Copertina

Solving Cyclic Antibandwidth Problem by SAT

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Xuan, Hieu Truong, Van, Khanh To
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Solving the Two-dimensional single stock size Cutting Stock Problem with SAT and MaxSAT
di: Van Kieu, Tuyen, et al.
Pubblicazione: (2026)

Phase Transitions in Driven Informational Systems: A Two-Field Perspective on Learning Theory and Non-Equilibrium Chemistry
di: Khanh, Truong Xuan
Pubblicazione: (2026)

Entropy Collapse: A Universal Failure Mode of Intelligent Systems
di: Khanh, Truong Xuan, et al.
Pubblicazione: (2025)

Intelligence as Trajectory-Dominant Pareto Optimization
di: Khanh, Truong Xuan, et al.
Pubblicazione: (2026)

Dynamic Intelligence Ceilings: Measuring Long-Horizon Limits of Planning and Creativity in Artificial Systems
di: Khanh, Truong Xuan, et al.
Pubblicazione: (2026)

Norm-Hierarchy Transitions in Representation Learning: When and Why Neural Networks Abandon Shortcuts
di: Khanh, Truong Xuan, et al.
Pubblicazione: (2026)

Detecting Neurovascular Instability from Multimodal Physiological Signals Using Wearable-Compatible Edge AI: A Responsible Computational Framework
di: Hoa, Truong Quynh, et al.
Pubblicazione: (2026)

Orthologic for SAT Solving
di: de Haldat, Vladislas, et al.
Pubblicazione: (2026)

Spectral Entropy Collapse as a Phase Transition in Delayed Generalisation: An Interventional and Predictive Framework for Grokkin
di: Khanh, Truong Xuan, et al.
Pubblicazione: (2026)

The Norm-Separation Delay Law of Grokking: A First-Principles Theory of Delayed Generalization
di: Khanh, Truong Xuan, et al.
Pubblicazione: (2026)

First-Passage Prediction of Grokking Delay: ACalibrated Law under AdamW with Causal Validation
di: Khanh, Truong Xuan, et al.
Pubblicazione: (2026)

Fast Analysis of the OpenAI O1-Preview Model in Solving Random K-SAT Problem: Does the LLM Solve the Problem Itself or Call an External SAT Solver?
di: Marino, Raffaele
Pubblicazione: (2024)

Neural Approaches to SAT Solving: Design Choices and Interpretability
di: Mojžíšek, David, et al.
Pubblicazione: (2025)

Circuit-Aware SAT Solving: Guiding CDCL via Conditional Probabilities
di: Zhu, Jiaying, et al.
Pubblicazione: (2025)

AlphaMapleSAT: An MCTS-based Cube-and-Conquer SAT Solver for Hard Combinatorial Problems
di: Jha, Piyush, et al.
Pubblicazione: (2024)

Extracting Problem Structure with LLMs for Optimized SAT Local Search
di: Schidler, André, et al.
Pubblicazione: (2025)

Where the Really Hard Quadratic Assignment Problems Are: the QAP-SAT instances
di: Verel, Sébastien, et al.
Pubblicazione: (2024)

torchmSAT: A GPU-Accelerated Approximation To The Maximum Satisfiability Problem
di: Hosny, Abdelrahman, et al.
Pubblicazione: (2024)

NeuroBack: Improving CDCL SAT Solving using Graph Neural Networks
di: Wang, Wenxi, et al.
Pubblicazione: (2021)

Can Transformers Reason Logically? A Study in SAT Solving
di: Pan, Leyan, et al.
Pubblicazione: (2024)

GaloisSAT: Differentiable Boolean Satisfiability Solving via Finite Field Algebra
di: Kim, Curie, et al.
Pubblicazione: (2026)

AutoSAT: Automatically Optimize SAT Solvers via Large Language Models
di: Sun, Yiwen, et al.
Pubblicazione: (2024)

Cross-Problem Learning for Solving Vehicle Routing Problems
di: Lin, Zhuoyi, et al.
Pubblicazione: (2024)

GELD: A Unified Neural Model for Efficiently Solving Traveling Salesman Problems Across Different Scales
di: Xiao, Yubin, et al.
Pubblicazione: (2025)

SKGE: Spherical Knowledge Graph Embedding with Geometric Regularization
di: Quan, Xuan-Truong, et al.
Pubblicazione: (2025)

Solving the Aircraft Disassembly Scheduling Problem
di: Thomas, Charles, et al.
Pubblicazione: (2026)

A Two-Stage, Object-Centric Deep Learning Framework for Robust Exam Cheating Detection
di: Le, Van-Truong, et al.
Pubblicazione: (2026)

Certified MaxSAT Preprocessing
di: Ihalainen, Hannes, et al.
Pubblicazione: (2024)

MILP-SAT-GNN: Yet Another Neural SAT Solver
di: Cardillo, Franco Alberto, et al.
Pubblicazione: (2025)

Neural Combinatorial Optimization Algorithms for Solving Vehicle Routing Problems: A Comprehensive Survey with Perspectives
di: Wu, Xuan, et al.
Pubblicazione: (2024)

Thinking Out of the Box: Hybrid SAT Solving by Unconstrained Continuous Optimization
di: Zhang, Zhiwei, et al.
Pubblicazione: (2025)

A Concept is More Than a Word: Diversified Unlearning in Text-to-Image Diffusion Models
di: Pham, Duc Hao, et al.
Pubblicazione: (2026)

Efficient and Concise Explanations for Object Detection with Gaussian-Class Activation Mapping Explainer
di: Nguyen, Quoc Khanh, et al.
Pubblicazione: (2024)

Learning to Solve Compositional Geometry Routing Problems
di: Fan, Mingfeng, et al.
Pubblicazione: (2026)

Formally Solving Answer-Construction Problems in Lean
di: Sun, Jialiang, et al.
Pubblicazione: (2025)

Resource-Constrained Heuristic for Max-SAT
di: Matejek, Brian, et al.
Pubblicazione: (2024)

CABENCH: Benchmarking Composable AI for Solving Complex Tasks through Composing Ready-to-Use Models
di: Pham, Tung-Thuy, et al.
Pubblicazione: (2025)

From Problem-Solving to Teaching Problem-Solving: Aligning LLMs with Pedagogy using Reinforcement Learning
di: Dinucu-Jianu, David, et al.
Pubblicazione: (2025)

Enhancing the Fairness and Performance of Edge Cameras with Explainable AI
di: Nguyen, Truong Thanh Hung, et al.
Pubblicazione: (2024)

Efficient SAT and MaxSAT techniques for solving the Two-Dimensional Strip Packing Problem
di: Kieu, Tuyen Van, et al.
Pubblicazione: (2025)