Zobrazeno 1 - 10
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pro vyhledávání: '"Zhuowei An"'
The intertwining of electron-hole correlation and nontrivial topology is known to give rise to exotic topological excitonic insulators. Here, we show that the involvement of quantum geometry can lead to more exotic excitonic phases exhibiting physica
Externí odkaz:
http://arxiv.org/abs/2412.09305
Autor:
Guo, Peter L., Lin, Zhuowei
This paper investigates the number of supports of the Schubert polynomial $\mathfrak{S}_w(x)$ indexed by a permutation $w$. This number also equals the number of lattice points in the Newton polytope of $\mathfrak{S}_w(x)$. We establish a lower bound
Externí odkaz:
http://arxiv.org/abs/2412.02932
We study structural clustering on graphs in dynamic scenarios, where the graphs can be updated by arbitrary insertions or deletions of edges/vertices. The goal is to efficiently compute structural clustering results for any clustering parameters $\ep
Externí odkaz:
http://arxiv.org/abs/2411.13817
We prove a criterion of when the dual character $\chi_{D}(x)$ of the flagged Weyl module associated to a diagram $D$ in the grid $[n]\times [n]$ is zero-one, that is, the coefficients of monomials in $\chi_{D}(x)$ are either 0 or 1. This settles a co
Externí odkaz:
http://arxiv.org/abs/2411.10933
The FCC's National Broadband Map aspires to provide an unprecedented view into broadband availability in the US. However, this map, which also determines eligibility for public grant funding, relies on self-reported data from service providers that i
Externí odkaz:
http://arxiv.org/abs/2410.08518
Subject-driven text-to-image (T2I) customization has drawn significant interest in academia and industry. This task enables pre-trained models to generate novel images based on unique subjects. Existing studies adopt a self-reconstructive perspective
Externí odkaz:
http://arxiv.org/abs/2409.05606
Sentiment classification (SC) often suffers from low-resource challenges such as domain-specific contexts, imbalanced label distributions, and few-shot scenarios. The potential of the diffusion language model (LM) for textual data augmentation (DA) r
Externí odkaz:
http://arxiv.org/abs/2409.03203
Autor:
Wang, Xunzhi, Zhang, Zhuowei, Li, Qiongyu, Chen, Gaonan, Hu, Mengting, li, Zhiyu, Luo, Bitong, Gao, Hang, Han, Zhixin, Wang, Haotian
The rapid development of large language models (LLMs) has shown promising practical results. However, their low interpretability often leads to errors in unforeseen circumstances, limiting their utility. Many works have focused on creating comprehens
Externí odkaz:
http://arxiv.org/abs/2406.12784
Nested Named Entity Recognition (NNER) focuses on addressing overlapped entity recognition. Compared to Flat Named Entity Recognition (FNER), annotated resources are scarce in the corpus for NNER. Data augmentation is an effective approach to address
Externí odkaz:
http://arxiv.org/abs/2406.12779
Autor:
Li, Zhuowei, Xu, Zihao, Han, Ligong, Gao, Yunhe, Wen, Song, Liu, Di, Wang, Hao, Metaxas, Dimitris N.
In-context Learning (ICL) empowers large language models (LLMs) to adapt to unseen tasks during inference by prefixing a few demonstration examples prior to test queries. Despite its versatility, ICL incurs substantial computational and memory overhe
Externí odkaz:
http://arxiv.org/abs/2405.14660