6 papers
Towards Robust Personalized Federated Learning: Vulnerability Assessment and Defense Co-Design
Mingyuan Fan, Cen Chen
The proliferation of IoT devices has fueled distributed edge systems to collect vast amounts of sensitive data, creating fertile ground for on-device machine learning applications.…
Evaluating Interactive Reasoning in Large Language Models: A Hierarchical Benchmark with Executable Games
Mingyuan Fan, Weiguang Han, Daixin Wang +3
We introduce a multi-turn interactive framework for reasoning evaluation that treats reasoning as active evidence acquisition and belief updating. Wherein, LLMs receive only the ta…
What Does the Server See? Understanding Privacy Leakage from Large Language Models in Split Inference
Mingyuan Fan, Yu Liu, Fuyi Wang +1
The deployment of large language models (LLMs) on resource-constrained devices remains challenging, spurring interest in split inference, where models are partitioned between clien…
CSMD: Curated Multimodal Dataset for Chinese Stock Analysis
Yu Liu, Zhuoying Li, Ruifeng Yang +2
The stock market is a complex and dynamic system, where it is non-trivial for researchers and practitioners to uncover underlying patterns and forecast stock movements. The existin…
FedCoT: Communication-Efficient Federated Reasoning Enhancement for Large Language Models
Chuan Li, Qianyi Zhao, Fengran Mo +1
Efficiently enhancing the reasoning capabilities of large language models (LLMs) in federated learning environments remains challenging, particularly when balancing performance gai…
CCJA: Context-Coherent Jailbreak Attack for Aligned Large Language Models
Guanghao Zhou, Panjia Qiu, Mingyuan Fan +4
Despite explicit alignment efforts for large language models (LLMs), they can still be exploited to trigger unintended behaviors, a phenomenon known as "jailbreaking." Current jail…