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Efficient Multilingual Neural Machine Translation via Corpus-Driven

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

Can Large Language Models Execute Parent Orders?

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)

Report GitHub Issue

https://arxiv.org/html/2608.03154v1
com/COMBINI-Hub/Multi_Agent_Relation_Extraction

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https://arxiv.org/pdf/2607.27188v1
pËyFþÐE®Ë¡F£;¸å{ºƒ[¾WÎ4šr ‘ŠÚë®ׯ»_àÙRëŽÞÏv×®+÷ËÞ>S¶ÆíŸÚ‚Rv‘|u ŠîŽ|žØ‚Ò= Ê韥øÚ”ó~ò"È'àìOuüZwE”ªGŒá£i›Dˆ§óÉÓwX )¨›¥,Á‰€Pæu‘í¯´n&ß‘¿ÍÛü«v"RÞX`> stream xœÅ[]sÛ6}ß_�·Mg7$¾îììL7©w“&mÒ4ÝNh™¶¸–E•’Ó¸¿~ÏIYveËÓéxh@äppïÅýHã´�Â8#¬GaE¡Q8¡LDé…ŠeÚ(”QèÀû…0÷=ZÐ{%¬Â=¯Ñ ïáè½m îyiQzáïá Þ�"Xƒ²

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https://arxiv.org/pdf/2407.00125
Reliability.Performance.- Software and its engineering -> Software organization and properties.- Computing methodologies -> Artificial intelligence.) /Title (A Survey on Failure Analysis and Fault Injection in AI Systems) /Trapped /False

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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

Global coal trade is resilient to maritime chokepoints

https://arxiv.org/html/2608.00328v2
The exception is a restriction to maritime traffic in the South and East China Sea, which could raise costs by 10 $/t for China, whilst reducing costs for other importers in the region by similar levels

Inverse Learning of Latent Risk-Neutral Densities from Irregular Option

https://arxiv.org/html/2607.27188v1
5 Real NIFTY data: adaptation helps but does not close the gap 6 Discussion 6

MDGAM-Based Cooperative Task Scheduling for Communication-Constrained

https://arxiv.org/html/2608.00648v1
Distributed Multi-Agent Systems Report GitHub Issue × Title: Content selection saved. Describe the issue below: Description: Submit without GitHub Submit in GitHub arXiv is now an independent nonprofit! Learn more × Back to arXiv

Multi-agent Off-policy Actor-Critic Reinforcement Learning for Partially

https://arxiv.org/html/2407.04974v1
Unlike many existing dec-POMDP-based RL approaches, the proposed algorithm is suitable for model-free multi-agent reinforcement learning as it does not require knowledge of a transition model

Information Retrieval

https://arxiv.org/list/cs.IR/new
Skip to main content System maintenance August 4th and 5th Learn more × Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Information Retrieval New submissions Cross-lists Replacements See recent

Probing Character-level Transformers for the Spanish L-shaped Morphome

https://arxiv.org/html/2608.03452v1
And when a learner reproduces the pattern, does it thereby represent it, or only its visible alternations

Every Wrong Answer Counts: Option-Level Psychometrics for LLM Multiple

https://arxiv.org/html/2608.02966v1
(c) Because these distractor preferences vary with ability, their identities provide Fisher information that correctness does not retain

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https://arxiv.org/html/2609.03027v1
Such compromises could severely curtail their potential to discover transient phenomena

Herding, Momentum, and Reversal in China’s A-Share Market: An Agent

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

Train Often, Deploy Selectively: Forward-Gated Model Replacement in

https://arxiv.org/html/2607.28577v1
Production forecasting systems retrain models regularly, but a retrained candidate does not necessarily outperform a continuously maintained incumbent that has continued to learn

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https://arxiv.org/html/2608.03358v1
However, it does not satisfy these requirements

Activation-Guided Neuron Intervention to Induce Alzheimer’s-Related

https://arxiv.org/html/2608.03067v1
Computational Language Phenotypes in a Large Language Model Report GitHub Issue × Title: Content selection saved. Describe the issue below: Description: Submit without GitHub Submit in GitHub arXiv is now an independent nonprofit!

Optimal Execution with Passive Market Impact

https://arxiv.org/html/2607.28323v1
Report GitHub Issue × Title: Content selection saved. Describe the issue below: Description: Submit without GitHub Submit in GitHub arXiv is now an independent nonprofit! Learn more × Back to arXiv Why HTML? Report Issue Back to

Consensus Measures for Unstructured Biomedical Text Annotations

https://arxiv.org/html/2608.03529v1
(2024), where a human expert and an automated system might describe information in different terms

Coordinated Primary Frequency Regulation and Grid-Forming Control for

https://arxiv.org/html/2608.02813v1
Wind Turbine Generators Report GitHub Issue × Title: Content selection saved. Describe the issue below: Description: Submit without GitHub Submit in GitHub arXiv is now an independent nonprofit! Learn more × Back to arXiv Why HTML?

Towards Real-world Environment-aware Zero-shot Text-to-speech Synthesis

https://arxiv.org/html/2608.03011v1
via Disentangled Audio Infilling Report GitHub Issue × Title: Content selection saved. Describe the issue below: Description: Submit without GitHub Submit in GitHub arXiv is now an independent nonprofit! Learn more × Back to arXiv

Matching-Driven Deep Reinforcement Learning for Energy-Efficient

https://arxiv.org/html/2407.13076v1
Index Terms: LoRa, multigateway, system energy efficiency, matching-based, multiagent deep reinforcement learning

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https://arxiv.org/pdf/2005.14165
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https://arxiv.org/pdf/2607.27070v1
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https://arxiv.org/pdf/2608.02758
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https://arxiv.org/pdf/2402.03300
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https://arxiv.org/pdf/2608.03118
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https://arxiv.org/pdf/2407.02510
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https://arxiv.org/src/2006.02759
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