paper-with-me

graph partitioning

1개 벤치마크 · 논문 230편 · 이 태스크의 논문 보기 →

Benchmarks

custom

결과 1개

Most implemented

Papers

Diversity-aware View Partitioning for Scalable VGGT

2026-07-02 · Jinsoo Park, Donggyu Choi, Ahyun Seo, Minsu cho 외 arxiv

Geometry transformers such as VGGT achieve strong performance by jointly reasoning over multiple views with global attention. However, scaling them to large view collections remains challenging due to the quadratic cost …

Camera Pose Estimationgraph partitioning3D Reconstruction

When Parallelism Pays Off: Cohesion-Aware Task Partitioning for Multi-Agent Coding

2026-05-31 · Xu Yang, Lunyiu Nie, Ethan Chandra, Stanislav Gannutin 외 arxiv

Multi-agent Large Language Model (LLM) systems offer a way to decompose complex tasks, such as coding, through parallelization and context isolation. However, adding agents in practice introduces inter-agent communicatio…

Community Detectiongraph partitioning

Neural Acceleration for Graph Partitioning

2026-05-18 · Joshua Dennis Booth, Vishvam Patel arxiv

Graph Partitioning is a critical problem in numerous scientific and engineering domains including social network analysis, VLSI design, and many more. Spectral methods are known to produce quality partitions while minimi…

graph partitioning

Neural QAOA$^{2}$: Differentiable Joint Graph Partitioning and Parameter Initialization for Quantum Combinatorial Optimization

2026-05-13 · Zubin Zheng, Jiahao Wu, Shengcai Liu arxiv

The quantum approximate optimization algorithm (QAOA) holds promise for combinatorial optimization but is constrained by limited qubits. While divide-and-conquer frameworks like QAOA$^{2}$ address scalability by partitio…

Zero-shot Generalizationgraph partitioning

Structural Interpretations of Protein Language Model Representations via Differentiable Graph Partitioning

2026-05-09 · Siddhant Dutta, Edward Tan Beng Wai, Soumick Sarker, Pasan Gunawardane 외 arxiv

Protein language models such as ESM-2 learn rich residue representations that achieve strong performance on protein function prediction, but their features remain difficult to interpret as structural $\&$ evolutionary si…

Protein Function PredictionProtein Language Modelgraph partitioning

EmbedPart: Embedding-Driven Graph Partitioning for Scalable Graph Neural Network Training

2026-04-01 · Nikolai Merkel, Ruben Mayer, Volker Markl, Hans-Arno Jacobsen arxiv

Graph Neural Networks (GNNs) are widely used for learning on graph-structured data, but scaling GNN training to massive graphs remains challenging. To enable scalable distributed training, graphs are divided into smaller…

Graph Neural Networkgraph partitioning

전체 230편 보기 →