Skip to content

Rankings Industries Companies Research Blog

Sign in List your company

ResearchFormerly WizWand

Papers Benchmarks Datasets Tasks

Research
Benchmarks
Knapsack on Knapsack N=15 (test)

Knapsack on Knapsack N=15 (test)

58.5Vector AccuracyILP-Loss

Updated 8mo ago

Evaluation results

Method	Links
ILP-Loss2022.10		58.5
CombOptNet2022.10		48.2

State-of-the-art paper

ILP-Loss

A Solver-Free Framework for Scalable Learning in Neural ILP Architectures

Dataset

Knapsack

Follow for updates

Join SOTA2 Contact

Related benchmarks

Sudoku Solving on Symbolic Sudoku Sudoku Solving on Visual Sudoku Constraint Learning on Random constraints Binary synthetic (test)Constraint Learning on Random constraints Dense synthetic (test)Random Constraints on Random Constraints Binary

Building an AI company?

Claim your profile, keep your facts current and see how buyers find you. Rankings are never paid for.

How rankings work List your company

Independent, evidence-based rankings of AI solutions for business buyers.

Explore

Rankings
Industries
Categories
Companies
Top AI companies

Read

Blog
Research
llms.txt

For AI companies

List your company
Claim a profile
Ranking badges

SOTA2

Why SOTA2
How we rank
Contact

© 2026 SOTA2Built in Bellevue, USA