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30 result(s) for “okapi bm25 site hotchips pp site www toffeeweb com site www key org site:arxiv.org” of 126 matched · 461 ms

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For each evaluation sample, we construct an Okapi BM25 index over its decoded text chunks; the index is therefore sample-specific rather than a shared external knowledge base
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https://arxiv.org/html/2608.03048v1
com/JetAstra/PI-Mem Introduction The ability to reason over long contexts is increasingly important for large language models (LLMs), supporting applications such as long-document question answering (Gemini Team 2025; Yang et al

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https://arxiv.org/html/2608.02613v1
We evaluate five open-weight readers with Vanilla context, BM25-RAG, Oracle retrieval, Memobase, and MemSearch as memory backends

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/2501.13956v1
com Abstract We introduce Zep, a novel memory layer service for AI agents that outperforms the current state-of-the-art system, MemGPT, in the Deep Memory Retrieval (DMR) benchmark

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

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

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

1 Introduction

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

Geometric Cross-Modal Token Selection for Latency-Constrained Multimodal

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

Global coal trade is resilient to maritime chokepoints

https://arxiv.org/html/2608.00328v2
org perpetual non-exclusive license arXiv:2608

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/html/2609.03159v1
Description: arXiv is now an independent nonprofit

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https://arxiv.org/pdf/2608.03883
3/ pdfx PDF/X Schema external URL to an online version or preprint AuthoritativeDomain Text http://www

Efficient Multilingual Neural Machine Translation via Corpus-Driven

https://arxiv.org/html/2608.03480v1
org perpetual non-exclusive license arXiv:2608

Optimizing Age of Information in Vehicular Edge Computing with Federated

https://arxiv.org/html/2407.02342v1
org) Wen Chen is with the Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai 200240, China(e-mail: wenchen@sjtu

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https://arxiv.org/pdf/2608.02758
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https://arxiv.org/html/2608.03358v1
org perpetual non-exclusive license arXiv:2608

Matching-Driven Deep Reinforcement Learning for Energy-Efficient

https://arxiv.org/html/2407.13076v1
Gateway LoRa Networks Ziqi Lin, Xu Zhang, Shimin Gong,  Lanhua Li, Zhou Su,  and Bo Gu This work was supported in part by the National Science Foundation of China (NSFC) under Grant U20A20175 and in part by the National Key R&D Program of China under Grant 2020YFB1713800

Rainfall is rough

https://arxiv.org/html/2607.27099v1
org perpetual non-exclusive license arXiv:2607

Finance-Informed Neural Network: Learning the Geometry of Option Pricing

https://arxiv.org/html/2412.12213v2
The key idea underlying FINN is to replace supervision by observed option prices with a self-supervised, economically grounded training signal

Automatic Patient-Specific Microwave Ablation Planning Accelerated by a

https://arxiv.org/html/2608.03086v1
org perpetual non-exclusive license arXiv:2608

Can Large Language Models Execute Parent Orders?

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

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https://arxiv.org/html/2608.03154v1
org perpetual non-exclusive license arXiv:2608

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https://arxiv.org/pdf/2005.14165
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https://arxiv.org/pdf/2407.02510
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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/src/2006.02759
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https://arxiv.org/src/2006.01048
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https://arxiv.org/pdf/2407.00125
) /Title (A Survey on Failure Analysis and Fault Injection in AI Systems) /Trapped /False /arXivID (https://arxiv

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https://arxiv.org/pdf/2006.00342
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