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1. Founded semantics and constraint semantics of logic rules

   https://doi.org/10.1093/logcom/exaa056  

   Liu, Yanhong A; Stoller, Scott D (October 2020, Journal of Logic and Computation)

   null (Ed.)

   Abstract Logic rules and inference are fundamental in computer science and have been studied extensively. However, prior semantics of logic languages can have subtle implications and can disagree significantly, on even very simple programs, including in attempting to solve the well-known Russell’s paradox. These semantics are often non-intuitive and hard-to-understand when unrestricted negation is used in recursion. This paper describes a simple new semantics for logic rules, founded semantics, and its straightforward extension to another simple new semantics, constraint semantics, that unify the core of different prior semantics. The new semantics support unrestricted negation, as well as unrestricted existential and universal quantifications. They are uniquely expressive and intuitive by allowing assumptions about the predicates, rules and reasoning to be specified explicitly, as simple and precise binary choices. They are completely declarative and relate cleanly to prior semantics. In addition, founded semantics can be computed in linear time in the size of the ground program. 

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2. Interpreting Degree Semantics

   https://doi.org/10.3389/fpsyg.2019.02972  

   Wellwood, Alexis (January 2020, Frontiers in Psychology)
3. Semantics-guided synthesis

   https://doi.org/10.1145/3434311  

   Kim, Jinwoo; Hu, Qinheping; D'Antoni, Loris; Reps, Thomas (January 2021, Proceedings of the ACM on Programming Languages)

   This paper develops a new framework for program synthesis, called semantics-guided synthesis (SemGuS), that allows a user to provide both the syntax and the semantics for the constructs in the language. SemGuS accepts a recursively defined big-step semantics, which allows it, for example, to be used to specify and solve synthesis problems over an imperative programming language that may contain loops with unbounded behavior. The customizable nature of SemGuS also allows synthesis problems to be defined over a non-standard semantics, such as an abstract semantics. In addition to the SemGuS framework, we develop an algorithm for solving SemGuS problems that is capable of both synthesizing programs and proving unrealizability, by encoding a SemGuS problem as a proof search over Constrained Horn Clauses: in particular, our approach is the first that we are aware of that can prove unrealizabilty for synthesis problems that involve imperative programs with unbounded loops, over an infinite syntactic search space. We implemented the technique in a tool called MESSY, and applied it to SyGuS problems (i.e., over expressions), synthesis problems over an imperative programming language, and synthesis problems over regular expressions. 

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4. The semantics of questions

   https://doi.org/10.1002/wcs.1513  

   Moyer, Morgan C.; Syrett, Kristen (October 2019, Wiley Interdisciplinary Reviews: Cognitive Science)
5. Color Semantics in Human Cognition

   https://doi.org/10.1177/09637214231208189  

   Schloss, Karen B (February 2024, Current Directions in Psychological Science)

   People have associations between colors and concepts that influence the way they interpret color meaning in information visualizations (e.g., charts, maps, diagrams). These associations are not limited to concrete objects (e.g., fruits, vegetables); even abstract concepts, like sleeping and driving, have systematic color-concept associations. However, color-concept associations and color meaning (color semantics) are not the same thing, and sometimes they conflict. This article describes an approach to understanding color semantics called the color inference framework. The framework shows how color semantics is highly flexible and context dependent, which makes color an effective medium for communication. 

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