Zobrazeno 1 - 10
of 66
pro vyhledávání: '"Azad, Amar"'
Large language models (LLMs) have demonstrated remarkable performance in a wide range of natural language tasks. However, as these models continue to grow in size, they face significant challenges in terms of computational costs. Additionally, LLMs o
Externí odkaz:
http://arxiv.org/abs/2308.03638
Autor:
Patel, Leena, Roy, Ashwin, Barlow, Jonathan, O'Shea, Christopher, Nieves, Daniel, Azad, Amar J., Hall, Caitlin, Davies, Ben, Rath, Phalguni, Pavlovic, Davor, Chikermane, Ashish, Geberhiwot, Tarekegn, Steeds, Richard P., Gehmlich, Katja
Publikováno v:
In Molecular Genetics and Metabolism September-October 2024 143(1-2)
Publikováno v:
EMNLP 2022
Contrastive explanations for understanding the behavior of black box models has gained a lot of attention recently as they provide potential for recourse. In this paper, we propose a method Contrastive Attributed explanations for Text (CAT) which pro
Externí odkaz:
http://arxiv.org/abs/2109.07983
Site Reliability Engineers (SREs) play a key role in issue identification and resolution. After an issue is reported, SREs come together in a virtual room (collaboration platform) to triage the issue. While doing so, they leave behind a wealth of inf
Externí odkaz:
http://arxiv.org/abs/2105.15065
The sudden widespread menace created by the present global pandemic COVID-19 has had an unprecedented effect on our lives. Man-kind is going through humongous fear and dependence on social media like never before. Fear inevitably leads to panic, spec
Externí odkaz:
http://arxiv.org/abs/2010.06906
Conversational channels are changing the landscape of hybrid cloud service management. These channels are becoming important avenues for Site Reliability Engineers (SREs) %Subject Matter Experts (SME) to collaboratively work together to resolve an in
Externí odkaz:
http://arxiv.org/abs/2010.05569
Despite the tremendous success of neural dialogue models in recent years, it suffers a lack of relevance, diversity, and some times coherence in generated responses. Lately, transformer-based models, such as GPT-2, have revolutionized the landscape o
Externí odkaz:
http://arxiv.org/abs/2010.05572
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Entity typing (ET) is the problem of assigning labels to given entity mentions in a sentence. Existing works for ET require knowledge about the domain and target label set for a given test instance. ET in the absence of such knowledge is a novel prob
Externí odkaz:
http://arxiv.org/abs/1810.08782
The goal behind Domain Adaptation (DA) is to leverage the labeled examples from a source domain so as to infer an accurate model in a target domain where labels are not available or in scarce at the best. A state-of-the-art approach for the DA is due
Externí odkaz:
http://arxiv.org/abs/1809.08097