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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
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https://arxiv.org/html/2608.02613v1
2 pp, exceeding MemSearch reader scaling (+10

Producing Policy Recommendations: from Statistical Decision Theory to

https://arxiv.org/html/2607.29281v2
This paper reviews recent theoretical developments on research design for policy choice and provides new tools applied researchers can use to guide their design choices and communicate their policy recommendations

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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

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

https://arxiv.org/html/2608.03099v1
4 System Success Alone Does Not Isolate Language 5

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https://arxiv.org/html/2608.00458v1
The central challenge is that transmitting more message content does not necessarily improve the downstream performance

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https://arxiv.org/html/2609.03159v1
2, which are to Understand the Sun, Solar System, and Universe: “How does the Universe work

Sphere Retraction Normalizations

https://arxiv.org/html/2608.02668v1
Sphere pp-Angular Retraction Normalization

Learning to Control Unknown Strongly Monotone Games

https://arxiv.org/html/2407.00575v3
A NE does not optimize global objectives and can lead to poor performance

1. Introduction

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

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https://arxiv.org/html/2609.02852v1
However, various strands of evidence indicate that an LLM’s externalized linguistic outputs and mechanistically-extracted linguistic features can be an unreliable lens for understanding internal model computation

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https://arxiv.org/html/2609.03103v1
This geometry offers an efficient compromise among survey coverage, pointed sensitivity, system complexity, and resilience, and can be scaled to larger persistent soft X-ray monitoring architectures

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

Testing the effects of an unobservable factor: Do marriage prospects

https://arxiv.org/html/2410.19947v2
This observation raises two questions: (i) does the chosen major impact the marital outcomes of college graduates

Preying on Leveraged ETFsPreliminary and incomplete. This project was

https://arxiv.org/html/2608.03703v1
Dispersing the rebalance through the session, Korea’s chosen remedy, moves the order but not the reference that sizes it and can raise the toll

When Collaboration Becomes a Trigger:Collective Evidence-Threshold

https://arxiv.org/html/2608.01085v1
However, this collaboration introduces a vulnerability: backdoor behavior can be activated when peer evidence reaches a hidden threshold, rather than being determined by any single message

Effort-Centric Fairness in Lending Decisions

https://arxiv.org/html/2607.28847v1
3 Research Question 1: Does Masked Inequality Exist

Rainfall is rough

https://arxiv.org/html/2607.27099v1
The statistical inference methodology we introduce can identify critical cluster processes at small scales while recovering the signature of this criticality on coarser scale data obtained from other measurement sources

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

https://arxiv.org/html/2608.01366v2
com Affiliation: Department of Design and Manufacturing, Indian Institute of Science (IISc) , Bangalore , India , Srinidhi Ranjini Girish email: srinidhirgirish@gmail

You’ve Got to be Efficient: Ambiguity, Misspecification and

https://arxiv.org/html/2604.05327v4
Under mild conditions, the finite-sample likelihoods—which may themselves be misspecified—can be replaced by a limit experiment involving the Gaussian family as the reference likelihood

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

Computation and Language

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

I INTRODUCTION

https://arxiv.org/html/2407.10811v1
Recently, employing reinforcement learning (RL) to solve TSC has become a research hotspot since it does not require too much artificial priori and can improve performance significantly through the paradigm of trial and error

Global coal trade is resilient to maritime chokepoints

https://arxiv.org/html/2608.00328v2
The exception is a restriction to maritime traffic in the South and East China Sea, which could raise costs by 10 $/t for China, whilst reducing costs for other importers in the region by similar levels

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

https://arxiv.org/html/2608.03452v1
Prior studies have shown that character-level transformers can reproduce this pattern, but that evidence describes what models produce, not what they represent

Inverse Learning of Latent Risk-Neutral Densities from Irregular Option

https://arxiv.org/html/2607.27188v1
5 Real NIFTY data: adaptation helps but does not close the gap 6 Discussion 6

Artificial Intelligence

https://arxiv.org/list/cs.AI/new
We demonstrate that it can self-assemble functional circuits from scratch and rapidly re-route logic around permanent, previously unseen hardware faults

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https://arxiv.org/html/2608.03358v1
Introduction As Multimodal Large Language Models (MLLMs) become integrated into conversational assistants, human-AI interactions are evolving from text-centric toward multimodal exchanges, where assistants can retrieve and generate images in their responses

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

https://arxiv.org/html/2608.02966v1
(c) Because these distractor preferences vary with ability, their identities provide Fisher information that correctness does not retain

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

https://arxiv.org/html/2607.27063v1
The design does not claim that every momentum or reversal episode is caused by herding; instead, it provides a disciplined mechanism through which herding can amplify informational price adjustment

MDGAM-Based Cooperative Task Scheduling for Communication-Constrained

https://arxiv.org/html/2608.00648v1
The framework is suitable for a broad range of distributed task-planning applications and can be flexibly transferred to related scenarios with different practical constraints and settings