Les mathématiques de la langue : l'approche formelle de Montague
원문 초록
We present a natural language modelization method which is strongely relying on mathematics. This method, called "Formal Semantics," has been initiated by the American linguist Richard M. Montague in the 1970's. It uses mathematical tools such as formal languages and grammars, first-order logic, type theory and $\lambda$-calculus. Our goal is to have the reader discover both Montagovian formal semantics and the mathematical tools that he used in his method. ----- Nous pr\'esentons une m\'ethode de mod\'elisation de la langue naturelle qui est fortement bas\'ee sur les math\'ematiques. Cette m\'ethode, appel\'ee {\guillemotleft}s\'emantique formelle{\guillemotright}, a \'et\'e initi\'ee par le linguiste am\'ericain Richard M. Montague dans les ann\'ees 1970. Elle utilise des outils math\'ematiques tels que les langages et grammaires formels, la logique du 1er ordre, la th\'eorie de types et le $\lambda$-calcul. Nous nous proposons de faire d\'ecouvrir au lecteur tant la s\'emantique formelle de Montague que les outils math\'ematiques dont il s'est servi.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Personalized Exercise Recommendation with Semantically-Grounded Knowledge Tracing
Reasoning or Memorization? Unreliable Results of Reinforcement Learning Due to Data Contamination
A Practical Two-Stage Recipe for Mathematical LLMs: Maximizing Accuracy with SFT and Efficiency with Reinforcement Learning
The Delta Learning Hypothesis: Preference Tuning on Weak Data can Yield Strong Gains
LLMThinkBench: Towards Basic Math Reasoning and Overthinking in Large Language Models
EvoAgentX: An Automated Framework for Evolving Agentic Workflows
토론
이 논문과 연결된 포럼 글이 아직 없습니다.