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30 result(s) for “okapi bm25 site hotchips pp site www is gov site www if org site:arxiv.org” of 126 matched · 464 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
Then it must make an even harder judgment: even if the answer is known, is it actually appropriate to tell Bob
https://arxiv.org/html/2501.13956v1
Consequently, additional context is required to provide out-of-domain (OOD) knowledge and reduce hallucinations
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/2205.01882v5
2 Details of the DVD Dataset
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https://arxiv.org/pdf/2402.03300
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https://arxiv.org/pdf/2608.03883
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https://arxiv.org/src/2006.01048
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https://arxiv.org/pdf/2508.04671
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https://arxiv.org/src/2303.12712
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https://arxiv.org/html/2607.28577v1
org perpetual non-exclusive license
arXiv:2607
https://arxiv.org/html/2608.00458v1
org perpetual non-exclusive license
arXiv:2608
https://arxiv.org/html/2608.02918v1
org perpetual non-exclusive license
arXiv:2608
https://arxiv.org/pdf/2005.14165
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https://arxiv.org/pdf/2608.02758
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https://arxiv.org/pdf/2608.04008
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https://arxiv.org/pdf/2607.26405v1
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https://arxiv.org/pdf/2407.02510
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https://arxiv.org/src/2006.02759
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https://arxiv.org/pdf/2608.03833
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https://arxiv.org/pdf/2407.00125
) /Title (A Survey on Failure Analysis and Fault Injection in AI Systems) /Trapped /False /arXivID (https://arxiv
https://arxiv.org/pdf/2508.11152
3/ Trapped Text internal Indication if the document has been modified to include trapping information XMP Media Management Schema xmpMM http://ns
https://arxiv.org/pdf/2006.00342
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https://arxiv.org/pdf/2303.12712v5
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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/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/html/2609.02852v1
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https://arxiv.org/html/2609.03027v1
Report GitHub Issue
Description:
arXiv is now an independent nonprofit
https://arxiv.org/html/2609.03159v1
Description:
arXiv is now an independent nonprofit