In large language models (LLMs), code and reasoning reinforce each other: code offers an abstract, modular, and logic-driven structure that supports reasoning, while reasoning translates high-level goals into smaller, executable steps that drive more...
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Today's competitive environment drives the enterprises to extend their focus and collaborate with their business partners to carry out the necessities. Tight coordination among business partners assists to share and integrate the service logic global...
Rapid Single Flux Quantum (RSFQ) circuits are the most evolved superconductor logic family. However, the need to clock each cell and the deep pipeline causes a complex clock network with a large skew. This results in lower throughput and high latency...
Large Language Models (LLMs) are pivotal AI agents in complex tasks but still face challenges in open decision-making problems within complex scenarios. To address this, we use the language logic game ``Who is Undercover?'' (WIU) as an experimental p...
While text-to-visual models now produce photo-realistic images and videos, they struggle with compositional text prompts involving attributes, relationships, and higher-order reasoning such as logic and comparison. In this work, we conduct an extensi...
Explicit state logic model checking tool -- 2002 winner of the ACM System Software Award. (⭐ 455)
Soldier crabs Mictyris guinotae exhibit pronounced swarming behaviour. The swarms of the crabs tolerant of perturbations. In computer models and laboratory experiments we demonstrate that swarms of soldier crabs can implement logical gates when place...
Correlated electron systems are among the centerpieces of modern condensed matter sciences, where many interesting physical phenomena, such as metal-insulator transition and high-Tc superconductivity appear. Recent efforts have been focused on electr...
The Alexa Skills Kit SDK for Java helps you get a skill up and running quickly, letting you focus on skill logic instead of boilerplate code. (⭐ 825)
Neuro-symbolic AI bridges the gap between purely symbolic and neural approaches to learning. This often requires maximizing the likelihood of a symbolic constraint w.r.t the neural network's output distribution. Such output distributions are typicall...
Spin waves in insulating magnets are ideal carriers for spin currents with low energy dissipation. An electric field can modify the dispersion of spin waves, by directly affecting, via spin-orbit coupling, the electrons that mediate the interaction b...
This work investigates the causal mechanism behind the effect of chatbot personification and persuasion strategies on users' perceptions and donation likelihood. In a 2 (personified vs. non-personified chatbot) x 2 (emotional vs. logical persuasion s...
Flock Logic was developed as an art and engineering project to explore how the feedback laws used to model flocking translate when applied by dancers. The artistic goal was to create choreographic tools that leverage multi-agent system dynamics with...
Aiming to offer a framework for blended learning to the teaching of proof theory, the present paper describes an interactive tutorial, called \textsc{TryLogic}, teaching how to solve logical conjectures either by proofs or refutations. The paper also...
A logical, reasonably standardized, but flexible project structure for doing and sharing data science work. (⭐ 9707)
sciences: the study of formal systems, such as those under the branches of logic and mathematics, which use an a priori, as opposed to empirical, methodology
A true lie is a lie that becomes true when announced. In a logic of announcements, where the announcing agent is not modelled, a true lie is a formula (that is false and) that becomes true when announced. We investigate true lies and other types of i...
As the name suggests, type-logical grammars are a grammar formalism based on logic and type theory. From the prespective of grammar design, type-logical grammars develop the syntactic and semantic aspects of linguistic phenomena hand-in-hand, letting...
In practice, navigation of mobile robots in confined environments is often done using a spatially discrete cost-map to represent obstacles. Path following is a typical use case for model predictive control (MPC), but formulating constraints for obsta...