Zobrazeno 1 - 10
of 69
pro vyhledávání: '"Lotfi, Ehsan"'
Zero-shot evaluation of information retrieval (IR) models is often performed using BEIR; a large and heterogeneous benchmark composed of multiple datasets, covering different retrieval tasks across various domains. Although BEIR has become a standard
Externí odkaz:
http://arxiv.org/abs/2412.08329
Statutory article retrieval plays a crucial role in making legal information more accessible to both laypeople and legal professionals. Multilingual countries like Belgium present unique challenges for retrieval models due to the need for handling le
Externí odkaz:
http://arxiv.org/abs/2412.07462
Automatic evaluation of open-domain dialogs remains an unsolved problem. Moreover, existing methods do not correlate strongly with human annotations. This paper presents a new automated evaluation method using follow-ups: we measure the probability t
Externí odkaz:
http://arxiv.org/abs/2209.05185
Knowledge Grounded Conversation Models (KGCM) are usually based on a selection/retrieval module and a generation module, trained separately or simultaneously, with or without having access to a gold knowledge option. With the introduction of large pr
Externí odkaz:
http://arxiv.org/abs/2110.02067
In this paper, we present the first multilingual FAQ dataset publicly available. We collected around 6M FAQ pairs from the web, in 21 different languages. Although this is significantly larger than existing FAQ retrieval datasets, it comes with its o
Externí odkaz:
http://arxiv.org/abs/2109.12870
Knowledgeable FAQ chatbots are a valuable resource to any organization. While powerful and efficient retrieval-based models exist for English, it is rarely the case for other languages for which the same amount of training data is not available. In t
Externí odkaz:
http://arxiv.org/abs/2108.00719
Autor:
Lotfi, Ehsan
The ozone level prediction is an important task of air quality agencies of modern cities. In this paper, we design an ozone level alarm system (OLP) for Isfahan city and test it through the real word data from 1-1-2000 to 7-6-2011. We propose a compu
Externí odkaz:
http://arxiv.org/abs/1511.02420
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Autor:
Lotfi, Ehsan1 ehsanelotfy@gmail.com, Isfahani, Saeed Aibaghi1 saeed.aibaghi@gmail.com
Publikováno v:
Innovation Management & Operational Strategies. 12/1/2021, Vol. 2 Issue 4, p420-733. 15p.
