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関連する概念動画

Language01:16

Language

921
Language is a unique communication system that uses words and systematic rules to organize and transmit information. Unlike other forms of communication, which may involve postures, movements, odors, or vocalizations, language relies on symbols and grammar. This makes human communication distinct from that of other species, who also communicate but do not use language in the same way humans do.
Corballis and Suddendorf (2007) and Tomasello and Rakoczy (2003) highlight the role of language in...
921
pH Scale02:41

pH Scale

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Hydronium and hydroxide ions are present both in pure water and in all aqueous solutions, and their concentrations are inversely proportional as determined by the ion product of water (Kw). The concentrations of these ions in a solution are often critical determinants of the solution’s properties and the chemical behaviors of its other solutes. Two different solutions can differ in their hydronium or hydroxide ion concentrations by a million, billion, or even trillion times. A common means of...
80.4K
Components of Language01:24

Components of Language

830
Language, whether spoken, signed, or written, consists of specific components: lexicon and grammar. The lexicon is the vocabulary of a language, comprising its words. Grammar is the set of rules used to convey meaning through the lexicon. For example, English grammar adds “-ed” to most verbs to indicate past tense. Words are formed by combining phonemes, which are the basic sound units of a language. Different languages have different sets of phonemes (e.g., “ah” vs.
830
Language Development01:22

Language Development

936
Children master language quickly and with relative ease, supported by both biological predisposition and reinforcement. B. F. Skinner (1957) proposed that language is learned through reinforcement, while Noam Chomsky (1965) argued that language acquisition mechanisms are biologically determined.
The critical period for language acquisition suggests that the ability to acquire language is at its peak early in life. As people age, this proficiency decreases. Language development begins very...
936
Language and Cognition01:27

Language and Cognition

812
Language serves as a bridge between ideas and communication, influencing how individuals perceive and interact with the world. Psychologists have long debated whether language shapes thought or vice versa. This discussion gained grip with Edward Sapir and Benjamin Lee Whorf in the 1940s, who proposed that language determines thought, a concept known as linguistic determinism. They suggested that the vocabulary and structure of a language influence how its speakers think and perceive reality.
812
Self-Evaluation Maintenance Model01:29

Self-Evaluation Maintenance Model

337
The Self-Evaluation Maintenance (SEM) model offers a psychological framework to understand how individuals’ self-esteem is influenced by the achievements of others, particularly those with whom they share close personal bonds. The SEM model operates when personal rather than social identity guides individuals. Central to this model is the notion that individuals have an inherent desire to preserve a favorable self-image, which is continuously shaped by interpersonal comparisons and...
337

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伝統中国医学試験問題のための大規模および軽量大規模言語モデルの評価：比較研究

Yizhen Li1, Shaohan Huang2, Jiaxing Qi2

  • 1The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, China.

Journal of evidence-based medicine
|February 11, 2026
PubMed
まとめ

大規模言語モデル（LLM）は伝統中国医学（TCM）において有望ですが、多肢選択問題には苦労しています。Qwen3-1.7Bのような最適化された軽量LLMは、リソースが限られたヘルスケア設定において実行可能な代替手段を提供します。

キーワード:
ベンチマーク評価大規模言語モデル軽量大規模言語モデルプロンプトエンジニアリング伝統中国医学

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科学分野:

  • 人工知能
  • 自然言語処理
  • 伝統中国医学

背景:

  • 伝統中国医学（TCM）は、その知識集約的な性質により、大規模言語モデル（LLM）にとって特有の課題を提示します。
  • TCM固有のベンチマークは存在するものの、この領域における軽量LLMのパフォーマンスは十分に調査されていません。
  • この研究では、展開のトレードオフを考慮して、TCMアプリケーションのための大規模および軽量LLMを体系的に評価および比較します。

主な方法:

  • 教科書から801件のTCM関連の質問のデータセットが開発されました。
  • 11のLLMが、英語と中国語の両方でゼロショットおよび少数ショットプロンプティングを使用して評価されました。
  • パフォーマンスは主に精度によって測定され、さまざまな質問タイプと推論カテゴリに焦点を当てました。

結論:

  • 大規模LLMはTCMにおいて強力な知識想起能力を示しますが、多肢選択タスクにおける限界と高い計算コストは、臨床応用の妨げとなる可能性があります。
  • Qwen3-1.7Bに代表される最適化された軽量LLMは、モデルの最適化とドメイン固有のトレーニングが、単にモデルサイズを増やすよりも有利であることを示唆しています。
  • この調査結果は、リソースが制約されたヘルスケア環境での最適化されたLLMの展開に関する洞察を提供しますが、実際の臨床意思決定におけるさらなる評価が保証されます。