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11 result(s) for “okapi bm25 site www eyespy cy site export nara gov site www key ed site:arxiv.org” · 604 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
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https://arxiv.org/html/2608.03048v1
To address this efficiency bottleneck, sparse attention restricts computation to selected tokens or key-value blocks, whereas recurrent formulations of linear attention summarize preceding tokens in a compact state
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/html/2501.13956v1
Retrieval-Augmented Generation (RAG) has emerged as a key area of interest in LLM-based applications
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/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/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
generation for scientific question answering over CORD-19
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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Information Retrieval
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