김동우 교수

Abstract The present paper attempts to provide an exact truthmaker semantical analysis of modalized propositions. According to the present proposal, an exact truthmaker for “Necessarily P ” is a state that bans every exact truthmaker for “Not P ”, and an exact truthmaker for “Possibly P ” is a state that allows an exact truthmaker for P . Based on this proposal, a formal semantics will be developed; and the soundness and completeness results for a well-known family of the systems of normal modal

Abstract I shall discuss Han’s analysis of the necessity of origin theses. His analysis comes in two parts. The negative part argues that well-known Kripkean arguments leave an inferential gap, thus falling short of establishing the necessity of origin theses. The positive part contends that the gap can only be bridged by Aristotelian metaphysics of essence and causation. I shall critically examine both the negative and positive parts of Han’s analysis.

Abstract I shall discuss some of the issues concerning a notorious doctrine of Frege that sentences are names of truth-values. I am interested in a problem raised by Kripke that the doctrine obscures the distinction between judgeable and unjudgeable contents. I shall present what I take to be Frege’s account of judgeable content: a proper expression of a judgeable content is susceptible to an analysis into a predicate and an argument-word, where a predicate is understood as a concept-word used t

In the addenda to his Naming and Necessity, Kripke provides an account of how necessary aposteriori statements are possible. In such a case, there is an apriori general principle telling us that it is necessary if true at all. Though straightforward in its broad compass, this account faces two obvious questions in its application: in each case of necessary aposteriori statements, what is the underlying principle and how is it established apriori? I treat these questions with respect to theoretic

ABSTRACT Kripke observes that the decimal numerals have the buck-stopping property: when a number is given in decimal notation, there is no further question of what number it is. What makes them special in this way? According to Kripke, it is because of structural revelation: each decimal numeral represents the structure of the corresponding number. Though insightful, I argue, this account has some counterintuitive consequences. Then I sketch an alternative account of the buck-stopping property

Plane geometry problem solving (PGPS) has recently gained significant attention as a benchmark to assess the multi-modal reasoning capabilities of large vision-language models.Despite the growing interest in PGPS, the research community still lacks a comprehensive overview that systematically synthesizes recent work in PGPS.To fill this gap, we present a survey of existing PGPS studies.We first categorize PGPS methods into an encoder-decoder framework and summarize the corresponding output forma

Plane geometry problem solving (PGPS) has recently gained significant attention as a benchmark to assess the multi-modal reasoning capabilities of large vision-language models. Despite the growing interest in PGPS, the research community still lacks a comprehensive overview that systematically synthesizes recent work in PGPS. To fill this gap, we present a survey of existing PGPS studies. We first categorize PGPS methods into an encoder-decoder framework and summarize the corresponding output fo

ABSTRACT To develop high‐energy‐dense lithium–sulfur batteries (LSBs), improving cycle performance by suppressing electrolyte depletion and stabilizing the anode–electrolyte interphase under lean‐electrolyte conditions is essential. Lithium nitrate (LiNO 3 ) is regarded as an effective additive that reduces electrolyte decomposition and stabilizes the interphases of the cathode and anode in LSBs, however, it also increases cell overvoltage, limiting rate performance. Herein, by exploring various

Oversmoothing has been recognized as a main obstacle to building deep Graph Neural Networks (GNNs), limiting the performance. This position paper argues that the influence of oversmoothing has been overstated and advocates for a further exploration of deep GNN architectures. Given the three core operations of GNNs, aggregation, linear transformation, and non-linear activation, we show that prior studies have mistakenly confused oversmoothing with the vanishing gradient, caused by transformation