satisfiability modulo theories
PulseAugur coverage of satisfiability modulo theories — every cluster mentioning satisfiability modulo theories across labs, papers, and developer communities, ranked by signal.
3 day(s) with sentiment data
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New benchmark MINIF2F-DAFNY tests LLMs for mathematical theorem proving
Researchers have developed MINIF2F-DAFNY, a new benchmark for evaluating Large Language Models (LLMs) in mathematical theorem proving. This system translates the miniF2F benchmark to Dafny, an auto-active verifier, enab…
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New concolic testing method enhances Transformer robustness analysis
Researchers have developed a new concolic testing method for Transformer classifiers that uses SHAP estimates to prioritize path predicates based on their influence on the model's predictions. This approach, implemented…
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New tools enable formal verification of industrial PLC ladder diagram programs
Researchers have developed ESBMC-PLC and Graph-ESBMC-PLC, new tools for formally verifying industrial control programs written in the IEC 61131-3 Ladder Diagram (LD) format. These tools translate graphical LD programs i…
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New system uses AI and formal methods for better clinical trial matching
Researchers have developed SatIR, a novel retrieval system designed to improve the matching of patients to clinical trials. This system goes beyond simple semantic similarity by treating trial eligibility criteria as fo…
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LLM-Assisted System Enhances Industrial Planning with Natural Language Interaction
A new paper introduces a hybrid system that combines a Satisfiability Modulo Theories (SMT) planner with a Large Language Model (LLM) for industrial automation planning. This system aims to improve the interpretability …
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New k-NBCs enhance safety for unknown nonlinear systems
Researchers have developed k-inductive neural barrier certificates (k-NBCs) to enhance safety guarantees for nonlinear systems with unknown dynamics. This method relaxes traditional safety constraints by allowing tempor…
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New SMT-based algorithm learns weighted automata efficiently
Researchers have developed a new SMT-based active learning algorithm for nondeterministic weighted automata (WFAs). This method offers a practical and robust alternative to existing techniques, producing minimal WFAs an…