%PDF-1.5 %âãÏÓ 1 0 obj << /Type /Pages /Count 14 /Kids [ 4 0 R 33 0 R 82 0 R 137 0 R 166 0 R 200 0 R 209 0 R 222 0 R 234 0 R 238 0 R 242 0 R 246 0 R 260 0 R 274 0 R ] >> endobj 2 0 obj << /Producer (PyPDF2) >> endobj 3 0 obj << /Type /Catalog /Pages 1 0 R >> endobj 4 0 obj << /Annots [ 5 0 R 6 0 R 7 0 R 8 0 R 9 0 R 10 0 R 11 0 R 12 0 R 13 0 R ] /Contents 14 0 R /CropBox [ 0 0 612 792 ] /MediaBox [ 0 0 612 792 ] /Resources << /Font << /F49 15 0 R /F68 20 0 R /F70 26 0 R /F1 31 0 R /F2 32 0 R >> /ProcSet [ /ImageC /Text /ImageI /ImageB /PDF ] >> /Rotate 0 /Type /Page /Parent 1 0 R >> endobj 5 0 obj << /A << /D (cite\056alves\055etal\0552023\055steering) /S /GoTo >> /Border [ 0 0 0 ] /C [ 0 1 0 ] /H /I /Rect [ 339.584 121.93 390.374 132.485 ] /Subtype /Link /Type /Annot >> endobj 6 0 obj << /A << /D (cite\056alves\055etal\0552023\055steering) /S /GoTo >> /Border [ 0 0 0 ] /C [ 0 1 0 ] /H /I /Rect [ 395.286 121.93 421.628 132.485 ] /Subtype /Link /Type /Annot >> endobj 7 0 obj << /A << /D (cite\056moslem\137adaptive\1372023) /S /GoTo >> /Border [ 0 0 0 ] /C [ 0 1 0 ] /H /I /Rect [ 426.819 121.93 487.173 132.485 ] /Subtype /Link /Type /Annot >> endobj 8 0 obj << /A << /D (cite\056moslem\137adaptive\1372023) /S /GoTo >> /Border [ 0 0 0 ] /C [ 0 1 0 ] /H /I /Rect [ 492.085 121.93 518.426 132.485 ] /Subtype /Link /Type /Annot >> endobj 9 0 obj << /A << /D (cite\056mu\055etal\0552023\055augmenting) /S /GoTo >> /Border [ 0 0 0 ] /C [ 0 1 0 ] /H /I /Rect [ 312.476 110.338 352.213 120.53 ] /Subtype /Link /Type /Annot >> endobj 10 0 obj << /A << /D (cite\056mu\055etal\0552023\055augmenting) /S /GoTo >> /Border [ 0 0 0 ] /C [ 0 1 0 ] /H /I /Rect [ 356.226 110.338 378.144 120.53 ] /Subtype /Link /Type /Annot >> endobj 11 0 obj << /A << /D (cite\056robinson\055etal\0552023\055chatgpt) /S /GoTo >> /Border [ 0 0 0 ] /C [ 0 1 0 ] /H /I /Rect [ 382.436 110.338 446.532 120.53 ] /Subtype /Link /Type /Annot >> endobj 12 0 obj << /A << /D (cite\056robinson\055etal\0552023\055chatgpt) /S /GoTo >> /Border [ 0 0 0 ] /C [ 0 1 0 ] /H /I /Rect [ 450.546 110.338 472.463 120.53 ] /Subtype /Link /Type /Annot >> endobj 13 0 obj << /A << /D (cite\056zhu\137multilingual\1372023) /S /GoTo >> /Border [ 0 0 0 ] /C [ 0 1 0 ] /H /I /Rect [ 476.756 110.338 518.705 120.53 ] /Subtype /Link /Type /Annot >> endobj 14 0 obj << /Length 