103 citations · 290 across the 30 of their papers we have counts for
6 papers · 1 filter
Q-Boost: On Visual Quality Assessment Ability of Low-level Multi-Modality Foundation Models
Zicheng Zhang, Haoning Wu, Zhongpeng Ji +9
Recent advancements in Multi-modality Large Language Models (MLLMs) have demonstrated remarkable capabilities in complex high-level vision tasks. However, the exploration of MLLM p…
A Theory of Non-Acyclic Generative Flow Networks
Leo Maxime Brunswic, Yinchuan Li, Yushun Xu +2
GFlowNets is a novel flow-based method for learning a stochastic policy to generate objects via a sequence of actions and with probability proportional to a given positive reward.…
Trust your Good Friends: Source-free Domain Adaptation by Reciprocal Neighborhood Clustering
Shiqi Yang, Yaxing Wang, Joost van de Weijer +3
Domain adaptation (DA) aims to alleviate the domain shift between source domain and target domain. Most DA methods require access to the source data, but often that is not possible…
Ternary Singular Value Decomposition as a Better Parameterized Form in Linear Mapping
Boyu Chen, Hanxuan Chen, Jiao He +2
We present a simple yet novel parameterized form of linear mapping to achieves remarkable network compression performance: a pseudo SVD called Ternary SVD (TSVD). Unlike vanilla SV…
Reparameterization through Spatial Gradient Scaling
Alexander Detkov, Mohammad Salameh, Muhammad Fetrat Qharabagh +4
Reparameterization aims to improve the generalization of deep neural networks by transforming convolutional layers into equivalent multi-branched structures during training. Howeve…
A General-Purpose Transferable Predictor for Neural Architecture Search
Fred X. Han, Keith G. Mills, Fabian Chudak +6
Understanding and modelling the performance of neural architectures is key to Neural Architecture Search (NAS). Performance predictors have seen widespread use in low-cost NAS and…