4 papers
BackendForge: Benchmarking Agentic End-to-End Code Generation with Backend Services
Yuzhe Guo, Mengzhou Wu, Yuan Cao +4
Large language models (LLMs) are increasingly used in agentic coding settings, where they can inspect files, execute commands, run tests, observe failures, and iteratively revise c…
AppForge: From Assistant to Independent Developer -- Are GPTs Ready for Software Development?
Dezhi Ran, Yuan Cao, Mengzhou Wu +10
Large language models (LLMs) have demonstrated remarkable capability in function-level code generation tasks. Unlike isolated functions, real-world applications demand reasoning ov…
Tuning LLMs by RAG Principles: Towards LLM-native Memory
Jiale Wei, Shuchi Wu, Ruochen Liu +3
Memory, additional information beyond the training of large language models (LLMs), is crucial to various real-world applications, such as personal assistant. The two mainstream so…
AI-native Memory 2.0: Second Me
Jiale Wei, Xiang Ying, Tao Gao +3
Human interaction with the external world fundamentally involves the exchange of personal memory, whether with other individuals, websites, applications, or, in the future, AI agen…