NishiSearch

Web This site Trusted

30 result(s) for “okapi bm25 site www eyespy cy site time log gov site github com site:arxiv.org” of 236 matched · 595 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: no result on this page carries a fetch time yet (indexed before the fetch epoch was stored beside the doc)

This study synthesizes adjacent research and introduces Enactive AI as a conceptual framework for enterprise and industry reasoning, site-level decision support, and execution feedback
from the top result below

Artificial Intelligence

https://arxiv.org/list/cs.AI/new
The implemented contract fixes evidence non-overwrite, branch isolation, grounded multi-subject timers, guarded state change, and declaration-ranked event ordering over time and space; an external runner still decides whether evidence becomes an authoritative move

Report GitHub Issue

https://arxiv.org/html/2608.02613v1
5 Composition: reader-bound LLM time + reader-free search C

Computation and Language

https://arxiv.org/list/cs.CL/new
We evaluate five open-weight readers with Vanilla context, BM25-RAG, Oracle retrieval, Memobase, and MemSearch as memory backends

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

1 Introduction

https://arxiv.org/html/2407.16741v3
At the same time, thanks to improvements in large language models (LLMs), there has also been a rapid development in AI agents that interact with and affect change in their surrounding environments

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

Computers and Society Aug 2026

https://arxiv.org/list/cs.CY/current
251-256 Showing up to 50 entries per page: fewer | more | all [1] arXiv:2608

Existence of Richter–Peleg representation for general preferences

https://arxiv.org/html/2508.08980v3
org perpetual non-exclusive license arXiv:2508

Social and Information Networks

https://arxiv.org/list/cs.SI/new
per page: fewer | more | all New submissions (showing 4 of 4 entries) [1] arXiv:2608

Machine Learning Dec 2024

https://arxiv.org/list/cs.LG/2024-12
3251-3298 Showing up to 50 entries per page: fewer | more | all [1] arXiv:2412

AgentScope 1.0: A Developer-Centric Framework for Building Agentic

https://arxiv.org/html/2508.16279v1
org perpetual non-exclusive license arXiv:2508

%PDF-1.5 %� 7 0 obj > stream xÚÓÎP(Îàýðendstream endobj 9 0 obj >

https://arxiv.org/pdf/2006.02318
3/ pdfx PDF/X Schema external URL to an online version or preprint AuthoritativeDomain Text http://www

%PDF-1.7 %¿÷¢þ 1 0 obj > >> endobj 2 0 obj > endobj 3 0 obj > stream

https://arxiv.org/pdf/2608.03883
3/ pdfx PDF/X Schema external URL to an online version or preprint AuthoritativeDomain Text http://www

%PDF-1.5 %� 152 0 obj > stream xÚmTËŽâ0¼ç+¼$æÀà$0Š� ‰Ã£­ö ‰a#A%

https://arxiv.org/pdf/2402.03300
áÀ߯«›ÀÌjDÕå²»«ífðãc;ZæÕÁŽÌ«Ÿ¶­®MfGÑÏ}í q•]/¶ìÞ­ÍmÞ¯¶o⣩²­íÄ0ZÇë²è^œx]fçkn{ÕÿE+{*ʧyÄpg�6;5’PìŠîìVž¤pH8$hù—mÚ¢*ß„z•R:")󨺠ÊÖß3‰qŸûX”ysO'Hî)-ò"ëî}³‹³‹ÍÛ[ÛÙ˺s �á3 4†{´¢p¿YôdšrýØëKæ‘+ˆ™ÇÞ a }ÀõàíÑ« W€‡Œ{ Fvm734…4˜‡¢´�A­«»èGÞÿc

[2608.03883] DS@GT-ARC at eRisk 2026 Task 3: Sparse, Semantic, and LLM

https://arxiv.org/abs/2608.03883
Our systems combine sparse BM25 retrieval, evidence-aware rescoring for self-referential symptom reports, embedding-based reranking, query-prototype expansion, and LLM-based reranking

[2608.03860] SciRet: A Compute-Aware Empirical Study of Retrieval and

https://arxiv.org/abs/2608.03860
The pipeline combines sentence-window chunking, BM25, BGE-M3 dense retrieval, reciprocal rank fusion, optional cross-encoder reranking, and grounded answer generation

[2104.08663] BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of

https://arxiv.org/abs/2104.08663
Our results show BM25 is a robust baseline and re-ranking and late-interaction-based models on average achieve the best zero-shot performances, however, at high computational costs

Information Retrieval

https://arxiv.org/list/cs.IR/recent
IR) Tue, 4 Aug 2026 (showing first 34 of 45 entries ) [17] arXiv:2608

Information Retrieval

https://arxiv.org/list/cs.IR/new
Skip to main content System maintenance August 4th and 5th Learn more × Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Information Retrieval New submissions Cross-lists Replacements See recent

[1411.2842] Logical Limitations to Machine Ethics with Consequences to

https://arxiv.org/abs/1411.2842
2842] Logical Limitations to Machine Ethics with Consequences to Lethal Autonomous Weapons Skip to main content arXiv is now an independent nonprofit

[2607.29380] The Tragedy of the Cognitive Commons: How AI Could Disrupt

https://arxiv.org/abs/2607.29380
arXiv is committed to these values and only works with partners that adhere to them

[2510.01395] Sycophantic AI Decreases Prosocial Intentions and Promotes

https://arxiv.org/abs/2510.01395
01395] Sycophantic AI Decreases Prosocial Intentions and Promotes Dependence Skip to main content arXiv is now an independent nonprofit

