Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Feng, Zhangchi"'
Autor:
Nie, Zhijie, Feng, Zhangchi, Li, Mingxin, Zhang, Cunwang, Zhang, Yanzhao, Long, Dingkun, Zhang, Richong
Text embedding has become a foundational technology in natural language processing (NLP) during the deep learning era, driving advancements across a wide array of downstream tasks. While many natural language understanding challenges can now be model
Externí odkaz:
http://arxiv.org/abs/2412.09165
This paper presents EasyRAG, a simple, lightweight, and efficient retrieval-augmented generation framework for automated network operations. Our framework has three advantages. The first is accurate question answering. We designed a straightforward R
Externí odkaz:
http://arxiv.org/abs/2410.10315
Cross-lingual Cross-modal Retrieval (CCR) is an essential task in web search, which aims to break the barriers between modality and language simultaneously and achieves image-text retrieval in the multi-lingual scenario with a single model. In recent
Externí odkaz:
http://arxiv.org/abs/2406.18254
The Composed Image Retrieval (CIR) task aims to retrieve target images using a composed query consisting of a reference image and a modified text. Advanced methods often utilize contrastive learning as the optimization objective, which benefits from
Externí odkaz:
http://arxiv.org/abs/2404.11317
Autor:
Zheng, Yaowei, Zhang, Richong, Zhang, Junhao, Ye, Yanhan, Luo, Zheyan, Feng, Zhangchi, Ma, Yongqiang
Efficient fine-tuning is vital for adapting large language models (LLMs) to downstream tasks. However, it requires non-trivial efforts to implement these methods on different models. We present LlamaFactory, a unified framework that integrates a suit
Externí odkaz:
http://arxiv.org/abs/2403.13372
Neural Radiance Field (NeRF) has received much attention in recent years due to the impressively high quality in 3D scene reconstruction and novel view synthesis. However, image degradation caused by the scattering of atmospheric light and object lig
Externí odkaz:
http://arxiv.org/abs/2304.11448
Publikováno v:
Inclusive Smart Cities & Digital Health; 2016, p477-488, 12p
