Web This site Trusted
30 result(s) for “okapi bm25 site terms com pp site www datacom com site www is gov site:arxiv.org” of 139 matched · 951 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
https://arxiv.org/html/2608.02613v1
We evaluate five open-weight readers with Vanilla context, BM25-RAG, Oracle retrieval, Memobase, and MemSearch as memory backends
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/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/2205.01882v5
2 Details of the DVD Dataset
M Additional Empirical Application: Fishing-site Choice
M
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
com/qiongwu86/Optimizing-AoI-in-VEC-with-Federated-Graph-Neural-Network-Multi-Agent-Reinforcement-Learnin
https://arxiv.org/pdf/2402.03300
YBҥ۶mtR`kM۶mԩSe Ŋkܸ= ;vL-[}^tiʔ)J,\p͚5G yIgf]jU```Ŋ (Ulٮ]_^߾|X nG |YOIvK]2nvڴlո1cΝ +IsΝ*Tpx≋/"懇t){bʕ+/dK,)ɓΝ;1Ӧ1Lr5qׯ_o֬Y6lhu
https://arxiv.org/pdf/2006.02318
3/ pdfx PDF/X Schema external URL to an online version or preprint AuthoritativeDomain Text http://www
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/list/cs.CL/new
Many practically important problems are naturally treated as black-box optimization (BBO) problems, in which only objective values are observable, and the functional form is unavailable
https://arxiv.org/html/2407.16741v3
com/All-Hands-AI/OpenHands
Slack http://bit
https://arxiv.org/html/2608.02668v1
com/hazdzz/deep_connection \ncudata[Correspondence]Jie Zhang (),
Correspondence: Cheng-Fang Su ()
“Geometry is not true, it is advantageous
https://arxiv.org/html/2608.03086v1
org perpetual non-exclusive license
arXiv:2608
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)
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/2608.03480v1
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
https://arxiv.org/html/2608.03063v1
SeqLLM is fully deployed at WeChat Pay, screening millions of merchants per day
https://arxiv.org/html/2608.03154v1
com/COMBINI-Hub/Multi_Agent_Relation_Extraction
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
https://arxiv.org/pdf/2407.02510
:L ;Zv%&Kݷ#D$Lk2T@k)j\ ڀy7Iϟ~ߞIs"c'pӠO 4GK@ߪc&4u~|K)AQP_I0h_xb
https://arxiv.org/pdf/2607.27188v1
) /Title (Inverse Learning of Latent Risk-Neutral Densities from Irregular Option Quotes) /Trapped /False /arXivID (https://arxiv
https://arxiv.org/src/2006.01048
z'P"#3f+ Sdy^t ϰ=wُy@ :dw q NzApO,VA6&G6 9"Ai6Z̠ȿ'R⒒:ɏ{ kjjE ii#www h}'5QUUULK[q~~%8fN&(WRrtS1 &599d6N] Rcŷ|h,, dw_GJ11as- a~aaRBzB>708l6t% $
https://arxiv.org/pdf/2407.00125
) /Title (A Survey on Failure Analysis and Fault Injection in AI Systems) /Trapped /False /arXivID (https://arxiv
https://arxiv.org/pdf/2508.04671
hc&1f/JF㟾SɫI-%Ux3Xx@戞0 q{,VY##HՅyrd:'is>cf M 4El +n-Mf%>ofYX a奬
https://arxiv.org/src/2303.12712
tP0uˬGV 0ă"\ EulISJѪ YEpTG
https://arxiv.org/pdf/2508.11152
com three Proceedings of ACM Conference (Conference'17) book 1 1 9 9 Tianjiao ZhaoJingrao LyuStokes JonesHarrison GarberStefano PasqualiDhagash Mehtahttp://arxiv
https://arxiv.org/list/cs.AI/new
, the meaning of a customized field) originates from users' domain knowledge and is rarely documented publicly
https://arxiv.org/html/2609.02852v1
Report GitHub Issue
Description:
arXiv is now an independent nonprofit
https://arxiv.org/html/2607.27188v1
In machine-learning terms, RND recovery is an inverse problem from irregular observations (Arridge et al
https://arxiv.org/html/2608.03529v1
ch
Abstract
Biomedical literature is increasingly mined for knowledge beyond the questions it was written to answer