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How does DRS improve the performance of VMs? 


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Dense Retrieval (DR) techniques improve the performance of virtual machines (VMs) by encoding queries and documents into a low-dimensional dense space and conducting effective semantic matching . DR models trained with large-scale supervised data can achieve this. However, when trained DR models are used in a target domain different from the labeled data, their effectiveness drops significantly . To address this, a novel DR framework called Disentangled Dense Retrieval (DDR) has been proposed. DDR supports effective and flexible domain adaptation for DR models by using a Relevance Estimation Module (REM) for modeling domain-invariant matching patterns and several Domain Adaptation Modules (DAMs) for modeling domain-specific features of multiple target corpora . DDR significantly improves ranking performance compared to strong DR baselines and traditional retrieval methods .

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Papers (5)Insight
The provided paper does not mention anything about DRS (Distributed Resource Scheduler) and its impact on improving the performance of VMs.
Open accessJournal ArticleDOI
Sulistiyani Sulistiyani, Roh Prihati 
26 Mar 2020
3 Citations
The provided paper does not mention anything about DRS or how it improves the performance of VMs. The paper focuses on analyzing the influence of psychological empowerment, effort, and satisfaction on performance in a specific context.
Open accessDissertation
25 Apr 2013
1 Citations
The provided paper does not mention anything about DRS or how it improves the performance of VMs. The paper focuses on the relationship between organisational energy and organisational performance.
Open access
01 Jan 2013
1 Citations
The provided paper does not mention anything about DRS or how it improves the performance of VMs. The paper is a template for MPMM 2013 and does not provide any specific information on a particular topic.
The provided paper is about Disentangled Dense Retrieval (DDR) and does not mention anything about improving the performance of VMs.

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