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22 result(s) for “okapi bm25 site terms com pp site github com site ley would site rec net site:arxiv.org” of 52 matched · page 2 · 563 ms
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https://arxiv.org/pdf/2607.28577v1
{™ÕÅ¥èuü÷™¡$›¤¤Œ]ûÌpæÌp8C2’NÒ‚BYARÂxN2ÂJNrÂ3N ã)Iž1Bø$¡”üHä)¡œÐ…`¤(à7˜IÊ’P0Ä2ÐË äa*•„åpTÀJ8�Œ.À9áiJ(€=–žãïŒð"ƒß@‚ a^fâ—·oÉæ=˜€Xþ"›?Õ1¹ï_¤Qƒ£ì«¶µ"|�¾{7ÞJ±¼ò‹Q/„V²ÈJ>H?t'Xø†“ÍoÚôrêàG ß)gž+ÊWh:g?ÁO”ú1Z¥n
https://arxiv.org/pdf/2608.03063
‘Êõë÷Ù”º›‡@°¤ê:^½ª¾(1ÉtÌãÂ0Íxª™a2ŠX̤6,aJ(–2•B#bZÆ93†CŸÅo’Å4¦XbbÆ5KUĸ�2F8$QŒ÷V Âfø# "RÁÈ^Ex‡WeðU-5CH®�D PᦱÁ;ü%2aþ’ïð—ÆxáRâ�ÃU¤˜$Wqʤ„�ï ¦øB®|‘uŠÈ/' .¥ …4�‚4À©à2N98À�QLIˆ@ƒÂG‘â]ã#Œ�šÒ ìð2 8£ð*"ñ4TS°¤9>‚Âú…àÜ+à
https://arxiv.org/html/2608.03577v1
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https://arxiv.org/html/2608.02941v1
Decoupling of LLM Safety in Low-Resource Bangla Derogatory Speech
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https://arxiv.org/pdf/2508.08980v3
-ð„õ®3;ËA~ýu�zv%ÍÌîª\Ìn«_ž~Ô’z´V1É´eŠqa˜fBVÌ0á ³LjÅS¼bžin|ÐV2Ιô™• ”Ìzx€ª¡f^ Ö+ÃgnáiáéÀÊÁÍD©À®‚'‡§uL€‰Ò¢ƒ¡üqíà‰. @ãNÂ8øóÖ>0c€!„1 UàB À¤ @&%˜hÍ$¸òÈácU�Lx¥˜„$à�žèǃ‰L+ @)p© ¿BSp¦ÀÔH¦’‚T€`Ï€ Ø+ø¨ÈáÏxÏþiÇ40ÇÛ$Ž›�
https://arxiv.org/pdf/2608.01657
#“®D9q~ýÞ‚2 ‘ôzF#Q÷ãà܃$#áDj"U”H¨&Š0#‰&\PbˆšX"Nh‘ŒPJx(#.)'ZB1~$±B€©áWKBÁCÑn! 쬀_�£A¾0„ª€? ~‘Ž˜Ê!.ÀfRlü ÅBœ…P.“ÔÀLp8ƒÅ ‡OÁÁj T ._`á�Â�0ç Èr—P»(ˆ ’Á” ¸”V—Z�Zpi!^Hò¡4Éऒ�†H…ª‚peƒ�%Hl-ƒ`¢
https://arxiv.org/pdf/2410.05779
‰eŠ”Ijg'}úH@âœw+÷â› Ð º¿þº'›Ã&Ù|x÷í�‚¿ÉFmTRlr«ãÂd›ÝéÝßþžlöðâ/›$NËbóBÍN›´Ìào»ù�wÿþ.‘NþüùÝ¿ü¨t²)ã2ÓÙæóóFʼnÊýž“$V9¼:mþíúK»¿Ûj“EÕó�6Ñó�ŠêÝ„¢rÓq.;œîèZO½ŒÄ“�œ|ÏÏs'U·§™$qYøÖ”e*Nµây 5¬™¶°�wŠV�{ÄQ@H‡—ŸîÒ2ú ß¼ŽS}r€\I—ìO_’DïDÿnj˜�0Z+Ž_¦†å
https://arxiv.org/pdf/2006.02602
¶ˆ^¦ßbÊ⇷½E‚ÿ(’¢é8Aâšžáôö�àX@åD‘¿6øhgŽÿ7Òû¯ôu[ õã-‚�0›£ º�Lø‡Â*ò:å˜h“$VpP/¥¡O¯í“©-¤¬ï~àɉòMIý5û&ƒBšÐdø]$Ô£v9d̾i»@Í�Ìäjòá0—p®¿¦X¡ Ô"Ihg> stream xÚuÉvܸñî¯è‹_Øï©;ÜšËQ–3Žò23~o4ÉA£D¢EÄ Ù
https://arxiv.org/pdf/2608.03138
¼ÌÓ+eÿ�,¿L}˜Ã‹ºÿuÌh{¼žÏÇ€HJ'›�êÃ>N�¼>ïNA-ËáÍÿôz*¥kÃy»±—ó®Ónx ÉZë�Z{¿IÂÐÿï3“qËóþæÝF¯öñ_ª³z“¬ šMJÓ �£Pp
https://arxiv.org/pdf/1911.06462
