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30 result(s) for “okapi bm25 site terms com pp site hotchips pp site www is gov site:arxiv.org” of 126 matched · 505 ms
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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
https://arxiv.org/html/2608.02613v1
2 pp, exceeding MemSearch reader scaling (+10
https://arxiv.org/html/2205.01882v5
2 Details of the DVD Dataset
M Additional Empirical Application: Fishing-site Choice
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https://arxiv.org/html/2412.12213v2
Instead of training on observed option prices, FINN is learned through a self-supervised replication objective based on dynamic hedging, ensuring economic consistency by construction
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
https://arxiv.org/pdf/2402.03300
YBéÒ¥Û¶m»téR‹¢–`kÊMÛ¶mëÔ©Sùòåe ÅŠkܸñûï¿ïÞ=»³;vL¿´-[¶¤}Û^ºtiÊ”)ò¤¥J•òôô,\¸pÍš5GŽyòäIgf���]µjU```ÅŠ(àååU¶lÙ®]»®_¿^ß¾|XŸ nëÑG•ÉÆ|YOIÄv—ðøã�K¢·�]2”n³víÚ´lÕ¸¸¸1cÆäÎ�Ûî ¸»»¿òÊ+ÖIsçÎ�*Tp´žx≋/¦"懇‡ët)ïÑÞ½{��šbþÊ•+Õß/¾ø¢í¢dýK–,)�æÉ“çÎ�;Ö1ÿôéÓ¦1åLråÊ5qâÄô�ùׯ_oÖ¬™ÝY6lhu
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
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
https://arxiv.org/html/2609.02852v1
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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
https://arxiv.org/html/2607.27188v1
org perpetual non-exclusive license
arXiv:2607
https://arxiv.org/html/2608.03529v1
ch
Abstract
Biomedical literature is increasingly mined for knowledge beyond the questions it was written to answer
https://arxiv.org/html/2608.03086v1
org perpetual non-exclusive license
arXiv:2608
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)
https://arxiv.org/html/2607.28410v1
org perpetual non-exclusive license
arXiv:2607
https://arxiv.org/html/2407.10811v1
com5Hua Wei is an assistant professor in the School of Computing and Augmented Intelligence at Arizona State University
https://arxiv.org/html/2608.03011v1
org perpetual non-exclusive license
arXiv:2608
https://arxiv.org/html/2608.00458v1
org perpetual non-exclusive license
arXiv:2608
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
https://arxiv.org/html/2608.03480v1
org perpetual non-exclusive license
arXiv:2608
https://arxiv.org/html/2608.02909v1
This approach is theoretically valid, easy to implement, and does not require new data
https://arxiv.org/html/2608.03063v1
8 pp in a production fraud detector serving billion-scale transaction traffic
https://arxiv.org/html/2608.03154v1
org perpetual non-exclusive license
arXiv:2608
https://arxiv.org/html/2410.19947v2
org perpetual non-exclusive license
arXiv:2410
https://arxiv.org/html/2407.13076v1
Su is with the School of Cyber Science and Engineering, Xi’an Jiaotong University, Xi’an 710049, China (E-mail: zhousu@ieee
https://arxiv.org/html/2608.01366v2
org perpetual non-exclusive license
arXiv:2608
https://arxiv.org/html/2608.03703v1
This project was begun on July 20, 2026; the present version is dated August 4, 2026
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
https://arxiv.org/src/2006.01048
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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