26 citations · 87 across the 12 of their papers we have counts for
12 papers
Unlocking Full Efficiency of Token Filtering in Large Language Model Training
Di Chai, Pengbo Li, Feiyuan Zhang +7
Token filtering has been proposed to enhance the utility of large language models (LLMs) by eliminating inconsequential tokens during training. While usingfewer tokens is expected…
Swift: Rethinking RDMA Control Plane for Elastic Computing
Junxue Zhang, Han Tian, Xinyang Huang +5
Elastic computing enables dynamic scaling to meet workload demands, and Remote Direct Memory Access (RDMA) enhances this by providing high-throughput, low-latency network communica…
FLASH-FHE: A Heterogeneous Architecture for Fully Homomorphic Encryption Acceleration
Junxue Zhang, Xiaodian Cheng, Gang Cao +6
While many hardware accelerators have recently been proposed to address the inefficiency problem of fully homomorphic encryption (FHE) schemes, none of them is able to deliver opti…
MixNet: A Runtime Reconfigurable Optical-Electrical Fabric for Distributed Mixture-of-Experts Training
Xudong Liao, Yijun Sun, Han Tian +13
Mixture-of-Expert (MoE) models outperform conventional models by selectively activating different subnets, named experts, on a per-token basis. This gated computation generates dyn…
PackVFL: Efficient HE Packing for Vertical Federated Learning
Liu Yang, Shuowei Cai, Di Chai +6
As an essential tool of secure distributed machine learning, vertical federated learning (VFL) based on homomorphic encryption (HE) suffers from severe efficiency problems due to d…
Towards Fair and Efficient Learning-based Congestion Control
Xudong Liao, Han Tian, Chaoliang Zeng +2
Recent years have witnessed a plethora of learning-based solutions for congestion control (CC) that demonstrate better performance over traditional TCP schemes. However, they fail…
Distributed Traffic Engineering in Hybrid Software Defined Networks: A Multi-agent Reinforcement Learning Framework
Yingya Guo, Qi Tang, Yulong Ma +2
Traffic Engineering (TE) is an efficient technique to balance network flows and thus improves the performance of a hybrid Software Defined Network (SDN). Previous TE solutions main…
A Survey on Vertical Federated Learning: From a Layered Perspective
Liu Yang, Di Chai, Junxue Zhang +6
Vertical federated learning (VFL) is a promising category of federated learning for the scenario where data is vertically partitioned and distributed among parties. VFL enriches th…
Multi-Objective Congestion Control
Yiqing Ma, Han Tian, Xudong Liao +4
Decades of research on Internet congestion control (CC) has produced a plethora of algorithms that optimize for different performance objectives. Applications face the challenge of…
Domain-specific Communication Optimization for Distributed DNN Training
Hao Wang, Jingrong Chen, Xinchen Wan +7
Communication overhead poses an important obstacle to distributed DNN training and draws increasing attention in recent years. Despite continuous efforts, prior solutions such as g…
Quantifying the Performance of Federated Transfer Learning
Qinghe Jing, Weiyan Wang, Junxue Zhang +2
The scarcity of data and isolated data islands encourage different organizations to share data with each other to train machine learning models. However, there are increasing conce…
Paper2vec: Citation-Context Based Document Distributed Representation for Scholar Recommendation
Han Tian, Hankz Hankui Zhuo
Due to the availability of references of research papers and the rich information contained in papers, various citation analysis approaches have been proposed to identify similar d…