Graph Theory and Algorithms

Discover maximal balanced quasi-clique enumeration for signed graphs. A novel NP-hard algorithm identifies cohesive subgraphs with positive and negative edges using branch-and-bound optimization.

Framework for testing conditional and unconditional independence between binary graphs using community correlations and graph encoder embeddings.

Thoth hardware prefetcher improves performance on sparse data structures by tracking producer-consumer load pairs and using annotation-directed sampling to capture complex memory access patterns.

Comparative performance analysis of GraphQL, gRPC, and Thrift for web interfaces shows gRPC fastest for large reads; GraphQL and Thrift better for small data volumes.

DTMiner optimizes temporal motif mining by coordinating multiple matching tasks around shared data access patterns, achieving 1.14×-11.98× performance improvements.

Survey of graph-based techniques in retrieval-augmented generation systems, examining their roles in database construction, algorithms, and reasoning with structured knowledge.

Framework for temporal abstractions that simplify coordination of asynchronous GPU tensor computations, reducing complexity and hardware-dependent errors in specialized concurrent execution.

Study proposes learnable communication graphs for multi-agent systems, enabling dynamic information sharing that adapts to task demands and reduces computational resource consumption.

SLAWS framework enhances sparse matrix multiplication by analyzing data locality patterns and orchestrating workloads adaptively, overcoming limitations of fixed-architecture accelerators.

Parallel algorithms for conflict graph management in mixed-integer programming enable larger cutting plane pools and substantially reduce solver times, especially for difficult problem instances.

GeoGraphNetworks: 110 validated spatial networks spanning US and UK transportation and hydrological systems in analysis-ready JSON and XLSX formats with complete topological and geographic data.

Systematic mapping of human-centric evaluation approaches for semantic resources like ontologies and knowledge graphs, synthesizing 15 years of research into a theoretical framework.

CORE applies Information Bottleneck principles to augment graph data for link prediction, simultaneously recovering missing edges and reducing noise to enhance model robustness.

Framework for identifying roles in multiplex networks by modeling trade-offs across layers while accounting for independence, dependence, and interdependence mechanisms.

Systematic study of query optimization bugs in graph databases reveals root causes, manifestation patterns, and fixes to improve GDBMS reliability and system design.

Temporal-clique subgraph pattern matching via integrated topological and temporal selectivity optimization with specialized join operators and cardinality estimation.

BenchPCNP: A labeled printed circuit netlist graph dataset for partitioning benchmarking, constructed from 50 production-verified circuits with 54 distinct module labels following IPC-2612 standards.

Prompt-driven framework combining LLMs with knowledge graphs for reliable knowledge-based question answering through structured subgraph retrieval and stepwise reasoning validation.

Graph matching framework for cross-modality intravascular ultrasound and optical coherence tomography sequence registration with simultaneous temporal and rotational alignment.

Distributed inference system using interleaved parallelism to dynamically balance latency-throughput trade-offs via task-aware batch management and strategic kernel scheduling across multiple GPUs.