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Freshness: newest result fetched 26 d ago · median age of these results 26 d · 1 of 30 carry a fetch time

Approximating Choice Data by Discrete Choice Models

https://arxiv.org/html/2205.01882v5
2 Details of the DVD Dataset M Additional Empirical Application: Fishing-site Choice M

1 Introduction

https://arxiv.org/html/2407.16741v3
com/All-Hands-AI/OpenHands Slack http://bit

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https://arxiv.org/pdf/1911.06462
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Sphere Retraction Normalizations

https://arxiv.org/html/2608.02668v1
com/hazdzz/deep_connection \ncudata[Correspondence]Jie Zhang (), Correspondence: Cheng-Fang Su () “Geometry is not true, it is advantageous

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https://arxiv.org/pdf/2407.02510
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Can Large Language Models Execute Parent Orders?

https://arxiv.org/html/2607.28410v1
org perpetual non-exclusive license arXiv:2607

Asking Questions the Right Way: A Multi-Agent Conversational System for

https://arxiv.org/html/2608.01366v2
org perpetual non-exclusive license arXiv:2608

Optimizing Age of Information in Vehicular Edge Computing with Federated

https://arxiv.org/html/2407.02342v1
com/qiongwu86/Optimizing-AoI-in-VEC-with-Federated-Graph-Neural-Network-Multi-Agent-Reinforcement-Learnin

Computation and Language

https://arxiv.org/list/cs.CL/new
We evaluate five open-weight readers with Vanilla context, BM25-RAG, Oracle retrieval, Memobase, and MemSearch as memory backends

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https://arxiv.org/pdf/2006.00441
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https://arxiv.org/pdf/2510.03215
7 % 1 0 obj > endobj 2 0 obj > endobj 3 0 obj > stream Cache-to-Cache: Direct Semantic Communication Between Large Language ModelsTianyu FuZihan MinHanling ZhangJichao YanGuohao DaiWanli OuyangYu Wanghttp://arxiv

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https://arxiv.org/pdf/2006.00064
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https://arxiv.org/pdf/2006.15704
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https://arxiv.org/pdf/2402.03300
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[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

[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

[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

Information Retrieval

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

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

Artificial Intelligence

https://arxiv.org/list/cs.AI/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 Artificial Intelligence New submissions Cross-lists Replacements See recent

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https://arxiv.org/pdf/2604.05327v4
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https://arxiv.org/pdf/2507.17609
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https://arxiv.org/pdf/2608.01861
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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
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Report GitHub Issue

https://arxiv.org/html/2609.03103v1
Report GitHub Issue Description: arXiv is now an independent nonprofit

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!

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

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

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

What Language Does and What the Evidence Supports: A Functional Role

https://arxiv.org/html/2608.03099v1
Taxonomy and Evidence Audit of Language Grounding in Embodied Agents Report GitHub Issue × Title: Content selection saved. Describe the issue below: Description: Submit without GitHub Submit in GitHub arXiv is now an independent