NishiSearch

Web This site Trusted

30 result(s) for “okapi bm25 site terms com pp site hotshops pp site does could good com site:arxiv.org” of 142 matched · 621 ms

Scope: Nishi’s own index (our crawl + Common Crawl) — not the whole live web. Some sites block all automated crawlers (anti-bot walls), so their pages may be absent here even though we never filter lawful content.

Freshness: newest result fetched 24 d ago · median age of these results 24 d · 1 of 30 carry a fetch time

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
2 pp, exceeding MemSearch reader scaling (+10

Producing Policy Recommendations: from Statistical Decision Theory to

https://arxiv.org/html/2607.29281v2
Empirical Practice 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 GitHub Issue

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

Report GitHub Issue

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

Sphere Retraction Normalizations

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

Report GitHub Issue

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

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

Preying on Leveraged ETFsPreliminary and incomplete. This project was

https://arxiv.org/html/2608.03703v1
An LETF is a repackaging: it holds the underlying and borrows, and spans no payoff an investor could not construct directly

arXiv is now an independent nonprofit! Learn more ×

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

Report GitHub Issue

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

1. Introduction

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

Testing the effects of an unobservable factor: Do marriage prospects

https://arxiv.org/html/2410.19947v2
org perpetual non-exclusive license arXiv:2410

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

Report GitHub Issue

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

Learning to Control Unknown Strongly Monotone Games

https://arxiv.org/html/2407.00575v3
Gradient play converges to a unique Nash equilibrium (NE) that does not optimize the global objective

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

https://arxiv.org/html/2604.05327v4
Variational Preferences 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?

When Collaboration Becomes a Trigger:Collective Evidence-Threshold

https://arxiv.org/html/2608.01085v1
org perpetual non-exclusive license arXiv:2608

Rainfall is rough

https://arxiv.org/html/2607.27099v1
9 Detailed results for Météo France data at small time scales License: arXiv

Effort-Centric Fairness in Lending Decisions

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

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
Our rigid experiments show that our method has good cycle-flow relation and superior performance

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

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

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

Optimizing Age of Information in Vehicular Edge Computing with Federated

https://arxiv.org/html/2407.02342v1
com/qiongwu86/Optimizing-AoI-in-VEC-with-Federated-Graph-Neural-Network-Multi-Agent-Reinforcement-Learnin

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

Global coal trade is resilient to maritime chokepoints

https://arxiv.org/html/2608.00328v2
6 Model definition References License: arXiv

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

MDGAM-Based Cooperative Task Scheduling for Communication-Constrained

https://arxiv.org/html/2608.00648v1
Distributed Multi-Agent Systems 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

Multi-agent Off-policy Actor-Critic Reinforcement Learning for Partially

https://arxiv.org/html/2407.04974v1
Unlike many existing dec-POMDP-based RL approaches, the proposed algorithm is suitable for model-free multi-agent reinforcement learning as it does not require knowledge of a transition model

Automatic Patient-Specific Microwave Ablation Planning Accelerated by a

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