Zobrazeno 1 - 10
of 5 090
pro vyhledávání: '"CAO, Rui"'
Autor:
Tang, Tianning, Chen, Yuntian, Cao, Rui, Mostert, Wouter, Taylor, Paul H., McAllister, Mark L., Tai, Bing, Ma, Yuxiang, Callaghan, Adrian H., Adcock, Thomas A. A.
Many supervised machine learning methods have revolutionised the empirical modelling of complex systems. These empirical models, however, are usually "black boxes" and provide only limited physical explanations about the underlying systems. Instead,
Externí odkaz:
http://arxiv.org/abs/2412.12348
Multimodal Large Language Models (MLLMs) can enhance trustworthiness by aligning with human preferences. As human preference labeling is laborious, recent works employ evaluation models for assessing MLLMs' responses, using the model-based assessment
Externí odkaz:
http://arxiv.org/abs/2411.13697
Unseen Object Instance Segmentation (UOIS) is crucial for autonomous robots operating in unstructured environments. Previous approaches require full supervision on large-scale tabletop datasets for effective pretraining. In this paper, we propose UOI
Externí odkaz:
http://arxiv.org/abs/2409.15481
Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by complex physiological processes. Previous research has predominantly focused on static cerebral interactions, often neglecting the brain's dynamic nature and the challen
Externí odkaz:
http://arxiv.org/abs/2409.06163
Autor:
Wang, Tianrui, Li, Jin, Ma, Ziyang, Cao, Rui, Chen, Xie, Wang, Longbiao, Ge, Meng, Wang, Xiaobao, Wang, Yuguang, Dang, Jianwu, Tashi, Nyima
Self-supervised learning (SSL) has garnered significant attention in speech processing, excelling in linguistic tasks such as speech recognition. However, jointly improving the performance of pre-trained models on various downstream tasks, each requi
Externí odkaz:
http://arxiv.org/abs/2409.00387
Autor:
Cao, Rui, Wang, Qiao
This research examines the use of Large Language Models (LLMs) in predicting time series, with a specific focus on the LLMTIME model. Despite the established effectiveness of LLMs in tasks such as text generation, language translation, and sentiment
Externí odkaz:
http://arxiv.org/abs/2408.04867
Surgical phase recognition is crucial for enhancing the efficiency and safety of computer-assisted interventions. One of the fundamental challenges involves modeling the long-distance temporal relationships present in surgical videos. Inspired by the
Externí odkaz:
http://arxiv.org/abs/2407.08333
Orbital degrees of freedom play an important role for understanding the emergence of unconventional quantum phases. Ultracold atomic gases in optical lattices provide a wonderful platform to simulate orbital physics. In this work, we consider spinles
Externí odkaz:
http://arxiv.org/abs/2407.00932
Unsupervised graph-level anomaly detection (UGAD) has attracted increasing interest due to its widespread application. In recent studies, knowledge distillation-based methods have been widely used in unsupervised anomaly detection to improve model ef
Externí odkaz:
http://arxiv.org/abs/2407.00383
Topological concepts have been employed to understand the ground states of many strongly correlated systems, but it is still quite unclear if and how topology manifests itself in the relaxation dynamics. Here we uncover emergent topological phenomena
Externí odkaz:
http://arxiv.org/abs/2406.04536