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This study synthesizes adjacent research and introduces Enactive AI as a conceptual framework for enterprise and industry reasoning, site-level decision support, and execution feedback
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https://arxiv.org/list/cs.AI/new
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Artificial Intelligence
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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/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.CL/new
We evaluate five open-weight readers with Vanilla context, BM25-RAG, Oracle retrieval, Memobase, and MemSearch as memory backends
https://arxiv.org/pdf/2407.00323
Цäù÷È"ˆSF\ó¼|û‘ø“XäP˜ôÓáIH{Ф{ü |ÆHÙK�è‚Oõ÷¬VبÔ$£²©Ø Orÿ&÷ðù®Ýe²;kxva¿£Ag¯°0W½j×ë% ìWî/G’: @L$Û"Æ@ûhx ªÕq€}Ù¢"3'“ÞÖ�a&�CÓ÷Çóºû±ÄØ4wœ×sÒŽ ͆°cY⤄ 4=ˆ:žu çaD§�6v�€D“ñ—„¡þ†C:´³v³S¹
https://arxiv.org/pdf/2608.00785
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https://arxiv.org/pdf/2005.14165
{ê´™ÖÝÆ[§uÊxÀ‚µ³~ Çtßú�œœ˜ ¯ÁíííYËÍÍÍ;Þi;ëw~~îî ð\^^¶p···ïu§WWWí�^__»û ¼gggíÜýýý{Ýé—/_Ú;-ŠÂÝ à5øôéS;÷ŽwzrròAR� ¼
https://arxiv.org/pdf/2407.00125
Reliability.Performance.- Software and its engineering -> Software organization and properties.- Computing methodologies -> Artificial intelligence.) /Title (A Survey on Failure Analysis and Fault Injection in AI Systems) /Trapped /False
https://arxiv.org/pdf/2608.03233
, ZæJìJ” �,’_ßSö’–lôbÙógÞ¼!)s±˜ñ4c‚%’³„eqÌ$ƒH –2àB²Œ�ˆb–3HŽƒ`�Gøƒ3I¤bÈŒó 3$ŒÇ×JÆ…ÀgŠO™ýôæ Û¿7�ö7{(̨w�±�x‚Ïn3ÇzmÝfÔ«%b[+,‚Ÿ¶œT‰½qßà±=‰õ4Ùb4Ýà& `[z©üÚUm¿ÁÍâgY6qz×›Séž ?ê¢u3yx2åÔë]¡:R²ƒ[V–Aìûò2á˜äA«fЪ/*ÂýYÿ¨œq²QEe¬þG
https://arxiv.org/pdf/2407.00273
YŽi»Ìk%êå ãm«ð ‘dázþZnJWÏó+í-èeiÆYêp©ëÒܤGTÉ@Ëým…T¯ÑÙÊ{«"¡�K|ãQßçJ@ó¨�úZ¢{/žÞÐCYëáH‚Æ à¨º¦ŽqHÄU
https://arxiv.org/pdf/2005.13905
&Q,l@2`„0!À`0ƒ1 À£$4g*S9g¾ùÎÃ9÷Ìó�~üã‡ÂPj÷‘ï?ø•¯}–“7ãZ+·�×½á7/mœÚê_^m�ûÊ7?ïGÿô™S�ž_9Y,|Ù?qâAïÝBÿJóU$è+{æaFÚB%„¥´5|!_èF04à Ùî0ê«kÁ ¨Äžt²:�fJ’5^€�c`츾âyZÛIâà˜Fv[Yb4 áhóE9'�'�“HC³&¤3h¨j|ÀwÅæ“’cM�}¡iGœ{þÄõXÛ
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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https://arxiv.org/pdf/2407.00215
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https://arxiv.org/list/cs.CY/current
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Computers and Society
Authors and titles for August 2026
Total of 256 entries : 1-50 51-100 101-150 151-200 ... 251-256
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https://arxiv.org/pdf/2407.02402
áÀ߯«›ÀÌjDÕå²»«ífðãc;ZæÕÁŽÌ«Ÿ¶®MfGÑÏ}í q•]/¶ìÞÍmÞ¯¶o⣩²íÄ0ZÇë²è^œx]fçkn{ÕÿE+{*ʧyÄpg�6;5’PìŠîìVž¤pH8$hù—mÚ¢*ß„z•R:")ó¨º ÊÖß3‰qŸûX”ysO'Hî)-ò"ëî}³‹³‹ÍÛ[ÛÙ˺s �á3 4†{´¢p¿YôdšrýØëKæ‘+ˆ™ÇÞ a }ÀõàíÑ« W€‡Œ{ Fvm734…4˜‡¢´�A«»èGÞÿc
https://arxiv.org/src/2002.02145
›SæùiæGnÆf‰ Y¥µA�9KüiŽÂ©qÖdXÎD¦„‰‘Eò£9ƒà«Yv¢âGMÌVz´Æ%ƒVfSR9KªdÚ�”H‘a¶š®O�€ˆ8Sy% !�(k‰7µÔİOÏJC¤ >À�dàkê$~€,®‰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/2508.02686
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https://arxiv.org/pdf/2210.00105