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30 result(s) for “okapi bm25 site hotchips pp site github com site text of de site www hca software site:arxiv.org” of 56 matched · 1147 ms
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Did you mean okapi bm25 site hotchips pp site github com site text of de site www ha software site:arxiv.org?
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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
(3) Search latency bites only at very small reader: on a Spark GB10 edge node, memory-search adds a moderate and fixed 8787/77/4848 ms (BM25-RAG/Memobase/MemSearch) that composes a small part of TTFT for most reader-backend combinations
https://arxiv.org/list/cs.AI/new
However, their performance heavily depends on the clarity and completeness of data semantics
https://arxiv.org/html/2608.03048v1
To address these issues, we propose PI-Mem (Parallel-Iterative Memory), a mechanism that processes all chunks in parallel and iteratively refines a shared memory over a bounded number of turns
https://arxiv.org/html/2407.16741v3
edu
Abstract
Software is one of the most powerful tools that we humans have at our disposal; it allows a skilled programmer to interact with the world in complex and profound ways
https://arxiv.org/html/2608.03063v1
Offline comparison of deployment candidates (RQ3, Table 13)
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/list/cs.CL/new
(3) Search latency bites only at very small reader: on a Spark GB10 edge node, memory-search adds a moderate and fixed 87/7/48 ms (BM25-RAG/Memobase/MemSearch) that composes a small part of TTFT for most reader-backend combinations
https://arxiv.org/html/2608.02668v1
Both prove to be members of a one-parameter family of angular retractions, pp-SpheretNorm, whose rotation angle saturates rather than growing without bound
https://arxiv.org/list/cs.SE/new
PL)
Glob patterns, a domain-specific language for structured string matching, are a foundational yet understudied component of modern software development embedded in everything from build scripts and configuration files to web server routes
https://arxiv.org/html/2509.22186v2
ocr, PP-StructureV3), establishing new performance records in text recognition, formula recognition, table recognition, and reading order prediction
https://arxiv.org/html/2403.08299v1
The landscape of software development has witnessed a paradigm shift with the advent of AI-powered assistants, exemplified by GitHub Copilot
https://arxiv.org/html/2608.02918v1
Biscainho are with SMT, DEL/Poli & PEE/COPPE, Federal University of Rio de Janeiro, Brazil (corresponding e-mail: wallace
https://arxiv.org/pdf/2608.03157
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https://arxiv.org/html/2407.04503v4
team, Université de Bordeaux, France
Abstract
As large language models (LLMs) start interacting with each other and generating an increasing amount of text online, it becomes crucial to better understand how information is transformed as it passes from one LLM to the next
https://arxiv.org/pdf/2006.02759
