9 citations · 18 across the 11 of their papers we have counts for
5 papers · 1 filter
DynSplit-KV: Dynamic Semantic Splitting for KVCache Compression in Efficient Long-Context LLM Inference
Jiancai Ye, Jun Liu, Qingchen Li +5
Although Key-Value (KV) Cache is essential for efficient large language models (LLMs) inference, its growing memory footprint in long-context scenarios poses a significant bottlene…
SOFA-FL: Self-Organizing Hierarchical Federated Learning with Adaptive Clustered Data Sharing
Yi Ni, Xinkun Wang, Han Zhang
Federated Learning (FL) faces significant challenges in evolving environments, particularly regarding data heterogeneity and the rigidity of fixed network topologies. To address th…
ODIA: Oriented Distillation for Inline Acceleration of LLM-based Function Calling
Hanlong Zhang, Jingsheng Yang, Hao Li +2
Function Calling is a crucial technique that enables Large Language Models (LLMs) to interact with external systems through APIs. However, the high latency associated with LLM-base…
Assay2Mol: large language model-based drug design using BioAssay context
Yifan Deng, Spencer S. Ericksen, Anthony Gitter
Scientific databases aggregate vast amounts of quantitative data alongside descriptive text. In biochemistry, molecule screening assays evaluate candidate molecules' functional res…
Distributed Equivalent Substitution Training for Large-Scale Recommender Systems
Haidong Rong, Yangzihao Wang, Feihu Zhou +8
We present Distributed Equivalent Substitution (DES) training, a novel distributed training framework for large-scale recommender systems with dynamic sparse features. DES introduc…