3 papers
cs.LG2026
Towards Automated Kernel Generation in the Era of LLMs
Yang Yu, Peiyu Zang, Chi Hsu Tsai +11
The performance of modern AI systems is fundamentally constrained by the quality of their underlying GPU kernels, which translate high-level algorithmic semantics into low-level ha…
cs.LG2025
DataFlow: An LLM-Driven Framework for Unified Data Preparation and Workflow Automation in the Era of Data-Centric AI
Hao Liang, Xiaochen Ma, Zhou Liu +32
The rapidly growing demand for high-quality data in Large Language Models (LLMs) has intensified the need for scalable, reliable, and semantically rich data preparation pipelines.…
cs.CL2025
Beyond Natural Language Perplexity: Detecting Dead Code Poisoning in Code Generation Datasets
Chi-Chien Tsai, Chia-Mu Yu, Ying-Dar Lin +2
The increasing adoption of large language models (LLMs) for code-related tasks has raised concerns about the security of their training datasets. One critical threat is dead code p…