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30 result(s) for “okapi bm25 site hotshops pp site model kb be site popups use act be site:arxiv.org” of 223 matched · 742 ms

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Did you mean okapi bm25 site hotshops pp site model kb be site popup use act be site:arxiv.org?

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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
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https://arxiv.org/html/2608.02613v1
Code, the MASim simulator, and the MemArena-L benchmark will be released upon acceptance

Artificial Intelligence

https://arxiv.org/list/cs.AI/new
Our approach utilizes a two-stage generation process: first, the model is prompted to self-select a unique, idiosyncratic persona to anchor its starting point; second, we apply a dual-stage sampling sieve, utilizing Top-$p$ filtering to preserve grammatical validity followed by extreme temperature scaling ($T \ge 4

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https://arxiv.org/html/2608.03545v1
org perpetual non-exclusive license arXiv:2608

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https://arxiv.org/html/2608.03154v1
Previous BioRE approaches can generally be categorized into rule-based systems and supervised transformer-based models, each with distinct strengths and limitations

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https://arxiv.org/html/2608.03048v1
To discourage redundant turns, we optimize the workflow through reinforcement learning with an auxiliary turn-efficiency reward, enabling the model to adaptively exit once sufficient evidence has been accumulated

1 Introduction

https://arxiv.org/html/2501.13956v1
Since entire conversation histories, business datasets, and other domain-specific content cannot fit effectively inside LLM context windows, new approaches need to be developed for agent memory

Computation and Language

https://arxiv.org/list/cs.CL/new
Recent studies have therefore examined how to automatically derive optimization problems from natural-language descriptions, but existing benchmarks focus on settings where objectives and constraints can be written explicitly as mathematical expressions

Information Retrieval

https://arxiv.org/list/cs.IR/new
However, skills are naturally structured, multi-field objects, where each field provides different information about when and how the skill should be used

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https://arxiv.org/pdf/2607.27070v1
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https://arxiv.org/pdf/2508.11152
document was published isbn Text external ISBN for the publication in which the document was published doi Text external Digital Object Identifier for the document url URL external URL at which the document can be found byteCount Integer internal Approximate file size in octets pageCount Integer internal Number of

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https://arxiv.org/pdf/2608.03883
If defined, must be one of book, catalog, feed, journal, magazine, manual, newsletter, pamphlet

1 Introduction

https://arxiv.org/html/2407.16741v3
In particular, AI agents, systems that can perceive and act upon the external environment, have recently received ever-increasing research focus

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https://arxiv.org/pdf/2102.13654
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https://arxiv.org/pdf/2205.01882v5
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https://arxiv.org/pdf/2407.02402
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https://arxiv.org/src/2006.02464
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https://arxiv.org/pdf/2006.02318
If defined, must be one of book, catalog, feed, journal, magazine, manual, newsletter, pamphlet

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https://arxiv.org/pdf/2608.02817
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https://arxiv.org/pdf/2608.02758
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https://arxiv.org/src/2005.13905
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https://arxiv.org/src/2405.20232
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https://arxiv.org/pdf/2607.26188v1
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https://arxiv.org/pdf/2407.02510
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https://arxiv.org/pdf/2608.02867
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https://arxiv.org/src/2006.02230
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https://arxiv.org/pdf/2006.01128
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https://arxiv.org/src/2006.01354
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https://arxiv.org/pdf/2608.02122
) /Title (DEFT: Joint Task Placement and DVFS for Energy-Efficient Multi-GPU Runtimes) /Trapped /False /arXivID (https://arxiv

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https://arxiv.org/src/2006.02893
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https://arxiv.org/pdf/2005.14165
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