3 papers
cs.AR2026
Quality over Quantity: Diversity-Aware Data Selection for Efficient Verilog Code Generation
Yiheng Shen, Wei Zheng, Xiao Wei +3
Large Language Models (LLMs) have shown remarkable potential in Verilog code generation, yet existing datasets contain con siderable noise and redundancy. Prior data selection meth…
cs.AR2025
Large Language Model for Verilog Code Generation: Literature Review and the Road Ahead
Guang Yang, Wei Zheng, Xiang Chen +14
Code generation has emerged as a critical research area at the intersection of Software Engineering (SE) and Artificial Intelligence (AI), attracting significant attention from bot…
cs.CL2025
StatEval: A Comprehensive Benchmark for Large Language Models in Statistics
Yuchen Lu, Run Yang, Yichen Zhang +6
Despite rapid advances in large language models (LLMs), statistical reasoning remains underrepresented in existing LLM benchmarks, which often do not reflect the layered, proof-dri…