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30 result(s) for “okapi bm25 site terms com pp site www datacom com site en wikipedia org site:arxiv.org” of 139 matched · page 2 · 753 ms
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https://arxiv.org/pdf/2608.03118
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https://arxiv.org/pdf/2608.04008
Ù6¨¦ãþ ¬>Ÿ–£þÇÈŒ6=RBmL”õ·LXƇÄM¤_ ³|¼èÉöVõN‡eÑï]Vƒñ¨Ð[ÁRóªÒ{‚ñ5X68$T§å÷ž…`=�ªŒì™"ÿ03[‚Rô/u‰ Cƒ*ÌJ¬³sI)u–8ƒW“qÿMI|�WGÏ0hù©Z5+ÆÞ§l*¢ pƒair 3÷zÝ } ÃBx×�ŠJ ê±ß£²ºóÛ¡jÞy Ń£‹ŠE"eSPL0¯Š }O;ï®�¾kã;ï_žþEØëø¢æ»³6ó"®)´º†sºr„›\#÷¢êU¥xtôƒ÷’Q‚ é í÷2~'åw�grã‰xô¢W]ÇÕpp*þc …¾ÿ)>VÕåô‡NçbQWŒ'ç�óZŸ]
https://arxiv.org/pdf/2608.03095
™æ×ÏéÖÖ’W“[G³÷éïtËaÄ!q$|� I¤ Pˆ`$ž¥Éè :�ïš¾^�á, k*̾Æè(JÎÑß[Eô“N‡ß_ëaô]õ߯€÷àl€¶ÆE1Í_Á0�wÒl¼Ãµ8p v¨Äz3lœÄwQ’G¥ÈÜYcñCt—Þß§Iîä'%O|{ ø@ìDYšo肋áö`%E\ “ å¶z\A@ݼOîÒ¡u;ð>Ͼ®VlÅ`¸¤WI|gË‹ÖuWÖ’sbc§ Ÿó"º$ßSd¥Î²a”Y
https://arxiv.org/src/2006.02759
YT,‹ *Šÿ¹ËÌÜ™LÒ²øþ÷þÿÍÍÌ�{Ï=÷ì÷Ü;3==ö¡Biû¸¿òHƒ#;»#þ…Ãø‹ÏÓ3²²²Ò3³²:¦Ç¥¥§eÃ×ñ/ÅŠ!IæƒE9V½ªîÿ‡= ÿ=b€Ê©þ�Ïf—.÷8ƒ³²2ÍùŸž–‘Õ1ñ?=³cfzfZ6ð?£cÇŽq\ÚeÆÃôøÎÿ$NÏz.5•Ã21‚“ä2¯À¹Ä —?p7A ý¼WâRòø`1t¦z=EÍ„ ÇA*·IHJHâzçé58ÐÐü�ð5Çõ e·
https://arxiv.org/pdf/2608.02851v1
%ß6ùõ�ÃG"¥8/1tx4œ93CŠŒ`“LÔ’)¦cš9S1Ã8‚YÆeí˜cܨšÕŒ;ͯ˜¨4LCÏ‚ eQ™0F3®˜p†ÞÑLVVÒ»L ²Ì-“ÊѳcÒ8z®™t4¯¨˜ªhÁ™¢È(Sš¹dSLÕ‚ž5Ó\Ò³aZ*úµLkC|rÚ*ÄÀ´«1)3•¤I83ÜÒ¤‚) —ÌhL®˜1F2‚ŒµœœaÆYÁ¤e¦¶Šœb¶²ätÍ,§qU1+(nÅ™•ôG‘.Òð|û-»ÿ±;tãÀþϾÙvc»yn†çîÐ�½¨¸
https://arxiv.org/pdf/2303.12712v5
z$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/2006.04122
/Width 614 >> stream xÚì� XŒkÇ�=D!D‘6"ZT–$E%BE¨äˆì²gQ)tˆÐJ{ÚhU(íJ+!‘V) D”óÝõœó~s¦)Ieäþ_÷Õ5óîͼóüÞÿ³ÜÏ£P( …j…þÀ� …B¡P(D& …B¡P€ÌiÓ¦�A¡P( E# È„ø�B¡P(háˆÈD¡P( ‘‰B¡P("…B¡P(D& …ú%õõë×úúúºÿ%X‹ ‘‰B¡~;ß¿ÿðäéó�[‘Öö^§
https://arxiv.org/pdf/2608.03411
”ý6appÂl‘Мe~Ž-yè�2GiìÂ�‘‡&pf3ÒK·¤—jGÒKeòÁ ,õ"&:w|Ò¶öÝP"´rf�r\úÂxÝqF¢Ë=/Ü–ºƒÛn¦Èâ™îÆ*>Ó]zJX-éw_îö0}óó0°(B²5àû×±&›ì2 �
https://arxiv.org/pdf/2608.03233
T½+Ñj¬±qø8¸ ÇM\¯c¡¤~wD`ž”Œõ%::P ÏsC`à zßzæ¯TrÔêH`$Å{0‡ÝF{ÿìŒkëʆêÃÆ„Ð endstream endobj 411 0 obj > stream On the Diversity of Analogy Making in Large Language ModelsYuanhao ShenDaniel Xavier de SousaCaio César Sifuentes BarcelosHongyu GuoXiaodan Zhuhttp://arxiv
https://arxiv.org/abs/2006.04236
Comments: 2019 IEEE 5th International Conference on Big Data Intelligence and Computing (DATACOM)
Subjects: Distributed, Parallel, and Cluster Computing (cs
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.AI/new
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üðƒ48#¼vBB¯Òˆ mÅt÷ž={vêÔ Ö³ðĉ{ôèÁWüËk»ví¨À_ªrOR£°²u•>˜ÖüÕüÅÅÅYSÃ\+V,·™ÍßLqO€8µ--”ÛégÏžMq¼––ÛJLLTùwîÜÉÙv²ðÍ›7Ožß·o_pp°8M„ÿíÒ¥÷³Ï>ƒ¼°¸uëÖ¼©S§Nƒ úõëÇ+V,]ºôk¯½V¹re ; y‹)‚ñ„¿€põÕWò[Y'0õõõÅA�=zøðáxX,Ÿ={V…àf‡E‡$0’Q[ºJÍH‚Å*4Z¾|ùìdñ¦oß¾
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https://arxiv.org/pdf/2205.01882v5
žÄ35šÄAâ,:ÿ¾¤-e[ÖdN£�ùÞ#¥h‚ @�ô4(kÁ€±,8§ÀAá-x�² %H-HÒ"}�´É�EA räÔ€V[�°@²[P(¤¥í÷ œ!{Z §Í QÑf ZiJ† µ£$ ´¥z¨�>J@Úò[Ð…¡äŒ0(…‘¦ b`ÐQrFY J‚ц8!Z •0–’*MµúíåK¸úX¯ëvÿÁ³í®Ù6ûº›ÍÌ'c³#³éÍ»j]î~ÌäsV°7ë‘QI=0R%ŒßàÕ«öc˜} >
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