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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
02604 [pdf, html, other]
Title: ISEE: Interactive Semantic Enrichment for Database Fields
Yuan Tian, Yiru Chen, Rakesh R
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/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/list/cs.CY/current
251-256
Showing up to 50 entries per page: fewer | more | all
[1] arXiv:2608
https://arxiv.org/list/cs.SI/new
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New submissions (showing 4 of 4 entries)
[1] arXiv:2608
https://arxiv.org/pdf/2402.03300
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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/list/cs.IR/recent
02880 [pdf, html, other]
Title: Field Aware Agent Skill Retrieval
Paimon Goulart, Liang Wu, Kelly Wan, Evangelos E
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/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/list/cs.IR/new
02880 [pdf, html, other]
Title: Field Aware Agent Skill Retrieval
Paimon Goulart, Liang Wu, Kelly Wan, Evangelos E
https://arxiv.org/abs/1411.2842
2842] Logical Limitations to Machine Ethics with Consequences to Lethal Autonomous Weapons
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https://arxiv.org/abs/2607.29380
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https://arxiv.org/abs/2510.01395
01395] Sycophantic AI Decreases Prosocial Intentions and Promotes Dependence
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arXiv is now an independent nonprofit
https://arxiv.org/list/econ.GN/recent
03596 [pdf, other]
Title: Transnational political violence in African borderlands
David G
https://arxiv.org/list/cs.LG/2024-12
3251-3298
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[1] arXiv:2412
https://arxiv.org/pdf/2407.00345
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https://arxiv.org/src/2205.11916v1
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https://arxiv.org/html/2508.08980v3
org perpetual non-exclusive license
arXiv:2508
https://arxiv.org/pdf/2608.01366
) /Title (Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution) /Trapped /False /arXivID (https://arxiv
https://arxiv.org/src/2006.02318
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https://arxiv.org/pdf/2104.00446
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https://arxiv.org/pdf/2608.04341
) /Title (Continuous Improvement and Parallel Autonomous Exploration: An LLM-Agent Framework for Searching Large Solution Spaces) /Trapped /False /arXivID (https://arxiv
https://arxiv.org/pdf/2607.28577v1
) /Title (Train Often, Deploy Selectively: Forward-Gated Model Replacement in Crypto Markets) /Trapped /False /arXivID (https://arxiv
https://arxiv.org/src/2205.11916v3
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https://arxiv.org/src/2006.01048
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https://arxiv.org/pdf/2407.02510
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https://arxiv.org/src/2608.03994
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