Zobrazeno 1 - 10
of 22 690
pro vyhledávání: '"retrieval model"'
Autor:
Liu, Chi, Cao, Jiangxia, Huang, Rui, Cai, Kuo, Ding, Weifeng, Luo, Qiang, Gai, Kun, Zhou, Guorui
Recommendation systems (RecSys) are designed to connect users with relevant items from a vast pool of candidates while aligning with the business goals of the platform. A typical industrial RecSys is composed of two main stages, retrieval and ranking
Externí odkaz:
http://arxiv.org/abs/2412.13844
Autor:
Zhao, Zijia, Guo, Longteng, Yue, Tongtian, Hu, Erdong, Shao, Shuai, Yuan, Zehuan, Huang, Hua, Liu, Jing
In this paper, we investigate the task of general conversational image retrieval on open-domain images. The objective is to search for images based on interactive conversations between humans and computers. To advance this task, we curate a dataset c
Externí odkaz:
http://arxiv.org/abs/2410.18715
Given the large number of Hindi speakers worldwide, there is a pressing need for robust and efficient information retrieval systems for Hindi. Despite ongoing research, comprehensive benchmarks for evaluating retrieval models in Hindi are lacking. To
Externí odkaz:
http://arxiv.org/abs/2409.05401
In-context learning (ICL) enables large language models (LLMs) to generalize to new tasks by incorporating a few in-context examples (ICEs) directly in the input, without updating parameters. However, the effectiveness of ICL heavily relies on the se
Externí odkaz:
http://arxiv.org/abs/2410.02203
A supervised ranking model, despite its advantage of being effective, usually involves complex processing - typically multiple stages of task-specific pre-training and fine-tuning. This has motivated researchers to explore simpler pipelines leveragin
Externí odkaz:
http://arxiv.org/abs/2409.17745
In this technical report, we describe our submission to DCASE2024 Challenge Task6 (Automated Audio Captioning) and Task8 (Language-based Audio Retrieval). We develop our approach building upon the EnCLAP audio captioning framework and optimizing it f
Externí odkaz:
http://arxiv.org/abs/2409.01160
Deploying dense retrieval models efficiently is becoming increasingly important across various industries. This is especially true for enterprise search services, where customizing search engines to meet the time demands of different enterprises in d
Externí odkaz:
http://arxiv.org/abs/2401.12540
Ranker and retriever are two important components in dense passage retrieval. The retriever typically adopts a dual-encoder model, where queries and documents are separately input into two pre-trained models, and the vectors generated by the models a
Externí odkaz:
http://arxiv.org/abs/2312.16821
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.