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https://arxiv.org/html/2608.03480v1
com Arabic Institute for Translation, Algiers, Algeria CERIST, Algeria Nasredine Semmar CEA LIST, Paris-Saclay, France Hassina Aliane CERIST, Algeria
Abstract
The adoption of large pre-trained multilingual models for neural machine translation (MNMT) faces a major challenge: excessive memory and computational
https://arxiv.org/html/2607.28410v1
com/zaneopen/PACE
1 Introduction
Reducing execution costs is a central objective for financial institutions (Bertsimas and Lo 1998)
https://arxiv.org/html/2608.03154v1
com/COMBINI-Hub/Multi_Agent_Relation_Extraction
https://arxiv.org/pdf/2006.02318
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https://arxiv.org/pdf/2607.27188v1
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https://arxiv.org/pdf/2608.03883
CL journal 1613-0073 1 A arXiv GenPDF (tex2pdf:8def8d8) 2026-08-05T01:19:06+00:00 2026-08-05T01:19:06+00:00 2026-08-05T01:19:12
https://arxiv.org/pdf/2407.00125
) /Title (A Survey on Failure Analysis and Fault Injection in AI Systems) /Trapped /False /arXivID (https://arxiv
https://arxiv.org/pdf/2508.11152
com three Proceedings of ACM Conference (Conference'17) book 1 1 9 9 Tianjiao ZhaoJingrao LyuStokes JonesHarrison GarberStefano PasqualiDhagash Mehtahttp://arxiv
https://arxiv.org/list/cs.AI/new
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https://arxiv.org/html/2608.03452v1
And when a learner reproduces the pattern, does it thereby represent it, or only its visible alternations
https://arxiv.org/html/2608.02966v1
(c) Because these distractor preferences vary with ability, their identities provide Fisher information that correctness does not retain
https://arxiv.org/html/2609.03027v1
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https://arxiv.org/html/2607.27063v1
The design does not claim that every momentum or reversal episode is caused by herding; instead, it provides a disciplined mechanism through which herding can amplify informational price adjustment
https://arxiv.org/html/2607.28577v1
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https://arxiv.org/html/2608.03358v1
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https://arxiv.org/html/2608.03067v1
Computational Language Phenotypes in a Large Language Model
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https://arxiv.org/html/2607.28323v1
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https://arxiv.org/html/2608.02813v1
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https://arxiv.org/html/2608.03529v1
(2024), where a human expert and an automated system might describe information in different terms
https://arxiv.org/html/2608.03011v1
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https://arxiv.org/html/2407.13076v1
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LoRa, multigateway, system energy efficiency, matching-based, multiagent deep reinforcement learning
https://arxiv.org/pdf/2607.27070v1
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https://arxiv.org/pdf/2608.03157
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https://arxiv.org/pdf/2102.13654
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https://arxiv.org/pdf/2205.01882v5
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https://arxiv.org/pdf/2608.02817
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https://arxiv.org/html/2608.02971v1
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https://arxiv.org/html/2608.03233v1
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https://arxiv.org/html/2608.02918v1
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https://arxiv.org/pdf/2005.14165
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