13 citations · 14 across the 4 of their papers we have counts for
4 papers
Uncertainty-Guided Chain-of-Thought for Code Generation with LLMs
Yuqi Zhu, Ge Li, Xue Jiang +4
Chain-of-Thought (CoT) reasoning has been demonstrated as an effective technique for improving the problem-solving capabilities of large language models (LLMs) in the context of co…
LONGCODEU: Benchmarking Long-Context Language Models on Long Code Understanding
Jia Li, Xuyuan Guo, Lei Li +7
Current advanced long-context language models offer great potential for real-world software engineering applications. However, progress in this critical domain remains hampered by…
Showing LLM-Generated Code Selectively Based on Confidence of LLMs
Jia Li, Yuqi Zhu, Yongmin Li +2
Large Language Models (LLMs) have shown impressive abilities in code generation, but they may generate erroneous programs. Reading a program takes ten times longer than writing it.…
Fine-Tuning Pre-Trained Language Models Effectively by Optimizing Subnetworks Adaptively
Haojie Zhang, Ge Li, Jia Li +3
Large-scale pre-trained language models have achieved impressive results on a wide range of downstream tasks recently. However, fine-tuning an extremely large-scale pre-trained lan…