9246 >> stream q 0 g 0 G 0 g 0 G 0 g 0 G q 1 0 0 1 91.801 740.513 cm [ ] 0 d 0 J 0.249 w 0 0 m 428.398 0 l S Q 0 g 0 G 0 g 0 G BT /F68 17.9328 Tf 102.465 681.686 Td [ (Ho) 10 (w) -250 (Much) -250 (Data) -250 (is) -250 (Enough) -250 (Data\077) -310 (Fine\055T) 92 (uning) -250 (Lar) 10 (ge) ] TJ 35.05 -21.917 Td [ (Language) -250 (Models) -250 (f) 25 (or) -250 (In\055House) -250 (T) 74 (ranslation\072) ] TJ -40.295 -21.918 Td [ (P) 20 (erf) 25 (ormance) -250 (Ev) 10 (aluation) -250 (Acr) 18 (oss) -250 (Multiple) -250 (Dataset) -250 (Sizes) ] TJ 0 g 0 G 0 g 0 G /F68 10.9091 Tf -5.419 -50.952 Td [ (Inacio) -250 (V) 37 (ieira) ] TJ /F49 7.9701 Tf 60.501 3.959 Td [ (\003) ] TJ /F70 9.9626 Tf 292.033 -3.959 Td [ (inacio\100gmail\056com) ] TJ /F70 8.9664 Tf -352.534 -11.955 Td [ (Department) -250 (of) -250 (Computing\054) -250 (Dublin) -250 (City) -250 (Uni) 25 (v) 15 (ersity) 65 (\054) -250 (Dublin\054) -250 (Ireland) -250 (\046) -250 (Alpha) -250 (CRC\054) -250 (Cambridge\054) -250 (UK) ] TJ 0 g 0 G 0 g 0 G /F68 10.9091 Tf 0 -16.937 Td [ (W) 18 (ill) -250 (Allr) 18 (ed) ] TJ /F49 7.9701 Tf 52.036 3.959 Td [ (\003) ] TJ /F70 9.9626 Tf 262.311 -3.959 Td [ (william\056allred2\100mail\056dcu\056ie) ] TJ /F70 8.9664 Tf -314.347 -11.955 Td [ (Department) -250 (of) -250 (Computing\054) -250 (Dublin) -250 (City) -250 (Uni) 25 (v) 15 (ersity) 65 (\054) -250 (Dublin\054) -250 (Ireland) ] TJ 0 g 0 G 0 g 0 G /F68 10.9091 Tf 0 -16.937 Td [ (S) ] TJ 6.671 0.131 Td [ (\264) ] TJ -0.606 -0.131 Td [ (eamus) -250 (Lankf) 25 (ord) ] TJ /F70 9.9626 Tf 291.983 0 Td [ (seamus\056lankford\100adaptcentre\056ie) ] TJ /F70 8.9664 Tf -298.048 -11.955 Td [ (Department) -250 (of) -250 (Computer) -250 (Science\054) -250 (Munster) -250 (T) 70 (echnological) -250 (Uni) 25 (v) 15 (ersity) 65 (\054) -250 (Cork\054) -250 (Ireland) ] TJ 0 g 0 G 0 g 0 G /F68 10.9091 Tf 0 -16.936 Td [ (Sheila) -250 (Castilho) ] TJ /F70 9.9626 Tf 306.895 0 Td [ (sheila\056castilho\100adaptcentre\056ie) ] TJ /F70 8.9664 Tf -306.895 -11.955 Td [ (SALIS\057AD) 40 (APT) -250 (Centre\054) -250 (Dublin) -250 (City) -250 (Uni) 25 (v) 15 (ersity) 65 (\054) -250 (Dublin\054) -250 (Ireland) ] TJ 0 g 0 G 0 g 0 G /F68 10.9091 Tf 0 -16.937 Td [ (Andy) -250 (W) 65 (ay) ] TJ /F70 9.9626 Tf 325.913 0 Td [ (andy) 65 (\056w) 10 (ay\100adaptcentre\056ie) ] TJ /F70 8.9664 