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30 result(s) for “okapi bm25 site www eyespy cz site www beta cz site:arxiv.org” of 71 matched · 327 ms
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For each evaluation sample, we construct an Okapi BM25 index over its decoded text chunks; the index is therefore sample-specific rather than a shared external knowledge base
from the top result below
https://arxiv.org/html/2608.03048v1
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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/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/2205.01882v5
2 Details of the DVD Dataset
M Additional Empirical Application: Fishing-site Choice
M
https://arxiv.org/html/2608.03446v1
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arXiv:2608
https://arxiv.org/html/2608.03624v1
In domains such as healthcare, this is a hard requirement; sensitive data cannot leave the premises, so models must run on-site, often on limited hardware Garg et al
https://arxiv.org/html/2608.03504v1
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arXiv:2608
https://arxiv.org/list/cond-mat/new
The mixed anomaly between these is accommodated by the not-on-site action of the symmetries
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
IR)
Tue, 4 Aug 2026 (showing first 34 of 45 entries )
[17] arXiv:2608
https://arxiv.org/list/cs.IR/new
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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/html/2608.02813v1
Wind Turbine Generators
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[1] arXiv:2608
https://arxiv.org/list/gr-qc/new
\frac{r}{r_0}$; (v) $A(r)=B\,r^n+(1-B)$; (vi) $A(r)=r_0\,\frac{\mbox{ln} (1+r)}{\mbox{ln} (1+r_0)}$, (vii) $A(r)=r_0+a\,r_0\,\left[\left(\frac{r}{r_0}\right)^\beta-1\right]$, where $\beta<1$ and $0 < a\,\beta <1$
https://arxiv.org/list/cs.DS/new
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https://arxiv.org/html/2607.27099v1
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arXiv:2607
https://arxiv.org/html/2608.03086v1
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arXiv:2608
https://arxiv.org/html/2609.03027v1
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https://arxiv.org/html/2607.27063v1
-Based Network Model with Information Diffusion
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https://arxiv.org/list/astro-ph.IM/new
Total of 28 entries
New submissions (showing 11 of 11 entries)
Subjects: Instrumentation and Methods for Astrophysics (astro-ph.IM); General Relativity and Quantum Cosmology (gr-qc)
With the observational accuracy of astrometric space
https://arxiv.org/html/2607.28127v1
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https://arxiv.org/html/2608.02966v1
-Choice Benchmarks
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https://arxiv.org/html/0804.0969v1
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arXiv:0804
https://arxiv.org/html/2608.02851v1
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arXiv:2608
https://arxiv.org/html/2608.00458v1
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arXiv:2608