22 citations · 33 across the 11 of their papers we have counts for
4 papers · 1 filter
EffiCoder: Enhancing Code Generation in Large Language Models through Efficiency-Aware Fine-tuning
Dong Huang, Guangtao Zeng, Jianbo Dai +6
As large language models (LLMs) play an increasingly important role in code generation, enhancing both correctness and efficiency has become crucial. Current methods primarily focu…
Hybrid-Parallel: Achieving High Performance and Energy Efficient Distributed Inference on Robots
Zekai Sun, Xiuxian Guan, Junming Wang +6
The rapid advancements in machine learning techniques have led to significant achievements in various real-world robotic tasks. These tasks heavily rely on fast and energy-efficien…
EffiLearner: Enhancing Efficiency of Generated Code via Self-Optimization
Dong Huang, Jianbo Dai, Han Weng +5
Large language models (LLMs) have shown remarkable progress in code generation, but their generated code often suffers from inefficiency, resulting in longer execution times and hi…
EffiBench: Benchmarking the Efficiency of Automatically Generated Code
Dong Huang, Yuhao Qing, Weiyi Shang +2
Code generation models have increasingly become integral to aiding software development. Although current research has thoroughly examined the correctness of the code produced by c…