Tf -325.913 -11.955 Td [ (AD) 40 (APT) -250 (Centre\054) -250 (School) -250 (of) -250 (Computing\054) -250 (Dublin) -250 (City) -250 (Uni) 25 (v) 15 (ersity) 65 (\054) -250 (Dublin\054) -250 (Ireland) ] TJ ET q 1 0 0 1 91.801 431.391 cm [ ] 0 d 0 J 0.249 w 0 0 m 428.398 0 l S Q BT /F68 9.9626 Tf 91.801 411.392 Td [ (Abstract) ] TJ 0 g 0 G 0 g 0 G /F70 8.9664 Tf 19.925 -19.699 Td [ (Decoder) 20 (\055only) -283 (LLMs) -282 (ha) 20 (v) 15 (e) -283 (sho) 25 (wn) -282 (impressi) 25 (v) 15 (e) -283 (performance) -283 (in) -282 (MT) -283 (due) -282 (to) -283 (their) -283 (abili) 1 (ty) -283 (to) -283 (learn) -282 (from) -283 (e) 15 (xtensi) 25 (v) 15 (e) ] TJ 0 -11.955 Td [ (datasets) -324 (and) -325 (generate) -324 (high\055quality) -325 (translations\056) -533 (Ho) 25 (we) 25 (v) 15 (er) 40 (\054) -343 (LLMs) -325 (often) -324 (struggle) -325 (with) -324 (the) -325 (nuances) -324 (and) -325 (style) ] TJ 0 -11.956 Td [ (required) -253 (for) -254 (or) 18 (g) 5 (anisation\055speci\002c) -253 (translation\056) -320 (In) -254 (this) -253 (study) 65 (\054) -254 (we) -254 (e) 15 (xplore) -253 (the) -254 (ef) 25 (fecti) 25 (v) 15 (eness) -253 (of) -254 (\002) 1 (ne\055tuning) -254 (Lar) 18 (ge) ] TJ 0 -11.955 Td [ (Language) -334 (Models) -335 (\050LLMs\051\054) -355 (particularly) -334 (Llama) -335 (3) -334 (8B) -334 (Instruct\054) -355 (le) 25 (v) 15 (eraging) -335 (translation) -334 (memories) -334 (\050TMs\051\054) -356 (as) -334 (a) ] TJ 0 -11.955 Td [ (v) 25 (aluable) -250 (resource) -250 (to) -250 (enhance) -250 (accurac) 15 (y) -250 (and) -250 (ef) 25 (\002cienc) 15 (y) 65 (\056) ] TJ 0 -15.94 Td [ (W) 80 (e) -265 (in) 40 (v) 15 (estig) 5 (ate) -266 (the) -265 (impact) -266 (of) -265 (\002ne\055tuning) -265 (the) -266 (Llama) -265 (3) -266 (model) -265 (using) -265 (TMs) -266 (from) -265 (an) -266 (or) 18 (g) 5 (anisation) -265 (in) -265 (the) -266 (softw) 10 (are) ] TJ 0 -11.955 Td [ (sector) 55 (\056) -304 (Our) -231 (e) 15 (xperiments) -231 (co) 15 (v) 15 (er) -231 (\002) 25 (v) 15 (e) -231 (translation) -231 (directions) -231 (across) -231 (languages) -231 (of) -231 (v) 25 (arying) -231 (resource) -231 (le) 25 (v) 15 (els) -231 (\050English) ] TJ 0 -11.955 Td [ (to) -251 (Brazilian) -251 (Portuguese\054) -252 (Czech\054) -252 (Germ) 1 (an\054) -252 (Finnish\054) -252 (and) -251 (K) 35 (orean\051\056) -314 (W) 80 (e) -251 (analyse) -251 (di) 25 (v) 15 (erse) -251 (sizes) -251 (of) -252 (training) -251 (datasets) ] TJ 0 -11.956 Td [ (\0501k) -208 (to) -208 (207k) -207 (se) 15 (gments\051) -208 (to) -208 (e) 25 (v) 25 (aluate) -208 (their) -208 (in\003uence) -207 (on) -208 (translation) -208 (quality) 65 (\056) -296 (W) 80 (e) -208 (\002ne\055tune) -208 (sepa) 1 (rate) -208 (models) -208 (for) -208 (each) ] TJ 0 -11.955 Td [ (training) -250 (set) -250 (and) -250 (e) 25 (v) 25 (aluate) -250 (their) -250 (performance) -250 (based) -250 (on) -250 (automatic) -250 (metrics\054) -250 (BLEU\054) -250 (chrF\053\053\054) -250 (TER\054) -250 (and) -250 (COMET) 74 (\056) ] TJ 0 -15.94 Td [ (Our) -254 (\002ndings) -254 (re) 25 (v) 15 (eal) -254 (impro) 15 (v) 15 (ement) -254 (in) -254 (translation) -254 (performance) -254 (with) -254 (lar) 18 (ger) -254 (datasets) -255 (a) 1 (cross) -255 (all) -254 (metrics\056) -322 (On) -254 (a) 20 (v) 15 (er) 20 (\055) ] TJ 0 -11.955 Td [ (age\054) -256 (BLEU) -254 (and) -255 (COMET) -254 (scores) -255 (increase) -254 (by) -255 (13) -254 (and) -255 (25) -254 (points\054) -256 (respecti) 25 (v) 15 (ely) 65 (\054) -255 (on) -255 (the) -254 (lar) 18 (gest) -255 (training) -254 (set) -255 (ag) 5 (ainst) ] TJ 0 -11.955 Td [ (the) -350 (baseline) -350 (model\056) -610 (Notably) 65 (\054) -375 (there) -350 (is) -350 (a) -349 (performance) -350 (deterioration) -350 (in) -350 (comparison) -350 (with) -350 (the) -350 (baseline) -350 (model) ] TJ 0 -11.956 Td [ (when) -275 (\002ne\055tuning) -275 (on) -276 (only) -275 (1k) -275 (and) -275 (2k) -275 (e) 15 (xamples\073) -288 (ho) 25 (we) 25 (v) 15 (er) 40 (\054) -282 (we) -275 (observ) 15 (e) -275 (a) -275 (substantial) -275 (impro) 15 (v) 15 (ement) -276 (as) -275 (the) -275 (train\055) ] TJ 0 -11.955 Td [ (ing) -221 (dataset) -221 (size) -221 (increases\056) -300 (The) -221 (study) -221 (highlights) -221 (the) -221 (potential) -221 (of) -220 (inte) 15 (grating) -221 (TMs) -221 (with) -221 (LLMs) -221 (to) -221 (create) -221 (bespok) 10 (e) ] TJ 0 -11.955 Td [ (translation) -269 (models) -270 (tailored) -269 (to) -269 (the) -270 (speci\002c) -269 (needs) -270 (of) -269 (b) 20 (usinesses\054) -274 (thus) -269 (enhancing) -270 (translation) -269 (quality) -270 (and) -269 (reduc\055) ] TJ 0 -11.955 Td [ (ing) -239 (turn\055around) -239 (times\056) -306 (This) -239 (approach) -238 (of) 25 (fers) -239 (a) -239 (v) 25 (aluable) -239 (insight) -238 (for) -239 (or) 18 (g) 5 (anisations) -239 (seeking) -239 (to) -238 (le) 25 (v) 15 (erage) -239 (TMs) -239 (and) ] TJ 0 -11.955 Td [ (LLMs) -250 (for) -250 (optimal) -250 (translation) -250 (outcomes\054) -250 (especially) -250 (in) -250 (narro) 25 (wer) -250 (domains\056) ] TJ /F68 10.9091 Tf -19.925 -31.881 Td [ (1) -1000 (Intr) 18 (oduction) ] TJ /F70 9.9626 Tf 0 -25.049 Td [ (In) -355 (recent) -355 (years\054) -381 (decoder) 20 (\055only) -355 (lar) 18 (ge) -355 (language) -355 (mod\055) ] TJ 0 -11.955 Td [ (els) -222 (\050LLMs\051) -223 (ha) 20 (v) 15 (e) -222 (re) 25 (v) 20 (olutionised) -223 (the) -222 (machine) -222 (transla\055) ] TJ 0 g 0 G 0 g 0 G 221.671 37.004 Td [ (tion) -233 (\050MT\051) -233 (\002eld) -234 (due) -233 (to) -233 (their) -233 (ability) -234 (to) -233 (learn) -233 (from) -233 (v) 25 (ast) ] TJ 0 -11.955 Td [ (amounts) -357 (of) -357 (data) -358 (and) -357 (generate) -357 (high\055quality) -357 (transla\055) ] TJ 0 -11.955 Td [ (tions) -443 (\050) ] TJ 0 0 0.5 rg 0 0 0.5 RG [ (Alv) 15 (es) -443 (et) -443 (al\056) ] TJ 0 g 0 G [ (\054) ] TJ 0 0 0.5 rg 0 0 0.5 RG [ -443 (2023a) ] TJ 0 g 0 G [ (\073) ] TJ 0 0 0.5 rg 0 0 0.5 RG [ -443 (Moslem) -443 (et) -443 (al\056) ] TJ 0 g 0 G [ (\054) ] TJ 0 0 0.5 rg 0 0 0.5 RG [ -443 (2023a) ] TJ 0 g 0 G [ (\073) ] TJ 0 0 0.5 rg 0 0 0.5 RG 0 -11.955 Td [ (Mu) -353 (et) -353 (al\056) ] TJ 0 g 0 G [ (\054) ] TJ 0 0 0.5 rg 0 0 0.5 RG [ -352 (2023) ] TJ 0 g 0 G [ (\073) ] TJ 0 0 0.5 rg 0 0 0.5 RG [ -353 (Robinson) -353 (et) -353 (al\056) ] TJ 0 g 0 G [ (\054) ] TJ 0 0 0.5 rg 0 0 0.5 RG [ -353 (2023) ] TJ 0 g 0 G [ (\073) ] TJ 0 0 0.5 rg 0 0 0.5 RG [ -353 (Zhu) -352 (et) -353 (al\056) ] TJ 0 g 0 G [ (\054) ] TJ 0 g 0 G 0 g 0 G ET Q q 0 0 612 792 re W n 1 0 0 1 0 0 cm BT /F1 12 Tf 14.4 TL ET BT /F2 7 Tf 8.4 TL ET BT 1 0 0 1 170.6935 20 Tm (Proceedings\040of\040the\04016th\040Conference\040of\040the\040Association\040for\040Machine\040Translation\040in\040the\040Americas\054) Tj T* ET BT 1 0 0 1 198.3925 10 Tm (Chicago\054\040USA\054\040September\04030\040\055\040October\0402\054\0402024\056\040Volume\0401\072\040Research\040Papers) Tj T* ET Q endstream endobj 15 0 obj << /BaseFont /FIXYHH+CMSY8 /FirstChar 3 /FontDescriptor 16 0 R /LastChar 106 /Subtype /Type1 /ToUnicode 18 0 R /Type /Font /Widths 19 0 R >> endobj 16 0 obj << /Ascent 750 /CapHeight 683 /CharSet (\057asteriskmath\057bar\057braceleft\057braceright) /Descent -194 /Flags 4 /FontBBox [ -30 -955 1185 779 ] /FontFile 17 0 R /FontName /FIXYHH+CMSY8 /ItalicAngle -14 /StemV 46 /Type /FontDescriptor /XHeight 431 >> endobj 17 0 obj << /Filter /FlateDecode /Length1 1442 /Length2 6512 /Length3 0 /Length 7496 >> stream xœuT”ßú.Râ(Ò  0tw‡t‡„„0„ÃÌ013Cƒt#% ¢„Ò "RÒ HJ«„tûãüÏù{׺w}kÍ÷íçý¾û}ž=,†÷”¡(;˜ ‰–ªêß· ‹ ‹88LXgØ_ÀaCc(¤ì8¨¢a`,Scq~ú($PÇÝ("‘”‘’Š ËüË…–ª=P ¾ P…„a ª(Wo4î€Åmó¯O 7„("##Åÿ;¨ìC# `$PŒu€¹àv„€÷QëýÜòX¬«¬§§§ Ø#ˆBÃxøž¬Ð†¡=`Pெ÷À.°? 8€&Ìü>Êë FÀ8À!1¸w$†â6Þ×ָœõþ8ðÿž PDPäÓýþ•ü†@P.®`¤7 Ú#œa@ =A¬–FB9‚1(\<ØŒpÛá~Wj(Á¸ÿ¶‡ ®XŒ áü«E¡_ip§¬Ž„ª¢\\`H,ð«>5Á»·ÐŸÉ:!QžHß¿{jÿ« ¨»«)áæÓVû낃 ÿÆà0,PBXFRR\s¼ B¿Ò›x»Â~E~Á¸ü}]Q®@{\0„=÷øbÀ0 íó÷ýOÃ?W Áí`pðïì8fÿg>á ã¸'þõüï—5Ž^PÒÙûßî¿ç+¤¡ýÀBK‹ïOÇÿkSQAy}Ä„2@i  ””ÐÿŸiÁˆ¿eÿ;ViÊü©wLÿªØã/¸ÿŠƒøÏ\÷P8Ö€Üÿ&¹•°„0÷#òÿMõß!ÿ7†ÿÊòÿ"ù¤áîìüÛÌýÛþ˜Á.gï¿8ÒºcqÐGád€üoWsØÑêàw—ÿ¶jcÁ8!(#á82ˆˆ ‹ÿÁ „jˆÀBþPænúKjÎ$Ì…Aüº[pQÂÂÿeÃéâ„»?08^þ6Ápòùç¾êH úKg¢’@0 öãè$Š›·¯NP˜×o&…‘(,.ˆëÑhB~U(ÆàzF`œpSpøeü‹K…ìÀèÿ Dq 9Ãì±ÿ‹ý…ÿLûþ!îh4N¨¿y„«þ_ëß·æƒ >N¢ r¡Ž5¡ÍÇUÊŒž+ï‰>·F%XtGJ`9§žû:è]ÍÔsSy-¿5f8]>:éÇÈ»u<äeÕž4Ÿªõ‹§Þ½¤²#Û²×‡1AQða©´¨%ŠíD£;dA„ ®'æ“çaRbk«­˜5K™o@àËCr–TFìcåœÖoø1,쟱ï,¬Èã(Ñ twmÓáüDÜ‘Js,ý‰÷(.ãÝÜ\_vOwšØnžng¥dy8=µKÎ@R/=Mb¶NSEâPµ8%•þ…K8ç<¸»ó#H¦ñíLŸ}õñvâ¾Fƒ¡#¨uzLG êo·Ó]3gpÍ)ˆR¤y32’t:·­³Á]O¼¢h•Œóë×/ˆkÞ[·7»¨Ð«JFBšË 73ØèÕÔîhÜ¢‡F* °”È–ö—ŠËŠºí£ÜyäáU}@LVE£hü f^™GÁÉØô<•Vö±Í±zžø¦·Ü¥à½}¯úRŠT³=yW7—ÛÏØõN˜¡7ë—¨ÎÓ~±o³Ìx«q„þH¶ûV"´q;ÅÎjŽ"!‡…eíI=ë-œÏWÞ÷Zݍmô˜sÌz×ðê45°5p=õnÐçqVË:ž¼‰Ë4Z¦™fÿN:›÷‹)Š_}F:§¯‡>ÙEûT~Ûv»b+$™•'mœ:æ›KöÞÖ|©d³8#Ê¿aú:¨³Ú; Þ¡LYØÁ­Bœ}ëó¿&±ð° Gxèó%4O«Ãá=‡3ç֏ž ²€h¢`‡Ñnyé-!ürу±wo´žï©T/ôÛ2×m0Ö†¯n ¾3íç#BŽ‡±ea)â>ž,ÑÄã«£,¹ï _ä"wÍFtðeijIý/Âñ3\“8“4¹¿»D¯Je$»°ØÜMŽUø©‹°ße½>óÁµ'°bzM‹éüB­´y”“bª¤oi£ÈQóÉj÷ dµÜß4e¶®FR˜ñsQ›ûs…C~8$t‹YË59Ôz\Æ3C×[Ÿ¸dJDùF:‘3ˆË~N¦£8”—<$ ÞV‘l¡1šˆ¤:ÿH$æöùv;y4WÜÕg—€š@g)oa8{í× 9-Ó>Áç~ ^ŽTañ1¾,—Š§¾4\솵ÍÉCiïH\µÙ½CjŒ»Ä˜áçPtNè÷C&YÉLýŸ™mWeÂ>¨v™1¨.XÄ : o9jKP¡œUŸ¥öÑùɃŸt¹Ld.ûåÑ•EJmô¹}½¡°ñ‡#}‰#¤&RÇfRøJð ýK¿=}ªáÜ^ÈZ“™æRÏÊà<Šjyϵ H™l^Gý@!Hþæ­[]ÖÖØ L>A®‘û‰ïSÿ’'$r)Ë>>e)Zs-]Õ/!–0}ïΏ§…輂™*9JÀ­‰º'xF…Æ’èë–Ÿ¢ÙÎ{¾ùôœštî³ÈGðzÓZ«Lç¾ò:.zÀÔLàÆnÙúþ˜9²O2[XTWÿ¹ØãšV`¦o<~{zå"b>”+ø3M‹ää°ùÀP[ å&©•…ËcÅÞM™,š@ (GnÅwÝٻɟ…õ5 -|Ù!M†ºG@ëó.üÀ¶ ¼r=úÌëû%œ{ãõ±k¤–A>#7D@GrâËA®6ëõ÷¶]ÏJÜTÔ€”d\ÓQdz4\#æßgP