6 papers
GNMR: Runtime Stability Control for Low-Precision Large Language Model Training
Boao Kong, Weichen Jia, Engao Zhang +6
Training stability is a key bottleneck in low-precision language model training: efficient low-cost paths can still produce short-lived numerical risks at a small set of operators.…
CodePivot: Bootstrapping Multilingual Transpilation in LLMs via Reinforcement Learning without Parallel Corpora
Shangyu Li, Juyong Jiang, Meibo Ren +7
Transpilation, or code translation, aims to convert source code from one programming language (PL) to another. It is beneficial for many downstream applications, from modernizing l…
oxo-call: Documentation-grounded Skill Augmentation for Accurate Bioinformatics Command-line Generation with Large Language Models
Yun Peng, Yujun Sun, Jia Ding +6
Command-line bioinformatics tools remain essential for genomic analysis, yet their diversity in syntax and parameterization presents a persistent barrier to productive research. We…
HiFloat4 Format for Language Model Pre-training on Ascend NPUs
Mehran Taghian, Yunke Peng, Xing Huang +22
Large foundation models have become central to modern machine learning, with performance scaling predictably with model size and data. However, training and deploying such models i…
\texttt{ReMind}: Understanding Deductive Code Reasoning in LLMs
Jun Gao, Yun Peng, Xiaoxue Ren
Large Language Models (LLMs) have achieved remarkable progress in code-related tasks. Despite their advancement, empirical evidence reveals that they still struggle with \emph{dedu…
PEACE: Towards Efficient Project-Level Efficiency Optimization via Hybrid Code Editing
Xiaoxue Ren, Jun Wan, Yun Peng +5
Large Language Models (LLMs) have demonstrated significant capability in code generation, but their potential in code efficiency optimization remains underexplored. Previous LLM-ba…