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関連する概念動画

Language01:16

Language

894
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...
894
Components of Language01:24

Components of Language

776
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.
776
Language Development01:22

Language Development

872
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...
872
Language and Cognition01:27

Language and Cognition

730
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.
730
Frustration and Conflict: Approach-Approach, Approach-Avoidance01:20

Frustration and Conflict: Approach-Approach, Approach-Avoidance

497
Frustration occurs when people are obstructed or prevented from achieving a desired goal or fulfilling a perceived need. For example, when someone's input is ignored in a discussion, it can lead to feelings of frustration. Conflict, however, arises from opposing interests, goals, or actions. Conflicts can take various forms based on the nature of these opposing desires or goals.
One common type of conflict is the Approach–Approach Conflict. In this case, a person faces two desirable...
497
Higher Mental Functions of the Brain: Language01:10

Higher Mental Functions of the Brain: Language

3.5K
Language is a system of communication that allows the expression of thoughts, ideas, and feelings. The brain processes language in both hemispheres.
Language formation and comprehension take place in the dominant hemisphere. The dominant hemisphere is responsible for understanding the meaning of spoken, written, or sign language, as well as the ability to communicate. For most people, the left hemisphere is the dominant one. The right hemisphere, then, gives tone and emotional context to the...
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関連する実験動画

Updated: Jan 23, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
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HealthContradict:言語モデルにおける生物医学的知識の競合の評価

Boya Zhang1, Alban Bornet2, Rui Yang3

  • 1Faculty of Medicine, University of Geneva, Geneva, Switzerland. boya.zhang@unige.ch.

NPJ digital medicine
|January 21, 2026
PubMed
まとめ

言語モデルは文脈を利用して健康に関する質問に答えることができるが、競合する情報は応答に影響を与える。生物医学的にファインチューニングされたモデルは、正しい文脈を利用し、不正確な情報に抵抗することに優れている。

キーワード:
言語モデル生物医学知識の競合健康情報文脈ファインチューニング誤情報

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科学分野:

  • 人工知能
  • 生物医学情報学
  • 自然言語処理

背景:

  • 言語モデル(LM)は、健康情報検索にますます使用されています。
  • 複雑で矛盾した生物医学情報に対するLMのパフォーマンスを評価することは重要です。

研究 の 目的:

  • 長くて矛盾した生物医学的文脈 over LMの推論を評価する。
  • さまざまな文脈設定が健康に関する質問に対するLMの応答に与える影響を評価する。

主な方法:

  • 健康に関する質問、事実に基づいた回答、矛盾した文書を含む920のインスタンスを持つ専門家によって検証されたHealthContradictデータセットを利用しました。
  • 正しい、不正確な、矛盾したコンテキストを含むさまざまなプロンプト設定をテストしました。
  • LMの出力に対するコンテキストの影響を測定しました。

主要な成果:

  • HealthContradictデータセットは、既存のベンチマークよりも効果的にLMの文脈推論能力を区別します。
  • ファインチューニングされた生物医学LMは、正しい文脈を活用する能力を示しました。
  • モデルは、不正確または矛盾する文脈情報に対して回復力を示しました。

結論:

  • 生物医学LMの強みは、事前学習知識と文脈推論の両方に由来します。
  • LMは、誤報の影響を軽減しながら、正確な健康情報を効果的に活用できます。