‡Äî0â�c‚ÔjõëÓ/€.×Öe6^�F?¾nNxsÞüô"”ç÷ï_üõuÞD¡*Ã2ºyw“Ç7yXª0�·ææCPÏãhú©{Di c*~ü†q_õu[uLhûøhqº®ƒiàîz€Î~®:ÇéÅŒwÃx>||ÿ/8ëm¤Uš”|¦‡CÃøé%ŒÌ³ÀÎõ [aP!WyÔããeøèuk¬:Üj ¿?µ2€Ÿ!1¯Çj[32�8âCÛ˜[{MÕpÈŽ{†»«Ù“©O}ûûldþ©š¸ãTYG’™—aB!�Lx«�ãÝÍ}S�aœ
https://arxiv.org/pdf/2601.04660
•ÄË�³qì®ýÿU9Ý·ÏíCb MJUš qû¾_Ý þ#}—þ#ýâî‡*}ü!-í¿q©,êV~›/Õ˜öuUëôñïéí{Ü-˶Iß?¦ÝhGá£kª¢‡!íú&yÿ÷ô‹÷ïë´Jßÿ%ý�柽¸L›4ß]âJ¾·ÿnÿ—뙽{q™Öiþ�Û—ö×Õe‚'Ñ?±O\Û1òÝ=PØKÐÝ€Ùe ¾� 'wäGiŒ±ªìÜu0Óç'N×XÊø?�/sµ:2ÉÃ1ÂÃ��éû7é/ß[ñ‘ø¼‡Kù¼’�Lc
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
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https://arxiv.org/pdf/2407.00323
ÚhmÃ^àA²jDÐT÷pL¿£ÅüÎhÏoÑ9çú¹î‘Y@& “Á ‘åá�ë÷íׯ{üeþOó¿Ì÷‹î°ÜÎûíb»ÞÌ7»ý¢?ôý|×ïÛî°Ÿß}7ÿf~‹ŠËš߬7ëõ|Éù× ƒÙ«Ÿæ_7ó«?ªò–¿¿bÙz~õŽOtøó«G3U.=£ÔV³7?üƒ ìûÒÃ`8ªíûGóõa±Ÿ_ýíѬ‹!Í É�j`¸ w; —ejnxï]PšÍr9 úóüùŸù\ª˜~ ïóW?ÍNà}½í ðv·]ô]7Bû·W[k
https://arxiv.org/pdf/2006.02464
> stream xÚÓÎP(Îà ýð endstream endobj 9 0 obj > stream xÚÓÎP(Îà ýð endstream endobj 11 0 obj > stream xÚÓÎP(Îà ýð endstream endobj 17 0 obj > stream xÚÓÎP(Îà ýð endstream endobj 20 0 obj > stream xÚÓÎP(Îà ýð endstream
https://arxiv.org/src/2006.00441
çºÎJ§ºWZ¬ÕIýªº›ÙØÞÖÁÐÉ”ÎÁÄ àÿ¦Äð•ØØXþ:¥9³°32302³±0²±130}É12²³³0üß5 ÿœ\�] � œìí]þwrÿSùÿK©‚ˆ-#3éÀÁíÁYé]ÞÌÀ�½‘½Œ©�¹‹ëK‰€^ÌÒÆÅÔéëlcèb*bjlobJÀÇåìâdjhåXœ%]K2ìòøNí%I·RõŒÐ„`ˆMÐßÃØFÐTG 7ô›ä“ÿ=³œˆ«úv:wƒŒƒ"*¹^:
https://arxiv.org/pdf/2507.17609
כּžñÖöìfóëKêÅ#ÉòÜXÜÎRE>¤(Ršc©x%M%*ªT%+FY¥*¦EUWÜÐJWB˜ÊT’Ô%•¢ð‹VªV0ÖBW”Wš‘ŠŠJצ¢²2’�,`fðr>ó(p°šV8�sø $!XÅ`Š$ð›Ão¿Q�šWL‚¿A”æ¤b Oø òŒºQ0 ‡(W•i@s%ào`ÚT\€¥+j%+d%ŠVY%ÐáGH «’²€Š–¢>Âb ¢ †W~„" Õ°®� (KIŽ×•”ø5` vt€
https://arxiv.org/pdf/2608.00328
æ §HŽcùë·Æ /³Nž8ƒî>Ý}ºÑà…‘‚p"K"U”HÂhIaZ’’pɉ&‚Qbˆ(KB"\(Q‚ʈ2†PÐ)`Q$¡’® ‹�hƒ«Œ8üu(¬€k W@á%%Œ�}Éã PrÂ0šR¦¥9 jaCˆ®€gèÃÏ@9@±RªR@F Òð‡sE¸€Ÿ ô$á ×aIBÞüqÈR€Žy@S*É OÁ q!ˆ ªEe ¬”DH" ê+¢ ÈQ ”…&Šƒ_YI Æ�tJ.”QÀ
https://arxiv.org/pdf/2506.01844
SmolVLA: A Vision-Language-Action Model for Affordable and Efficient RoboticsMustafa ShukorDana AubakirovaFrancesco CapuanoPepijn KooijmansSteven PalmaAdil ZouitineMichel AractingiCaroline PascalMartino RussiAndres MarafiotiSimon