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https://arxiv.org/pdf/2402.03300
Â0ÞìØíÔˆ3tÙq;%ñJo4MY‘óŽi_�:Ó&þÿkó“6Þ°Óߪñ¨"ËEôDEþ²ÆöÓû_Ó#‰æ9& aS;èQúN€ï•)ɧŸ«ñcuz;vK¹ù÷K¸ª‡«XÙ5¶y
https://arxiv.org/pdf/2608.03118
ZØz|ÐPG«-Tû*¾öÄö1ÇÆP¡8YîvkÚ©-'NÄŸéá`ÀPMÝŽ$&‡] L—'|*¡ûÍ�¥p7k7m¢E™7·€nÙîrøy09U=–PP#ü'#Þ„v2Zú$íþt;Ʀël�r5÷ð‡ð”
https://arxiv.org/src/2006.03271
{ûÞùÅ–Ì 3ƒù*r”™TúfϨËÏ~§Ÿ{øyðà>¿âgùõèàáƒÏö+O‚ê¯:õLªâ±'#�i?ÔùØKR}ŒUšíy½Ÿ3ó²Ro¬ÎU¨Ày“Úƒ©Üedƒ8w+%í²¼wëííV6µXìõvN8à¸W^;ð�6¬½èÉ„ýx§U‚a ÎKÇeÏ �X“±$Õj»Ž&„Øá„ ñ�ïõQ8MÊÈŽÜ�¼_üPfÙ;F¿/^½ùáíéÉëSïõ§/žÌÄ�¤I�2§Xác†C„êvøt9
https://arxiv.org/src/2006.01331
>'š"J=&_[¿:¾�$¿@0üÿâÕ›Þ^AjˆØj«>¢ÌÄ ‡†˜[Œª¤AÔôQ‘t`}~Q¨?½z(Rx€�‰{>2„¨J¢`ÇÎÒ»Aý ±˜;©ˆ×2?;_ڱ퀂.ì™OˆVþcñøÐ±nÁ{¾cçì){Æž³ïÙ_ÙöoìßÙKöнf?°7ìoì-{Ç.Ø�ìïì'ö3ûû¢c½·&›Í˜Ã\ÆÙœ-Ø’yì7vÍ|°� ±÷,f KYÆnØ-[±5û éÙCödj"¼ç¢êF?&8C%(æE|C$
https://arxiv.org/src/2402.03300
ƒ|öí/Áû1‹f&Æ¿Yׯ ~½ÖæÿõàMÞ¤¿=ùm|oúî·ú¯Îÿ»ø^þ/Åßmÿ_Õ5ò‹Çÿ ÌoB÷è¡ÞKýÉPoFç}øæNÿèA½Ç¼ß¥ömöü™¿òþ„jš9Ú¹Øÿo1î±ßo DåÅü¹ÿ+î þØÿOÈÿOxÇÀÿޙߊü_
https://arxiv.org/src/2006.00342
¨uXÞ{Æ8•ö}ë»z÷ú®oŸ‹™ç¹ïÿýûÿŸßÿt߃BYèê› ÷íÛ'ô•.¸TT”ùßàúð…B+ ¡•€„² ƒVB¡ÑŠ;ÐBêk4ýâ°ØD& 1étö_Éý»ùÿ£�îâÍ€™lØëï¶äŸë︔™Ê$$Ì`}=™ÿè(%eAþïPB+)ñò_Lÿ“ÿÿ…KFÊÌR^׉î Ë+!Q��™å.Þ�¨ŒŒ&²éLuG%’`S"‰ìè© Õ�;À¤™M�Õ¡©è™X@¦Óô‰l0¥ˆRDÉ£0òJ(+´Š:
https://arxiv.org/pdf/2303.12712v5
z$gs ²h)„Ïèùý ý_:^X�ÂGCyëêr�G4NǦúpP%êõŪBînk5¢(z…ÖÓ¸%T†ÞQ˜Õãx¯¢[èèð�^ÙÎNwií‡ o[”HaWc±‡vøÑ}¾¿°ÅÇû;ÇF� š~€é�õ
https://arxiv.org/pdf/2006.03178
=’õþú=W–egWY ‚AÓP¡yÏ=ç’É¥�”K†t@BR€ßŠ„pIø$´G¡OÒ%)ñ�ÖøO20é!4 -IR^@J’ Ñ(Ò@R>i�ÏÒ¡ í’\-ÈÓø\“„LâcfŒòÁAòAÂtzŠ’çS࣠(Wœ}"ã ‘Qþ &Ô„QÂ=ß Å�D2 'å-fäÔ ? 7ñ˲ø� ` 'DÈ�§0J Œ&à1!œü`ð 9ㆳ�{ø%0Ÿ¬L‘RqBl.+c¤b
https://arxiv.org/src/2006.01598
IK”Ö¿l÷¹÷Æ®ªE‘¢ô�)Qä_¾~ÿú¿óî§oÿéÃßúæãë¿ý›üFþK)´?忇?mòÉÄôo¬OÉ瘓—vÖÛdþÍÌÿ¼¨ÿ~ùðñë÷øÃ¿yÿîÝÇgí^‚ÿÿéÿE¾ú}ýüáÿõúý‡7ï~úÒ~öÏ?ýüËÇ/í—ÿî˯þÛùõ«ÿøæ‡~üú§Ÿ¾ú÷¯?¼ýøî篜±ñÿå?ÿ§þÃýå§×Þ¼þé«¿t1º“p¿ŽÄ?ÿ‡ÿð>¾ÿú§úæ‡w ÿûûwß½ÿúÇ?
https://arxiv.org/src/2006.02085
rúž�Ù¥•¸Ó]+Z¸W�—ǧ'¡-tfž•ˆÀ�||þâå Þ»ízŽmE{¸�:oŸ=W–ãÄélæ.Ø öîÝ×äþ— o;’›0°?–SÆ‘ñbŠ EP˜ðÚ yoäjz0H´'ÞæÒOŒJœû²�û»ˆDÈv]¶+Øià@È „óÝú©—¸¡·ü¢ÓùWO¦Ã�eûV”ìÙ^üû�±1þ†ÃýAÿ‡Šÿ£ÑÁÿÇÿÆgg§³³ÃNçnÌàîØÏ…O|ÕÃÞˆæ¥Ã®ÝdÎ’¹`Ž´ã$rC–
https://arxiv.org/pdf/2006.02833
ŧ^ÒaÈ™Qš¡„ÕᛀpôÇ Gæò1ÚÏ'g‰ =|Ü@ÒŠé�_¿ƒt—_üi»íendstream endobj 208 0 obj > stream xÚ�YK“ܶ¾ëWÌ%UÜ* D€oeǶ’ØŽã�œŠ¼Î»Ã,‡¤×ë_Ÿ~��Wöeh �F£ñõƒáîaî¾yÊÿÛÛWo¾ÖÉNkU$‰ÙÝÞï²PåiºË’B…i¾»v‚ﻟ~üÇÍ>ÖiP•Cy(�uÜý%LÂ÷7¹ º¦²ý¹ë‡›»Û¿½ùÚè]¦Š,ÔÈR¯8Ëv±Š¢‚9æžÛ>Þ$IPž‘u^vàÿ²QÀÓ˜àƒ6wL:vm5[a7ìo^šúl[ÜppâÑÐ~€í3Om—{T–Î,É07N
https://arxiv.org/abs/2608.03883
The task requires systems to rank candidate Reddit sentences according to their relevance to each of the 18 symptoms in the Adult ADHD Self-Report Scale (ASRS-v1
https://arxiv.org/abs/2104.08663
We leverage a careful selection of 18 publicly available datasets from diverse text retrieval tasks and domains and evaluate 10 state-of-the-art retrieval systems including lexical, sparse, dense, late-interaction and re-ranking architectures on the BEIR benchmark
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
https://arxiv.org/list/cs.IR/recent
CL) [pdf, html, other]
Title: SciRet: A Compute-Aware Empirical Study of Retrieval and Reranking for Scientific RAG
Kaysarul Anas Apurba, Md