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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
2 pp, exceeding MemSearch reader scaling (+10

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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

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https://arxiv.org/html/2609.02852v1
Report GitHub Issue Description: arXiv is now an independent nonprofit

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

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

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https://arxiv.org/html/2608.03063v1
8 pp in a production fraud detector serving billion-scale transaction traffic

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

https://arxiv.org/html/2608.03099v1
In other systems, it directly conditions the action policy (Zitkovich et al

When Collaboration Becomes a Trigger:Collective Evidence-Threshold

https://arxiv.org/html/2608.01085v1
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

Decoupling Generation and Selection for Budget-Constrained Faithful

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

Learning to Control Unknown Strongly Monotone Games

https://arxiv.org/html/2407.00575v3
In large-scale systems, obtaining performance guarantees is challenging even with cooperative players since they do not know the reward functions of their peers

Effort-Centric Fairness in Lending Decisions

https://arxiv.org/html/2607.28847v1
The European Union’s Artificial Intelligence Act classifies creditworthiness assessment as a high-risk application, requiring that automated systems undergo rigorous fairness evaluation before deployment and throughout their operational lifecycle (European Parliament, 2024)

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

Computation and Language

https://arxiv.org/list/cs.CL/new
2 pp, exceeding MemSearch reader scaling (+10

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

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

Coordinated Primary Frequency Regulation and Grid-Forming Control for

https://arxiv.org/html/2608.02813v1
Recently, grid-forming (GFM) control has emerged as a promising solution for future power systems with high renewable penetration

MDGAM-Based Cooperative Task Scheduling for Communication-Constrained

https://arxiv.org/html/2608.00648v1
MA] 01 Aug 2026 MDGAM-Based Cooperative Task Scheduling for Communication-Constrained Distributed Multi-Agent Systems Licheng Wang    Mingtao Huang    Yuan Shen Thanks: The authors are with the Department of Electronic Engineering, and Beijing National Research Center for Information Science and Technology

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

I INTRODUCTION

https://arxiv.org/html/2407.10811v1
3Ziyue Li and Wolfgang Ketter are with the Information Systems Department at the University of Cologne, Germany

Efficient Multilingual Neural Machine Translation via Corpus-Driven

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

Inverse Learning of Latent Risk-Neutral Densities from Irregular Option

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

Matching-Driven Deep Reinforcement Learning for Energy-Efficient

https://arxiv.org/html/2407.13076v1
Zhang are with the School of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen 518107, China, and with the Guangdong Provincial Key Laboratory of Fire Science and Intelligent Emergency Technology, Guangzhou 510006, China (E-mails: gubo@mail

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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

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

https://arxiv.org/html/2412.12213v2
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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

1 Introduction

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

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

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

Artificial Intelligence

https://arxiv.org/list/cs.AI/new
Biological systems, in contrast, exhibit adaptive plasticity, maintaining function through dynamic re-organisation around damage

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https://arxiv.org/html/2609.03027v1
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