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30 result(s) for “okapi bm25 site www eyespy cy site www is gov site www tract com site:arxiv.org” of 68 matched · 667 ms
Scope: Nishi’s own index (our crawl + Common Crawl) — not the whole live web. Some sites block all automated crawlers (anti-bot walls), so their pages may be absent here even though we never filter lawful content.
Freshness: no result on this page carries a fetch time yet (indexed before the fetch epoch was stored beside the doc)
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
com/JetAstra/PI-Mem
Introduction
The ability to reason over long contexts is increasingly important for large language models (LLMs), supporting applications such as long-document question answering (Gemini Team 2025; Yang et al
https://arxiv.org/html/2501.13956v1
com
Abstract
We introduce Zep, a novel memory layer service for AI agents that outperforms the current state-of-the-art system, MemGPT, in the Deep Memory Retrieval (DMR) benchmark
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/list/cs.CL/new
Many practically important problems are naturally treated as black-box optimization (BBO) problems, in which only objective values are observable, and the functional form is unavailable
https://arxiv.org/list/cs.AI/new
, the meaning of a customized field) originates from users' domain knowledge and is rarely documented publicly
https://arxiv.org/pdf/2608.02615
mNJ3mDbwF=Ml;x,qq,ޣ^}ZXy:wWW|
https://arxiv.org/pdf/2006.00342
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https://arxiv.org/pdf/2006.04122
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https://arxiv.org/pdf/2608.03118
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https://arxiv.org/html/2407.16741v3
edu
Abstract
Software is one of the most powerful tools that we humans have at our disposal; it allows a skilled programmer to interact with the world in complex and profound ways
https://arxiv.org/html/2608.03154v1
org perpetual non-exclusive license
arXiv:2608
https://arxiv.org/pdf/2607.27188v1
) /Title (Inverse Learning of Latent Risk-Neutral Densities from Irregular Option Quotes) /Trapped /False /arXivID (https://arxiv
https://arxiv.org/pdf/2608.02122
) /Title (DEFT: Joint Task Placement and DVFS for Energy-Efficient Multi-GPU Runtimes) /Trapped /False /arXivID (https://arxiv
https://arxiv.org/pdf/2608.01785
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https://arxiv.org/abs/2608.03883
arXiv is committed to these values and only works with partners that adhere to them
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
arXiv is committed to these values and only works with partners that adhere to them
https://arxiv.org/list/cs.IR/new
IR)
Industrial recommenders increasingly adopt the pretrain-then-transfer paradigm, yet behavioral distribution drift raises two questions: what to learn from behavior sequences, and how to transfer the learned knowledge while the pretrained model is continually refreshed
https://arxiv.org/html/2607.28847v1
A parallel and increasingly intertwined regulatory concern is the explainability of automated credit decisions
https://arxiv.org/list/cs.CY/current
251-256
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[1] arXiv:2608
https://arxiv.org/pdf/2608.02867
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https://arxiv.org/src/2006.02155
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https://arxiv.org/pdf/2607.26405v1
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https://arxiv.org/src/2006.00508
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https://arxiv.org/src/2407.17789
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https://arxiv.org/src/2006.01331
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https://arxiv.org/src/2104.08691
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https://arxiv.org/src/2006.02833
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https://arxiv.org/src/2006.00342
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https://arxiv.org/src/2005.13905
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