4 papers
Parameter Importance-Driven Continual Learning for Foundation Models
Lingxiang Wang, Hainan Zhang, Zhiming Zheng
Domain-specific post-training often causes catastrophic forgetting, making foundation models lose their general reasoning ability and limiting their adaptability to dynamic real-wo…
FedDTRE: Federated Dialogue Generation Models Powered by Trustworthiness Evaluation
Shule Lu, Lingxiang Wang, Sijia Wen +2
With the rapid development of artificial intelligence, dialogue systems have become a prominent form of human-computer interaction. However, traditional centralized or fully local…
Beyond the Surface: A Solution-Aware Retrieval Model for Competition-level Code Generation
Shiwen Zhang, Lingxiang Wang, Hainan Zhang +3
In competitive programming task, problem statements are often embedded within elaborate narrative backgrounds, requiring deep understanding of the underlying solutions to successfu…
CodeBC: A More Secure Large Language Model for Smart Contract Code Generation in Blockchain
Lingxiang Wang, Hainan Zhang, Qinnan Zhang +4
Large language models (LLMs) excel at generating code from natural language instructions, yet they often lack an understanding of security vulnerabilities. This limitation makes it…