6 papers
SheetBrain: A Neuro-Symbolic Agent for Accurate Reasoning over Complex and Large Spreadsheets
Ziwei Wang, Jiayuan Su, Mengyu Zhou +7
Understanding and reasoning over complex spreadsheets remain fundamental challenges for large language models (LLMs), which often struggle with accurately capturing the complex str…
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…
Detecting Stealthy Backdoor Samples based on Intra-class Distance for Large Language Models
Jinwen Chen, Hainan Zhang, Fei Sun +4
Stealthy data poisoning during fine-tuning can backdoor large language models (LLMs), threatening downstream safety. Existing detectors either use classifier-style probability sign…
Learning Virtual Machine Scheduling in Cloud Computing through Language Agents
JieHao Wu, Ziwei Wang, Junjie Sheng +3
In cloud services, virtual machine (VM) scheduling is a typical Online Dynamic Multidimensional Bin Packing (ODMBP) problem, characterized by large-scale complexity and fluctuating…