5 papers
STORM-BORN: A Challenging Mathematical Derivations Dataset Curated via a Human-in-the-Loop Multi-Agent Framework
Wenhao Liu, Zhenyi Lu, Xinyu Hu +13
High-quality math datasets are crucial for advancing the reasoning abilities of large language models (LLMs). However, existing datasets often suffer from three key issues: outdate…
6Diffusion: IPv6 Target Generation Using a Diffusion Model with Global-Local Attention Mechanisms for Internet-wide IPv6 Scanning
Nabo He, DanDan Li, Xiaohong Huang
Due to the vast address space of IPv6, the brute-force scanning methods originally applicable to IPv4 are no longer suitable for proactive scanning of IPv6. The recently proposed t…
Communication-Efficient Federated Learning with Adaptive Compression under Dynamic Bandwidth
Ying Zhuansun, Dandan Li, Xiaohong Huang +1
Federated learning can train models without directly providing local data to the server. However, the frequent updating of the local model brings the problem of large communication…
FedGraph: an Aggregation Method from Graph Perspective
Zhifang Deng, Xiaohong Huang, Dandan Li +1
With the increasingly strengthened data privacy act and the difficult data centralization, Federated Learning (FL) has become an effective solution to collaboratively train the mod…
Device-Independent Quantum Private Query Protocol without the Assumption of Perfect Detectors
Dan-Dan Li, Xiao-Hong Huang, Wei Huang +1
The first device-independent quantum private query protocol (MRT17) which is proposed by Maitra \emph{et al.} [Phys. Rev. A 95, 042344 (2017)] to enhance the security through the c…