ruiyang Xu, Jialun Cao, Mingyuan Wu +6
Large Language Models (LLMs) have shown promise in various tasks, yet few benchmarks assess their capabilities in embedded system development. In this paper, we introduce EmbedAgen…
Across Programming Language Silos: A Study on Cross-Lingual Retrieval-augmented Code Generation
Qiming Zhu, Jialun Cao, Xuanang Chen +6
Current research on large language models (LLMs) with retrieval-augmented code generation (RACG) has largely focused on single-language settings, leaving their cross-lingual effect…
Beyond Correctness: Benchmarking Multi-dimensional Code Generation for Large Language Models
Jiasheng Zheng, Boxi Cao, Zhengzhao Ma +5
In recent years, researchers have proposed numerous benchmarks to evaluate the impressive coding capabilities of large language models (LLMs). However, current benchmarks primarily…