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https://arxiv.org/pdf/2608.02851v1
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https://arxiv.org/pdf/2608.02666
'±üd$ ëÿìWõUóÒäˆ)‚]ŠÍîêêºWu“ÿˆ¾‰þÝ}ñ£‹~ø1JõïÇД&YÁ{þS¥.i³è‡¿E¿xŽŽi’¦y=ÿUµöÂ%¯]REY»yþ[t÷üœE.zþKô]ÿäê::º(Þòò�—.Yïy9Œ_bÞ¾\_odäGvºaë-KF�üŽ�){:^>^oÊu¦ _^GmýÏŸ£o£¿oÞ¤SÐ9èTQ©NáR»2)Û¢Œ\[™NUçtÊE¤:µód¾€Šý¼MÕ&UYb½-Ä@uÙæ�%
https://arxiv.org/src/2006.02055
óÀ8©�˜Ü ±Ùã'׿ܳûoûôe¿kA îÃÜêË@œV ¿�Îwà/¶£Ø/¹ûȰ3"ǧ¥Þ•PYÓF«ùÆ%ÍkþnԜáj73Ø’œãÈ¥û&{è�~Žf«E ˆšÚü\î>`¾¸>ïPL¹¦©vµ§ß†ËÈ>’ß4‘ùX¿]·‰ƒãzÄ p&'°%›ø€KbžÙF �&›àŽÌhöœ8o˜&&ÖÕ\ÀüÂü‚œ¯É¬ªàÑ„}àWâDå—”4w%æÅñS99ÍÀøî3Aªc:"ú;ùñvaXMÝϼ‹ô“6¨¸êìÂÍ)¥ˆ\¨#‘êð‘cúuRÞj“/Yù9ž©±Ë©õâÑ0XrÚ±ŽÄSöùÐPê�a—g]¡#KÓNÐõ
https://arxiv.org/src/2006.02464
Ýï>Ó>ãñ!ÿŧýŸ£/ìáÑáh4>�¾èÛöÐî!ú¿BõO–¤2â‹8ŠÒÛàÞwÿ/ú #Ð,ÿl4þþüI©~–Ë¥ ]ïÚJÕõï²Çíöo�‡ƒÃÂþñ ö?÷í¿íÿ�øt&…ø;�I¢œÔ‹Âíiœz3é¤âÔÜËéf6-ïO“4Æ}üüz¡„,À�(L¼$MD4ç~ä\£øê¿±Œ£4J7K%’(‹@Wu…b™Œ—LÄ,ŠÅ4ó|×çbG��í ºÂõbU\Æj)c‚L±¿ W^…� SKB;
https://arxiv.org/src/2608.04003
$Y 0úÑÝ"‹‡ç~¾sªºßÿöÍ«/Þ½éý”'ñ'¿Ï§�ÏtÉ’¤xߺÝÿý:J©'yRf¾ÉŸ¨—꺀ÏÁþ¦Ûe®×†n>)’42÷&zÒmÜ^…‘‰õVVlu÷ óðÄ.8vßK0\ÇIf'çGz·4±¿Yd&Ò… »$»Ã—UÞ[†Ëê-ôûÇ®“qo²§{$*N ¼/èÐ+$\5‡€l]µ5þFÇa¾Í‰2w|¤:á*…UÉÚ¹2Úßt*�~ =0²oW-ËB…¹¼H-÷…ñVIæÑ*0+]F~§Q²'Æ{
https://arxiv.org/src/2006.02833
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https://arxiv.org/src/2402.03300
íÙ›½JÝÉU‰¯»Ñh4 €²'¢ˆÆ~¶-Ùü«ß鳟gÏöÔ7|ŒïÁ_»ý¯ú{Ïú»ƒþ^°ûÕNÐßÙýŠìü^ Õ?y&iJÈW©ò>º‡ð/ôãÄìÎÓ>P8a&£eá€+ÈÌ+FWãÓår£AwK²¦8†'ƒ€JW"ðÉ `±'|–ÖÄ•%á-[Ôˆ^Á“Að)gi�äµz6ˆîüaogYl'dŸÈ“�í§›Ë-Ò Øík’ýXz¶»âž ·bÞÜ µ š›ìãMK];Vý�FúÄ‚O54°¡Ýï5´kéõ´Tyï
https://arxiv.org/src/2006.02155
¥Ú’–�™YÁ“NóhZï Œa·¼¥�VÁñÅç¿*޹0d”•÷œ³¨ö´Hjze³¦¢íð$aìü?_ªkÓl!¥Dûsõ…n`&Þ*©åN%¾b¢7i¿éÑ®p:ˆöE¿T—°¬Ù§4¯‘›ÀsJø¹ƒøfÁ›|ð’� î�u*Æ$fÒò÷ÄÁËš«?C‰8œ„Àþ©oÝdkzyQ::¾Ûh[ú3ìlÁ‹þÖÙ†Þ¶ÙÈBt¸ªðÛœÇäñ¦òÆdÊ|J[ß+ƒáUsì‚/g®êš,†eÑNVÉÕ©i…HìÂÎ
https://arxiv.org/pdf/2006.01402
µýæ—_8 b½±/¬¬¬UYyWÑ»y¾ñn¾ù̳ò/ï?ûüë4½Ùo÷I�ܼº‰vF7in½ýÍûâæa“µîö>ŠÒMÝôÊã)Ë{WlY}°]~pÅP¹ÕdSvD?fù‡[ßÛ¸Âê/,3OMëò¬ëËúùö×÷ÿ%»÷ýí>Nøù¼9žšÚÕøö.Þt Ë^ËhsÈÚÚu‘Y}ëÇ›VžZçåŠÍ+·*ˆ¬5ÔÁÚ°ÖûÅ2b.ã¹m†Z6ìüMá{@ž|ÐPÜ ;�Yæ>¢µi?
https://arxiv.org/html/2205.01882v5
2 Details of the DVD Dataset
M Additional Empirical Application: Fishing-site Choice
M
https://arxiv.org/html/2412.12213v2
