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20 result(s) for “okapi bm25 site allegrolokalnie pp site non jitter com site mmecommerce my site:arxiv.org” of 50 matched · page 2 · 364 ms
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https://arxiv.org/pdf/2608.02918
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https://arxiv.org/src/2303.12712
#�Z-ÿ!¼¦¿îÝ MCj8 ÕƒÂ™êÉ ™÷/E„tNèkyÔÿ>¬ôΉõÓâAŸ4â…Yr'K�R².qy¬Kªy92ÀfŸFÁçÊ•J.´çhÝ Ý¬×íƒÜ ÅÎVwN˜§Ÿc}]øX;‡—Æùqf#ÃaHè…š,9ÞdÒ±1óÐÆŽ:Ûö%ZtÙu!*ÕñZ޹:Û¹Â;"F.Ó::ªãTx¡ãÛ.�F666ÛÛÛÔÑ{'OUÿM�âËUÉ' ƒù�ˆ•²¶3ª`$Q¯¡ô
https://arxiv.org/src/2211.10435v1
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https://arxiv.org/pdf/2508.11152
com three Proceedings of ACM Conference (Conference'17) book 1 1 9 9 Tianjiao ZhaoJingrao LyuStokes JonesHarrison GarberStefano PasqualiDhagash Mehtahttp://arxiv
https://arxiv.org/abs/2608.03883
Our systems combine sparse BM25 retrieval, evidence-aware rescoring for self-referential symptom reports, embedding-based reranking, query-prototype expansion, and LLM-based reranking
https://arxiv.org/abs/2104.08663
Our results show BM25 is a robust baseline and re-ranking and late-interaction-based models on average achieve the best zero-shot performances, however, at high computational costs
https://arxiv.org/abs/2608.03860
The pipeline combines sentence-window chunking, BM25, BGE-M3 dense retrieval, reciprocal rank fusion, optional cross-encoder reranking, and grounded answer generation
https://arxiv.org/list/cs.IR/recent
IR)
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[17] arXiv:2608
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https://arxiv.org/pdf/2608.03157
ÄÌ4ºû4àC0ÎøMÈ8$SÙH‹‘Rp¬Æk4>¢eñ8ŠQ�{Ñ›Pp/ªIŠö1˜œñšMõŠc2ââ…^ø¼Q#ïT#ÑáNrFRÂK“àclƒ©‘w'�0I»ƒŸ}¢”ˆŸJüœãþUÞÁñ™h+`d@«WÙul“`¯r0=ÍÑhJl“ŒfÇ6'è‘ÏÅhÞ©&8bAŸƒ|¢ˆ šk³JˆžwÔ„ÔîØF�¹À´ÿù’LÅ·J6Q‰¶�‘†,'ø²¯ÎÄDÓUÁ {P½‰™_GObiw‚I®µ‰& zàk‚ýÑ�¾¥HÂF)Òª0^SÑogRÁ€¨“�ƒœ7™C¦¸ÈÁÑ6¿Ø8â¯W— lÀŸ2N *cåOÕ䂨8S
https://arxiv.org/html/2608.02813v1
Wind Turbine Generators
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https://arxiv.org/html/2608.03529v1
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https://arxiv.org/html/2608.00648v1
Distributed Multi-Agent Systems
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https://arxiv.org/html/2607.28847v1
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https://arxiv.org/pdf/2407.02510
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https://arxiv.org/pdf/2006.15704
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https://arxiv.org/pdf/2508.02691
7 %¿÷¢þ 1 0 obj > endobj 2 0 obj > endobj 3 0 obj > stream Statistical modeling of SOFR term structureTeemu PennanenWaleed Taoumhttp://arxiv
https://arxiv.org/pdf/2508.04671
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https://arxiv.org/pdf/2508.07408
-Aware Sentiment Factors from LLM-Augmented Financial Tweets: A Transparent Framework for Interpretable Quant TradingYueyi WangQiyao Weihttp://creativecommons.org/licenses/by/4.0/q-fin.STcs.CLcs.LG endstream endobj 4 0 obj > endobj 5 0 obj
https://arxiv.org/pdf/2407.01722
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