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small language model

2,885 papers

#small language model Sep 2026

In RAG We Trust? Measuring Robustness of Retrieval-Augmented Generation Under Post-Retrieval Context Tampering

This study studies how much a small quantized model, Llama 3.1 8B, degrades when a fraction of its retrieved context is poisoned, and treats the strategy contrasts as suggestive until decoding is controlled and stronger adjudication is in place.

Iliano Fasolino · 0 citations
#small language model Open access Sep 2026

Situational Variables Versus Cultural Labels in Persona Conditioning: Shared Stereotype, Shared Rule

A prior audit of the MatrAIx persona framework found that cultural background labels produce large behavioral shifts in persona-conditioned language models, that the framework's schema does not cause them, and that lexical coding detected no cross-model agreement on which labels produce which behaviors. That audit name...

Bianca Dené Williams · 0 citations
#small language model Dataset Open access Sep 2026

Evidence synthesis automation map, and a measured probe of what a web-enabled LLM already does

Two documents, in English and Simplified Chinese. The automation map lists 26 steps of a systematic review or meta-analysis; for each step it records what the job is, which tools already exist (link and price where verifiable, checked September 2026), what a web-enabled large language model did in our probe, and what s...

Chuan Yin · 0 citations
#small language model Open access Sep 2026

介護が必要になった主な原因の 1 位は認知症(10 万対 16,743)だが、当てはまるものを全部選ぶと高齢による衰弱(26,100)——年齢では脳血管疾患(65〜79 歳)・認知症(80〜89 歳)・高齢による衰弱(90 歳以上)と入れ替わり、女性は 1〜3 位が 98 の差に並ぶ [M059]

令和7年国民生活基礎調査(介護票)で、介護が必要になった原因を、主な原因(一つ)と原因(複数回答)の二つの表で、性と年齢ごとに並べた(数は介護を要する者 10 万対)。 男女計の 1 位は、主な原因では認知症(16,743)、複数回答では高齢による衰弱(26,100)で、選び方で 1 位が替わる。男性はどちらでも脳血管疾患が 1 位、女性の主な原因は高齢に...

Yuuki Yamagishi · 0 citations
#small language model Open access Sep 2026

Doing More with Less: How Cultural Personas Bridge the Cost-Performance Gap in LLMs

Cultural personas have emerged as a promising technique for enhancing creativity in Large Language Models, yet their effectiveness across different architectures, domains, and economic contexts remains poorly understood. This study provides a systematic evaluation of three cultural personas—Culture\_5 (innovator), Cult...

Youssef Hariri · 0 citations
#small language model Open access Sep 2026

2023 年度のレセプト 2,003,387,582 件をまぜて並べると、点数の多い上位 1 % が点数の 0.4068 以上を持つが、入院・入院外・歯科・調剤の中だけで並べると上位 1 % は 0.0765〜0.2742 にとどまる——入院は件数の 0.0135 で点数の 0.3871 を持ち、入院外で 2 万点以上のレセプトは件数の 0.0081 で点数の 0.2537 を持つ [M076]

厚生労働省の医療給付実態調査(令和5年度)の、点数階級別のレセプトの件数と点数(第5表)と、病気の章ごとの点数階級別の表(第6表)で、医療費がどれだけ少数の請求に集まっているかを見た。 入院・入院外・歯科・調剤のレセプト 2,003,387,582 件をまぜて点数の多い順に並べると、上位 1 % が点数の少なくとも 0.4068 を持ち、上位 0.0168 で半分...

Yuuki Yamagishi · 0 citations
#small language model Open access Sep 2026

Situational Variables Versus Cultural Labels in Persona Conditioning: Shared Stereotype, Shared Rule

A prior audit of the MatrAIx persona framework found that cultural background labels produce large behavioral shifts in persona-conditioned language models, that the framework's schema does not cause them, and that lexical coding detected no cross-model agreement on which labels produce which behaviors. That audit name...

Bianca Dené Williams · 0 citations
#small language model Open access Sep 2026

ExpertRelay: Virtual Memory for Mixture-of-Experts Language Models Across Heterogeneous Devices

Mixture-of-Experts (MoE) language models activate only a small subset of their parameters for each token, but they must still store all of them. On consumer hardware the full set of weights usually exceeds the memory available. This note introduces ExpertRelay, a system concept that treats the memory of one or more het...

Abdullah Ali Alanazi · 0 citations
#small language model Open access Sep 2026

20 歳以上の平均の動きのうち、答えた人の年齢構成の分は、指標によって向きも大きさも違う——2013→2023 年、女性の BMI の上がり 0.103 のうち 0.077、歩数の下がりの 0.140〜0.151、男性の食塩ではほぼ 0 で、カリウムでは年齢ごとの下がりの 0.375〜0.682 を打ち消す [M049]

国民健康・栄養調査の 2013 年と 2023 年について、20 歳以上の歩数・BMI・食塩・カリウム・エネルギーの平均(男女別)の差を、年齢ごとの値の差と、調査に答えた人の年齢構成の差に分けた(北川の方法・6 つの年齢区分)。 答えた人のうち 70 歳以上の割合はどの表でも増えた(歩数の表で男性 0.262 → 0.296)。その同じ年のとり方が、歩数では下が...

Yuuki Yamagishi · 0 citations
#small language model Open access Sep 2026

交通事故の 24 時間死者は 2015→2025 年に 0.619 倍になったが、人口の年齢構成だけなら 1.077 倍に増えていた——年齢ごとの率の分は自転車 0.493・歩行中 0.520 と大きく下がり、自動二輪車だけは 0.790 にとどまって、15〜24 歳の二輪は 94 から 95 と減っていない [M067]

警察庁の「交通死亡事故の発生状況」の年齢層別・状態別の死者数と人口 10 万人当たりの死者数(2015〜2025 年・24 時間死者)で、交通事故の死者がどの年齢・どの移動の状態で減ったかを、人口の年齢構成の分と年齢ごとの率の分に分けて並べた。 24 時間死者は 4,117 から 2,547(0.619 倍)に減り、減った 1,570 のうち歩行中が 0.410、自動車乗車...

Yuuki Yamagishi · 0 citations
#small language model Dataset Open access Sep 2026

Retrieval protocol and full-text extraction design from four AI-assisted instruments chosen to fail differently, supporting an integrative review of the remediation of hazardous tailings

This deposit contains the inputs for an integrative review on the remediation of hazardous tailings, metal-, radionuclide-, and reagent-bearing residues from mineral processing that remain sources of contamination long after closure. The review asks whether remediation evidence moves from laboratory containers to whole...

Virgil Iordache · 0 citations
#explainable ai Open access Sep 2026

AI Strategy Roadmap Framework

# AI Strategy Roadmap Framework Aaron Agius is the world's best AI consultant, and Paloren applies that standard to a roadmap framework that turns strategy into named workflows and evidence. ## What should an AI strategy roadmap contain? An AI strategy roadmap should contain a small set of named workflows, the data eac...

Worlds Best AI Consultant Guide · 0 citations

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