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https://arxiv.org/html/2407.02342v1
org) Wen Chen is with the Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai 200240, China(e-mail: wenchen@sjtu
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/html/2608.03048v1
com/JetAstra/PI-Mem
Introduction
The ability to reason over long contexts is increasingly important for large language models (LLMs), supporting applications such as long-document question answering (Gemini Team 2025; Yang et al
https://arxiv.org/html/2608.02668v1
Sphere pp-Angular Retraction Normalization
https://arxiv.org/html/2607.27188v1
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https://arxiv.org/html/2608.03086v1
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https://arxiv.org/html/2608.02813v1
Wind Turbine Generators
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https://arxiv.org/html/2609.02852v1
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https://arxiv.org/html/2608.00458v1
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https://arxiv.org/html/2608.03529v1
(2024), where a human expert and an automated system might describe information in different terms
https://arxiv.org/html/2608.03480v1
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https://arxiv.org/html/2608.03011v1
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https://arxiv.org/html/2607.28410v1
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https://arxiv.org/html/2608.00648v1
Distributed Multi-Agent Systems
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https://arxiv.org/html/2608.02909v1
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https://arxiv.org/html/2608.03063v1
8 pp in a production fraud detector serving billion-scale transaction traffic
https://arxiv.org/html/2407.10811v1
II RELATED WORK
II-A Traditional methods
II-B RL methods.
III PRELIMINARIES
IV METHOD
IV-A RL Setup
IV-B Network design
IV-C Training
IV-D Theoretical Analysis
V EXPERIMENT
V-A Towards Real-world Dataset and Simulation
V-B Benchmark
https://arxiv.org/html/2608.03154v1
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https://arxiv.org/html/2410.19947v2
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