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of 1 921
pro vyhledávání: '"ZHANG, Haoyu"'
Vision-Language (V-L) pre-trained models such as CLIP show prominent capabilities in various downstream tasks. Despite this promise, V-L models are notoriously limited by their inherent social biases. A typical demonstration is that V-L models often
Externí odkaz:
http://arxiv.org/abs/2411.12785
Autor:
Subirana-Granés, Marc, Hoffman, Jill, Zhang, Haoyu, Akirtava, Christina, Nandi, Sutanu, Fotso, Kevin, Pividori, Milton
Understanding the genetic basis of complex traits is a longstanding challenge in the field of genomics. Genome-wide association studies (GWAS) have identified thousands of variant-trait associations, but most of these variants are located in non-codi
Externí odkaz:
http://arxiv.org/abs/2410.23425
Autor:
Zhang, Haoyu, Liu, Jun, Zhu, Zhenhua, Zeng, Shulin, Sheng, Maojia, Yang, Tao, Dai, Guohao, Wang, Yu
ANNS for embedded vector representations of texts is commonly used in information retrieval, with two important information representations being sparse and dense vectors. While it has been shown that combining these representations improves accuracy
Externí odkaz:
http://arxiv.org/abs/2410.20381
The field of Multimodal Sentiment Analysis (MSA) has recently witnessed an emerging direction seeking to tackle the issue of data incompleteness. Recognizing that the language modality typically contains dense sentiment information, we consider it as
Externí odkaz:
http://arxiv.org/abs/2409.20012
Accurately reconstructing dense and semantically annotated 3D meshes from monocular images remains a challenging task due to the lack of geometry guidance and imperfect view-dependent 2D priors. Though we have witnessed recent advancements in implici
Externí odkaz:
http://arxiv.org/abs/2409.14019
Face morphing attack detection (MAD) algorithms have become essential to overcome the vulnerability of face recognition systems. To solve the lack of large-scale and public-available datasets due to privacy concerns and restrictions, in this work we
Externí odkaz:
http://arxiv.org/abs/2409.05595
Autor:
Jiang, Xinke, Fang, Yue, Qiu, Rihong, Zhang, Haoyu, Xu, Yongxin, Chen, Hao, Zhang, Wentao, Zhang, Ruizhe, Fang, Yuchen, Chu, Xu, Zhao, Junfeng, Wang, Yasha
In the pursuit of enhancing domain-specific Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) emerges as a promising solution to mitigate issues such as hallucinations, outdated knowledge, and limited expertise in highly specialized
Externí odkaz:
http://arxiv.org/abs/2408.09199
Mendelian randomization (MR) is a widely used tool for causal inference in the presence of unobserved confounders, which uses single nucleotide polymorphisms (SNPs) as instrumental variables (IVs) to estimate causal effects. However, SNPs often have
Externí odkaz:
http://arxiv.org/abs/2408.05386
In the field of autonomous systems, accurately predicting the trajectories of nearby vehicles and pedestrians is crucial for ensuring both safety and operational efficiency. This paper introduces a novel methodology for trajectory forecasting based o
Externí odkaz:
http://arxiv.org/abs/2408.12609
Single-pixel imaging (SPI) using a single-pixel detector is an unconventional imaging method, which has great application prospects in many fields to realize high-performance imaging. In especial, the recent proposed catadioptric panoramic ghost imag
Externí odkaz:
http://arxiv.org/abs/2407.19130