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26 result(s) for “okapi bm25 site allegrolokalnie pp site www simplest org br site provide com site:arxiv.org” · 683 ms

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The query asks the model to recall the topic of an earlier conversation about Tesla; the gold answer is anchored in one specific session about Pooja’s dig site
from the top result below

Report GitHub Issue

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

Producing Policy Recommendations: from Statistical Decision Theory to

https://arxiv.org/html/2607.29281v2
First, I focus on theoretical contributions in econometrics and provide a general framework that nests all the contexts and results reviewed using a coherent notation and narrative

Can Large Language Models Execute Parent Orders?

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

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

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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

Efficient Audio Enhancement with a Differentiable Psychoacoustic Loss

https://arxiv.org/html/2608.02918v1
org perpetual non-exclusive license arXiv:2608

1 Introduction

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

Computation and Language

https://arxiv.org/list/cs.CL/new
Using this benchmark, we provide the first evaluation of LLMs and show that current LLMs are capable of selecting suitable algorithms based on the given evaluation budget

Consensus Measures for Unstructured Biomedical Text Annotations

https://arxiv.org/html/2608.03529v1
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

General Relativity and Quantum Cosmology

https://arxiv.org/list/gr-qc/new
This leads to loud signals that provide new tests of gravity

Preying on Leveraged ETFsPreliminary and incomplete. This project was

https://arxiv.org/html/2608.03703v1
index complexes and leveraged volatility products — impact per unit of flow is modest, declines in predictability, and is partly offset by contrarian flows into and out of the funds (Ivanov and Lenkey 2018; Brøgger 2021; Barbon et al

Artificial Intelligence

https://arxiv.org/list/cs.AI/new
We provide our implementation as an open-source framework to enable more diverse and creative AI deployments

Mathematics

https://arxiv.org/list/math/new
up to 2000 entries per page: fewer | more | all New submissions (showing 219 of 219 entries) [1] arXiv:2608

Predicting Multilingual Classification and Translation Performance of

https://arxiv.org/html/2608.03446v1
org perpetual non-exclusive license arXiv:2608

Beyond Initialization Loss: A Systematic Study of Token Embedding

https://arxiv.org/html/2608.03494v1
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

Information Retrieval

https://arxiv.org/list/cs.IR/new
We provide the core implementation of KGD at this https URL

[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

[astro-ph/9901052] Constraining dark energy with SNe Ia and large-scale

https://arxiv.org/abs/astro-ph/9901052
The simplest explanation, a cosmological constant, is consistent with this, while some of the other possibilities are not

[1810.09420] LHC Dark Matter Working Group: Next-generation spin-0 dark

https://arxiv.org/abs/1810.09420
09420] LHC Dark Matter Working Group: Next-generation spin-0 dark matter models Skip to main content Learn about arXiv becoming an independent nonprofit

[1808.05288] Processes that break baryon number by two units and the

https://arxiv.org/abs/1808.05288
of the neutrino, by Susan Gardner and 1 other authors View PDF HTML (experimental) Abstract:We employ the simplest possible models of scalar-fermion interactions that are consistent with the gauge symmetries of the Standard Model and permit no proton decay to analyze the connections possible among processes that

Untitled Document

https://arxiv.org/html/2607.28294v1
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Information Retrieval

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

Eliminating Majority Illusion is Easy

https://arxiv.org/html/2407.20187v1
One of the simplest manifestation of majority illusion concerns election

1 Introduction

https://arxiv.org/html/2608.03486v1
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