9 papers
Data Science and Technology Towards AGI Part I: Tiered Data Management
Yudong Wang, Zixuan Fu, Hengyu Zhao +14
The development of artificial intelligence can be viewed as an evolution of data-driven learning paradigms, with successive shifts in data organization and utilization continuously…
Beyond the Turn-Based Game: Enabling Real-Time Conversations with Duplex Models
Xinrong Zhang, Yingfa Chen, Shengding Hu +6
As large language models (LLMs) increasingly permeate daily lives, there is a growing demand for real-time interactions that mirror human conversations. Traditional turn-based chat…
RAGEval: Scenario Specific RAG Evaluation Dataset Generation Framework
Kunlun Zhu, Yifan Luo, Dingling Xu +10
Retrieval-Augmented Generation (RAG) is a powerful approach that enables large language models (LLMs) to incorporate external knowledge. However, evaluating the effectiveness of RA…
ProSparse: Introducing and Enhancing Intrinsic Activation Sparsity within Large Language Models
Chenyang Song, Xu Han, Zhengyan Zhang +8
Activation sparsity refers to the existence of considerable weakly-contributed elements among activation outputs. As a prevalent property of the models using the ReLU activation fu…
OneBit: Towards Extremely Low-bit Large Language Models
Yuzhuang Xu, Xu Han, Zonghan Yang +5
Model quantification uses low bit-width values to represent the weight matrices of existing models to be quantized, which is a promising approach to reduce both storage and computa…
Delta-CoMe: Training-Free Delta-Compression with Mixed-Precision for Large Language Models
Bowen Ping, Shuo Wang, Hanqing Wang +7
Fine-tuning is a crucial process for adapting large language models (LLMs) to diverse applications. In certain scenarios, such as multi-tenant serving, deploying multiple LLMs beco…