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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/2609.02852v1
A linguistically-decodable feature is one that is defined in terms of natural language, and is extracted directly from a model’s natural-language outputs or indirectly via mechanistic probes like sparse autoencoders Bricken et al

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https://arxiv.org/html/2609.03027v1
Report GitHub Issue Description: arXiv is now an independent nonprofit

Sphere Retraction Normalizations

https://arxiv.org/html/2608.02668v1
On nanoGPT, all three methods outperform existing lightweight deep connection schemes, and the best validation loss is attained at finite pp, indicating that the exponential map is not the preferred retraction for spherical residual streams but merely one end of a spectrum

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

Global coal trade is resilient to maritime chokepoints

https://arxiv.org/html/2608.00328v2
GN] 04 Aug 2026 Global coal trade is resilient to maritime chokepoints Jorrit Gosens Centre for Climate and Energy Policy, Crawford School of Public Policy, Australian National University, Acton, 2600 Australian Capital Territory, Australia Corresponding author; jorrit

arXiv is now an independent nonprofit! Learn more ×

https://arxiv.org/html/2609.03159v1
Description: arXiv is now an independent nonprofit

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https://arxiv.org/pdf/2608.03157
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Rainfall is rough

https://arxiv.org/html/2607.27099v1
4 Rainfall is rough at large time scales 1

Inverse Learning of Latent Risk-Neutral Densities from Irregular Option

https://arxiv.org/html/2607.27188v1
In machine-learning terms, RND recovery is an inverse problem from irregular observations (Arridge et al

Consensus Measures for Unstructured Biomedical Text Annotations

https://arxiv.org/html/2608.03529v1
ch Abstract Biomedical literature is increasingly mined for knowledge beyond the questions it was written to answer

Automatic Patient-Specific Microwave Ablation Planning Accelerated by a

https://arxiv.org/html/2608.03086v1
The code is available at: https://github

Can Large Language Models Execute Parent Orders?

https://arxiv.org/html/2607.28410v1
com/zaneopen/PACE 1 Introduction Reducing execution costs is a central objective for financial institutions (Bertsimas and Lo 1998)

Coordinated Primary Frequency Regulation and Grid-Forming Control for

https://arxiv.org/html/2608.02813v1
Yufei Xi and Lin Cheng are with the State Key Laboratory of Power System Operation and Control (Department of Electrical Engineering, Tsinghua University), Beijing 100084, China Florian Döfler is with the Automatic Control Laboratory, ETH Zürich, 8092 Zürich, Switzerland Abstract Conventional grid-forming (GFM)

I INTRODUCTION

https://arxiv.org/html/2407.10811v1
com5Hua Wei is an assistant professor in the School of Computing and Augmented Intelligence at Arizona State University

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

https://arxiv.org/html/2608.03011v1
AS] 04 Aug 2026 Towards Real-world Environment-aware Zero-shot Text-to-speech Synthesis via Disentangled Audio Infilling Ye-Xin Lu, Xin Wang,  Yang Ai,  Hui-Peng Du,  Zhen-Hua Ling,  and Junichi Yamagishi This work is the extended version of our conference paper [1] published at IEEE International Conference on

Herding, Momentum, and Reversal in China’s A-Share Market: An Agent

https://arxiv.org/html/2607.27063v1
The local interaction structure is represented by von Neumann and Moore lattices and is later replaced by Erdős–Rényi and Watts–Strogatz networks for robustness

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https://arxiv.org/html/2608.00458v1
Consequently, BANDMAS is able to adaptively schedule communication packets while adhering to bandwidth, latency, deadline, and receiver context constraints

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https://arxiv.org/pdf/2006.01128
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MDGAM-Based Cooperative Task Scheduling for Communication-Constrained

https://arxiv.org/html/2608.00648v1
Abstract Cooperative task scheduling in communication-constrained distributed multi-agent systems is challenging because each agent must make decisions from partial and dynamic observations while satisfying complex practical constraints

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https://arxiv.org/src/2006.15704
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Efficient Multilingual Neural Machine Translation via Corpus-Driven

https://arxiv.org/html/2608.03480v1
com Arabic Institute for Translation, Algiers, Algeria CERIST, Algeria Nasredine Semmar CEA LIST, Paris-Saclay, France Hassina Aliane CERIST, Algeria Abstract The adoption of large pre-trained multilingual models for neural machine translation (MNMT) faces a major challenge: excessive memory and computational

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

https://arxiv.org/html/2607.28577v1
3 Forward evidence is useful without perfect ranking 4

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https://arxiv.org/html/2608.03358v1
Thus, enabling MLLMs to understand such perceptions is essential for building more empathetic and user-aligned assistants

Every Wrong Answer Counts: Option-Level Psychometrics for LLM Multiple

https://arxiv.org/html/2608.02966v1
(a) In this item, "Saturn" is a plausible distractor that reflects partial knowledge of LLM examinees, whereas "the Sun" is the correct answer

Probing Character-level Transformers for the Spanish L-shaped Morphome

https://arxiv.org/html/2608.03452v1
2 Membership is decodable beyond the surface forms 4

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

Mapping the City Through the Lens of Language Models

https://arxiv.org/html/2608.02971v1
In geographic settings, this behavior is consequential because the category city spans substantial variation in scale, form, infrastructure, ecology, function, and development

1. Introduction

https://arxiv.org/html/2608.02909v1
This approach is theoretically valid, easy to implement, and does not require new data

On the Diversity of Analogy Making in Large Language Models

https://arxiv.org/html/2608.03233v1
To our knowledge, this is among the first studies to systematically investigate output diversity in LLM-based analogy making