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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?

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

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

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

https://arxiv.org/html/2608.03011v1
org perpetual non-exclusive license arXiv:2608

[2608.03883] DS@GT-ARC at eRisk 2026 Task 3: Sparse, Semantic, and LLM

https://arxiv.org/abs/2608.03883
Our systems combine sparse BM25 retrieval, evidence-aware rescoring for self-referential symptom reports, embedding-based reranking, query-prototype expansion, and LLM-based reranking

[2608.03860] SciRet: A Compute-Aware Empirical Study of Retrieval and

https://arxiv.org/abs/2608.03860
The pipeline combines sentence-window chunking, BM25, BGE-M3 dense retrieval, reciprocal rank fusion, optional cross-encoder reranking, and grounded answer generation

[2104.08663] BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of

https://arxiv.org/abs/2104.08663
Our results show BM25 is a robust baseline and re-ranking and late-interaction-based models on average achieve the best zero-shot performances, however, at high computational costs

Information Retrieval

https://arxiv.org/list/cs.IR/recent
IR) Tue, 4 Aug 2026 (showing first 34 of 45 entries ) [17] arXiv:2608

Mapping the City Through the Lens of Language Models

https://arxiv.org/html/2608.02971v1
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

On the Diversity of Analogy Making in Large Language Models

https://arxiv.org/html/2608.03233v1
1 Complete Results I Prompts License: arXiv

Efficient Audio Enhancement with a Differentiable Psychoacoustic Loss

https://arxiv.org/html/2608.02918v1
Miranda is also with LCTI, Télécom Paris, IP Paris, France

Internalizing Academic Writing Workflows for Introduction Generation via

https://arxiv.org/html/2608.03138v1
Struct-Aware Policy Learning 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

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https://arxiv.org/html/2608.03545v1
org perpetual non-exclusive license arXiv:2608

Geometric Cross-Modal Token Selection for Latency-Constrained Multimodal

https://arxiv.org/html/2608.03141v1
org perpetual non-exclusive license arXiv:2608

Decoupling Generation and Selection for Budget-Constrained Faithful

https://arxiv.org/html/2608.03655v1
org perpetual non-exclusive license arXiv:2608

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https://arxiv.org/pdf/2205.01882v5
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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

Guarding a Target Area from a Heterogeneous Group of Cooperative

https://arxiv.org/html/2407.00762v1
Attackers I Introduction II Problem Formulation II-A Notation II-B Problem Statement III Preliminary: Single-Attacker Game IV Main Results IV-A Optimization Formulation of a Geometric Solution IV-B Proof of Equilibrium V Numerical

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https://arxiv.org/pdf/2608.02817
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https://arxiv.org/pdf/2608.03095
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https://arxiv.org/pdf/2407.00225
-scale, Independent and Comprehensive study of the power of LLMs for test case generationWendkûuni C. OuédraogoKader KaboréYinghua LiHaoye TianAnil KoyuncuJacques KleinDavid LoTegawendé F. Bissyandéhttp://creativecommons.org/licenses

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https://arxiv.org/pdf/2608.03709
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