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In our context, a message consists of relatively short text (several messages can fit within an LLM context window) along with the associated actor who produced the utterance
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https://arxiv.org/html/2501.13956v1
2 Knowledge Graph Construction
2.1 Episodes
2.2 Semantic Entities and Facts
2.2.1 Entities
2.2.2 Facts
2.2.3 Temporal Extraction and Edge Invalidation
2.3 Communities
3 Memory Retrieval
3.1 Search
3.2 Reranker
4 Experiments
4.1 Choice
https://arxiv.org/html/2608.02613v1
We evaluate five open-weight readers with Vanilla context, BM25-RAG, Oracle retrieval, Memobase, and MemSearch as memory backends
https://arxiv.org/html/2608.03048v1
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https://arxiv.org/list/cs.CL/new
We evaluate five open-weight readers with Vanilla context, BM25-RAG, Oracle retrieval, Memobase, and MemSearch as memory backends
https://arxiv.org/list/cs.AI/new
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Artificial Intelligence
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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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Information Retrieval
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Wed, 5 Aug 2026
https://arxiv.org/list/cs.IR/new
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Information Retrieval
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https://arxiv.org/html/2407.16741v3
2 OpenHands Architecture
2.1 Agent Definition and Implementation
2.2 Agent Runtime: How Execution of Actions Results in Observations
2.3 Agent Skills: The Extensible Agent-Computer Interface
2.4 Agent Delegation: Cooperative Multi-agent
https://arxiv.org/list/cs.CY/current
02551 [pdf, html, other]
Title: Who Should Be Generated
https://arxiv.org/abs/2607.29380
the Regeneration of Professional Expertise
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Computer Science > Computers and Society
arXiv:2607.29380 (cs)
[Submitted on 31 Jul
https://arxiv.org/abs/1411.2842
Lethal Autonomous Weapons
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Computer Science > Computers and Society
arXiv:
https://arxiv.org/abs/2510.01395
Yet, beyond isolated media reports of severe consequences, like reinforcing delusions, little is known about the extent of sycophancy or how it affects people who use AI
https://arxiv.org/src/2006.03178
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https://arxiv.org/list/cs.SI/new
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Social and Information Networks
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https://arxiv.org/src/2006.02318
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https://arxiv.org/pdf/2608.02833
KZ—Ms^7°\µé’N�aÓæ×ÿÖõ§®ÐϹ£«}\®vh=§Ç« ¹ªÙÇfþCyÜTÿ‹ÚLäzŠ�ëÕ4o´^ÍÚzÎ×ûY~╟³@u}7زœêcƒñ|Õüç‡å|þ Jòç¯ÐZ¯+q5wWóô¸™¼+ {ÜÀçr:=æëaûi+túYŠqy Wp¸¤ôxÞŒêÕ|…+ÈZò¶r§þZ¯÷q=åWpñx™+È»ÞÖ™_Mv¨ÿ-ôtº õ†L¯ë´nÀ*_ÏØu§–ë:}½ú%v,]qɶ3ÜP©WJ_wCúÝo¾ûþWÿpy~½
https://arxiv.org/list/econ.GN/recent
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General Economics
Authors and titles for recent submissions
Wed, 5 Aug 2026
Tue
https://arxiv.org/pdf/2609.03103
ãÒÊøËÒòËUôñÜ=d �êdY…�²Ä ß*Ë–€Ñþ€gÔYÎ÷äÓʤ•%xÑÉ(×™§ì²œK MdWG{˦×ÅN–¥ Ûg)ã÷\÷#t·8–JIƒ)q ï*ÿ)Ÿ_5'ÿG‰A“FßÃÅy£�bþ–ú�§ü½@~“Š–g“«fí®îO/î_¤Ñ¸Ç±l®^,S^1(n,ÈóŒ0jo�'qÉnEPU’³¸£,yÏåtq;›|))sUµ�2m辡²8’ÕÒô�´Á‘QÒ�Ôì ¬VÊÖdU—ÄÝ—äCy,Oäë”NÊòwy%¯s6)o§)Ÿ”KJ ›åD~n
https://arxiv.org/pdf/2607.26327v3
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https://arxiv.org/pdf/2407.02402
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https://arxiv.org/pdf/2407.00345
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https://arxiv.org/src/2002.02145
›SæùiæGnÆf‰ Y¥µA�9KüiŽÂ©qÖdXÎD¦„‰‘Eò£9ƒà«Yv¢âGMÌVz´Æ%ƒVfSR9KªdÚ�”H‘a¶š®O�€ˆ8Sy% !�(k‰7µÔİOÏJC¤ >À�dàkê$~€,®‰H8‰»ð¯PK@-�J&Ë�ò~ºpÇ=�áºCm¬ø>ŽEòÀuRÁà�Ÿð¯ù)ÌŸð§üþ-Æÿƒÿ'Î_ð—ü;þŠÿ�¿æoøÿžÿ�ÿÀä?ñÿR„Øsymrø”»Üã‚Ïøœ/¸Ï
https://arxiv.org/pdf/2608.01564
ZæÚ¬eË�äÝì¿ï )Û¤(mzY¯†�3ï=)XÆS%“ŒçS @°œA%XÁ¤ÊYÉ ^²ŠñLüø |àˆÎ Æ�ñA‡*ŠKáœòTø‹™dŽ¿ƒ+&J„%üôö-»»G’HþOv÷‡ù> ÷ÿÝ™ã@ÕýóW;4† îžÞ½g ð£ïÛ3‚ßv÷«íúMpá�ÿçBé¹�ó¾tæ‘ATLNŠ© �вˆh^1™WFõÅÜLW]†YdfùhvèÙ?ìÕ‡¶~ó× »á5{¥O'sÜØï«û×ìÐ3Åpî
https://arxiv.org/pdf/2608.02609
,”œ6ýúJtLÊ’ ËÎåÌá5&(Bñ1„‰@!�H"PŒ(g(A G(E,Nüà .‰H€?ŠŒ0E)‡;H€)\9X0\áCSŠp & _ ˜lø$àO"ø ±Ã �Ò)\Á$R†|R7Ql�¢ª€ÅpNîSD°lšFœá °(A,â‚àÓßÞ¿G“�~oÐäJýh ïö÷µ4ªl,°ööN7…‚œí݇›ÀÔdƒ�×F½ â'a8LÂÜê´ZCÜ1E“�ÚÔ °Þš/$ü޽:ÉxÔa½
https://arxiv.org/pdf/2412.12213
Finance-Informed Neural Network: Learning the Geometry of Option PricingAmine M. AboussalahXuanze LiCheng ChiRaj Patelhttp://creativecommons.org/licenses/by/4.0/cs.LGq-fin.CPstat.ML endstream endobj 4 0 obj > endobj 5 0 obj > endobj 6 0 obj
https://arxiv.org/html/2508.08980v3
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arXiv:2508
https://arxiv.org/pdf/2608.01366
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