360 citations · 645 across the 47 of their papers we have counts for
6 papers · 1 filter
CorDA: Context-Oriented Decomposition Adaptation of Large Language Models for Task-Aware Parameter-Efficient Fine-tuning
Yibo Yang, Xiaojie Li, Zhongzhu Zhou +4
Current parameter-efficient fine-tuning (PEFT) methods build adapters widely agnostic of the context of downstream task to learn, or the context of important knowledge to maintain.…
WKVQuant: Quantizing Weight and Key/Value Cache for Large Language Models Gains More
Yuxuan Yue, Zhihang Yuan, Haojie Duanmu +3
Large Language Models (LLMs) face significant deployment challenges due to their substantial memory requirements and the computational demands of auto-regressive text generation pr…
Neural Collapse Terminus: A Unified Solution for Class Incremental Learning and Its Variants
Yibo Yang, Haobo Yuan, Xiangtai Li +6
How to enable learnability for new classes while keeping the capability well on old classes has been a crucial challenge for class incremental learning. Beyond the normal case, lon…
Maximum-and-Concatenation Networks
Xingyu Xie, Hao Kong, Jianlong Wu +3
While successful in many fields, deep neural networks (DNNs) still suffer from some open problems such as bad local minima and unsatisfactory generalization performance. In this wo…
Dynamical System Inspired Adaptive Time Stepping Controller for Residual Network Families
Yibo Yang, Jianlong Wu, Hongyang Li +3
The correspondence between residual networks and dynamical systems motivates researchers to unravel the physics of ResNets with well-developed tools in numeral methods of ODE syste…
Differentiable Linearized ADMM
Xingyu Xie, Jianlong Wu, Zhisheng Zhong +2
Recently, a number of learning-based optimization methods that combine data-driven architectures with the classical optimization algorithms have been proposed and explored, showing…