General Economics

https://arxiv.org/list/econ.GN/recent
RM) Tue, 4 Aug 2026 (showing 16 of 16 entries ) [13] arXiv:2608

%PDF-1.7 %¿÷¢þ 1 0 obj > stream xœµ\ioÛ:ý>¿‚Ûyè£Dj4[›¦IÓ¤kÙV5^R

https://arxiv.org/pdf/2608.01934
ÏË›¢®sµ¡Ùq•�A r™�š4)^zf¿ï³Û߈õQâÄÂÜ$åÐ@ô@‰…^G ‰õ)N„‹½¼Ì9›ïŒq;x`"ݨN¯`�Äqj'fmRF‰x›˜­�ã3KqtðÕ­8:ÂfL]¶ ì¬ïN7êí»Q‘¸F�DÁ@Ý|Ý ÞC"Cy‹µX‰°\*±btÅœîÞlx^–Ö÷ö¼^¸_,…·VÛN›[évsZx¨Ï _ckúû··úÄð=vpu:÷pjØSòkìÐøõ»³[}úögͱÚ×�ýP~÷ƒÿä[ yÃIFºŒ–

%PDF-1.7 %¿÷¢þ 1 0 obj > stream xœ…WmOã8þ~¿Âá¤[b;NbiµRYX@ÀmÕr¢·§ÕÉ´¦Í’

https://arxiv.org/pdf/2609.03103
ãÒÊø­ËÒòËUôñÜ=d �êdY…�²Ä ß*Ë–€Ñþ€gÔYÎ÷äÓʤ•%xÑÉ(×™§­ì²œK MdWG{˦×ÅN–¥ Ûg)ã÷\÷#t·8–JIƒ )qï*ÿ)Ÿ_5'ÿG‰A“FßÃÅy£�bþ–ú�§ü½@~“Š–g“«fí®îO/î_¤Ñ¸Ç±l®^,S^1(n,ÈóŒ0jo�'qÉnEPU’³¸£, yÏåtq;›|))sUµ�2m辡²8’ÕÒô�´Á­‘QÒ�Ôì ¬VÊÖdU—ÄÝ—äCy,Oäë”NÊòwy%¯s6)o§)Ÿ”KJ ›åD~n

%PDF-1.4 %Óëéá 1 0 obj > endobj 3 0 obj > endobj 7 0 obj > endobj 8 0

https://arxiv.org/pdf/2407.00345
Õ+;Ÿ jýžÈ åmª (È£;%^B—üE»k¿OHxwåE¥ù µDg÷,]WQmPæ κŽ�æcy:0¾YdCoB`Y¿tò›Ë¨s›åHà ¾O$òâÞ#öÓê#ДÝ0Id¯)½ßo9¡·H•üLDz¯nî¹M¥�¾Ü—�‹" U‰€Zº‰iOMšg«F‚:©8©§ LZAڴ“ lX�N$C  ˆg¦

%PDF-1.4 %Óëéá 1 0 obj > endobj 3 0 obj > endobj 7 0 obj > endobj 8 0

https://arxiv.org/pdf/2608.00151
R†5ö9DüÉ‚6, ¥ÎβYƒW‚*e"ѹÚ�Rˆl®ŸßÔF≧Êk–l‘ò+Œ|ûZý-É[~ZзaˆÒd}æX®\>™Ö]«8ðn¤Ÿ¬V‚HIКÓÞb7ÆEèÈb8ÍíãÜd¿ìß%lVª)Pçf e’Z…6z³öà^wºcoM²±z†iÂ& ^ ”ŠÅ$aƒ�ÃZá nŸÎ¿Y¿PŒ‡ÍÍÐÒ$ ™ joVþ²ìßÝá“5ãnYçÊÝ@›Ã

‹'u�bìX X×·§ŠOÄ\*":"»,aPe `Å!’‘$3!¢­EÁ]Ä q/Z— ¸ÖE¥

https://arxiv.org/src/2205.11916v1
*H«âF]p\xçNHXô}ÿ¶ï½ïë|š„;÷œ{Îïì7À×Ó.œÁ#DD¸Œá Á�¦dQÖ £ñW=xœœØoxÔ¾m9N޶vö¶ðé ûlœíl50Î_&A�œfp†iÈ(ŠikßçÞÿ?}Â")‰e= ~ 35ŒGHBFJÚa4OFJšœMh‡E‚þŠ!þ”°ob]¤L|,ÇÚ–'Ž£ ÁcÐ+ØÑÀX.Âeñ±"寭þ"N ävöaàqL4Ég„ñì ÇE}ÅÖ¶Ù§f{š­¨î‰oA0zâÃJ*

%PDF-1.5 %¿÷¢þ 1 0 obj > >> endobj 2 0 obj > endobj 3 0 obj > stream

https://arxiv.org/pdf/2508.02758
5 %¿÷¢þ 1 0 obj > >> endobj 2 0 obj > endobj 3 0 obj > stream CTBench: Cryptocurrency Time Series Generation BenchmarkYihao AngQiang WangQiang HuangYifan BaoXinyu XiAnthony K

%PDF-1.7 %¿÷¢þ 1 0 obj > stream xœ­XM�7 ½÷Wè˜-P{$’’Í­M´i/E

https://arxiv.org/pdf/2608.01366
) /Title (Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution) /Trapped /False /arXivID (https://arxiv