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Logic Synthesis with Generative Deep Neural Networks
Xihan Li, Xing Li, Lei Chen, Xing Zhang, Mingxuan Yuan, Jun Wang
https://arxiv.org/abs/2406.04699 http…

Logic Synthesis with Generative Deep Neural Networks
While deep learning has achieved significant success in various domains, its application to logic circuit design has been limited due to complex constraints and strict feasibility requirement. However, a recent generative deep neural model, "Circuit Transformer", has shown promise in this area by enabling equivalence-preserving circuit transformation on a small scale. In this paper, we introduce a logic synthesis rewriting operator based on the Circuit Transformer model, named "ctrw" (Circuit T…

Trump tells rally-goers not to die in searing Vegas heat: ‘I don’t care about you, I just want your vote’
Remark get laughs at rally – but also draws raised eyebrows on social media as critics argue Trump was being truthful
https://www.independent.co.…

Trump tells rally-goers not to die in searing Vegas heat: ‘I don’t care about you, I just want your vote’
Remark get laughs at rally – but also draws raised eyebrows on social media as critics argue Trump was being truthful

law_firm: Lazega law firm network
Multiplex network with 3 edge types representing relationships (coworkers, friendship, advice) between partners and associates of a corporate law firm. Data hosted by Manlio De Domenico.
This network has 71 nodes and 2571 edges.
Tags: Social, Offline, Multilayer, Unweighted
https://

if a lesbian likes another lesbian while hiking, will she pin her to a pine while pining?

This https://arxiv.org/abs/2403.19431 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Base-extension Semantics for S5 Modal Logic
We develop a proof-theoretic semantics -- in particular, a base-extension semantics -- for multi-agent S5 modal logic (and hence also for the usual unindexed S5). Following the inferentialist interpretation of logic, this gives us a semantics in which validity is based on proof rather than truth. In base-extension semantics, the validity of formulae is generated by provability in a `base' of atomic rules and an inductive definition of the validity of the connectives. Base-extension semantics fo…

Logic Synthesis with Generative Deep Neural Networks
Xihan Li, Xing Li, Lei Chen, Xing Zhang, Mingxuan Yuan, Jun Wang
https://arxiv.org/abs/2406.04699 http…

Logic Synthesis with Generative Deep Neural Networks
While deep learning has achieved significant success in various domains, its application to logic circuit design has been limited due to complex constraints and strict feasibility requirement. However, a recent generative deep neural model, "Circuit Transformer", has shown promise in this area by enabling equivalence-preserving circuit transformation on a small scale. In this paper, we introduce a logic synthesis rewriting operator based on the Circuit Transformer model, named "ctrw" (Circuit T…

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did anyone draw cargo as a doggirl yet (she likes to Fetch)

A Remark on the Expressivity of Asynchronous TeamLTL and HyperLTL
Juha Kontinen, Max Sandstr\"om, Jonni Virtema
https://arxiv.org/abs/2406.04833 https…

A Remark on the Expressivity of Asynchronous TeamLTL and HyperLTL
Linear temporal logic (LTL) is used in system verification to write formal specifications for reactive systems. However, some relevant properties, e.g. non-inference in information flow security, cannot be expressed in LTL. A class of such properties that has recently received ample attention is known as hyperproperties. There are two major streams in the research regarding capturing hyperproperties, namely hyperlogics, which extend LTL with trace quantifiers (HyperLTL), and logics that employ …

A Remark on the Expressivity of Asynchronous TeamLTL and HyperLTL
Juha Kontinen, Max Sandstr\"om, Jonni Virtema
https://arxiv.org/abs/2406.04833 https…

A Remark on the Expressivity of Asynchronous TeamLTL and HyperLTL
Linear temporal logic (LTL) is used in system verification to write formal specifications for reactive systems. However, some relevant properties, e.g. non-inference in information flow security, cannot be expressed in LTL. A class of such properties that has recently received ample attention is known as hyperproperties. There are two major streams in the research regarding capturing hyperproperties, namely hyperlogics, which extend LTL with trace quantifiers (HyperLTL), and logics that employ …