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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

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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

1 Introduction

https://arxiv.org/html/2501.13956v1
Consequently, additional context is required to provide out-of-domain (OOD) knowledge and reduce hallucinations

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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

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

https://arxiv.org/html/2608.03067v1
Beyond their use as predictors, pretrained language models have also become tools for examining how linguistic information is organized in internal representations that can support AD prediction (Balagopalan et al

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

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https://arxiv.org/pdf/2402.03300
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https://arxiv.org/pdf/2608.02758
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https://arxiv.org/pdf/2407.02510
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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

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https://arxiv.org/src/2006.01048
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https://arxiv.org/pdf/2508.04671
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https://arxiv.org/src/2303.12712
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Computation and Language

https://arxiv.org/list/cs.CL/new
Many practically important problems are naturally treated as black-box optimization (BBO) problems, in which only objective values are observable, and the functional form is unavailable

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

https://arxiv.org/abs/2608.03883
arXiv is committed to these values and only works with partners that adhere to them

[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
arXiv is committed to these values and only works with partners that adhere to them

Global coal trade is resilient to maritime chokepoints

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

Rainfall is rough

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

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https://arxiv.org/pdf/2608.03157
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Inverse Learning of Latent Risk-Neutral Densities from Irregular Option

https://arxiv.org/html/2607.27188v1
org perpetual non-exclusive license arXiv:2607

Automatic Patient-Specific Microwave Ablation Planning Accelerated by a

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

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

https://arxiv.org/html/2607.28577v1
org perpetual non-exclusive license arXiv:2607

Report GitHub Issue

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

Efficient Multilingual Neural Machine Translation via Corpus-Driven

https://arxiv.org/html/2608.03480v1
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/2608.00458v1
org perpetual non-exclusive license arXiv:2608

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

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

Efficient Audio Enhancement with a Differentiable Psychoacoustic Loss

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

On the Diversity of Analogy Making in Large Language Models

https://arxiv.org/html/2608.03233v1
org perpetual non-exclusive license arXiv:2608

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