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30 result(s) for “okapi bm25 site hotshops pp site accelerate gov re site www news nil gov site:arxiv.org” of 42 matched · 500 ms
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The query asks the model to recall the topic of an earlier conversation about Tesla; the gold answer is anchored in one specific session about Pooja’s dig site
from the top result below
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/pdf/2402.03300
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https://arxiv.org/pdf/2005.14165
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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
Biological systems, in contrast, exhibit adaptive plasticity, maintaining function through dynamic re-organisation around damage
https://arxiv.org/pdf/2407.02402
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https://arxiv.org/pdf/2102.13654
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https://arxiv.org/src/2608.03883
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https://arxiv.org/src/2006.01354
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https://arxiv.org/pdf/2608.03233
T+jq8 M\c~wD`%::P sC` zzTrH`${0F{kʆƄ endstream endobj 411 0 obj > stream On the Diversity of Analogy Making in Large Language ModelsYuanhao ShenDaniel Xavier de SousaCaio César Sifuentes BarcelosHongyu GuoXiaodan Zhuhttp://arxiv
https://arxiv.org/src/2211.01910v2
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https://arxiv.org/src/2608.03882
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https://arxiv.org/pdf/2608.02851v1
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https://arxiv.org/src/2006.01402
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https://arxiv.org/src/2006.02464
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https://arxiv.org/pdf/2508.16279
AgentScope 1.0: A Developer-Centric Framework for Building Agentic ApplicationsDawei GaoZitao LiYuexiang XieWeirui KuangLiuyi YaoBingchen QianZhijian MaYue CuiHaohao LuoShen LiLu YiYi YuShiqi HeZhiling LuoWenmeng ZhouZhicheng ZhangXuguang
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/2608.03048v1
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https://arxiv.org/html/2510.03215v2
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https://arxiv.org/src/2006.02230
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https://arxiv.org/pdf/2608.00785
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https://arxiv.org/pdf/2608.01785
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https://arxiv.org/pdf/2608.02615
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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/src/2509.02523
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https://arxiv.org/src/2205.11916v3
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https://arxiv.org/src/2006.00441
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https://arxiv.org/pdf/2506.01844
SmolVLA: A Vision-Language-Action Model for Affordable and Efficient RoboticsMustafa ShukorDana AubakirovaFrancesco CapuanoPepijn KooijmansSteven PalmaAdil ZouitineMichel AractingiCaroline PascalMartino RussiAndres MarafiotiSimon
https://arxiv.org/pdf/2407.00132
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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