2 papers
cs.SE2025
Beyond Autoregression: An Empirical Study of Diffusion Large Language Models for Code Generation
Chengze Li, Yitong Zhang, Jia Li +2
LLMs have become the mainstream approaches to code generation. Existing LLMs mainly employ autoregressive generation, i.e. generating code token-by-token from left to right. Howeve…
cs.AI2025
NodeRAG: Structuring Graph-based RAG with Heterogeneous Nodes
Tianyang Xu, Haojie Zheng, Chengze Li +4
Retrieval-augmented generation (RAG) empowers large language models to access external and private corpus, enabling factually consistent responses in specific domains. By exploitin…