Cover Image

KNARsack: Teaching Neural Algorithmic Reasoners to Solve Pseudo-Polynomial Problems

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Požgaj, Stjepan, Georgiev, Dobrik, Šilić, Marin, Veličković, Petar
Format:	Preprint
Published:	2025
Subjects:	Artificial Intelligence Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Parallel Algorithms Align with Neural Execution
by: Engelmayer, Valerie, et al.
Published: (2023)

Recurrent Aggregators in Neural Algorithmic Reasoning
by: Xu, Kaijia, et al.
Published: (2024)

Neural Algorithmic Reasoning with Multiple Correct Solutions
by: Kujawa, Zeno, et al.
Published: (2024)

The Deep Equilibrium Algorithmic Reasoner
by: Georgiev, Dobrik, et al.
Published: (2024)

NAR-*ICP: Neural Execution of Classical ICP-based Pointcloud Registration Algorithms
by: Panagiotaki, Efimia, et al.
Published: (2024)

Neural Algorithmic Reasoning for Combinatorial Optimisation
by: Georgiev, Dobrik, et al.
Published: (2023)

Neural Bipartite Matching
by: Georgiev, Dobrik, et al.
Published: (2020)

Cayley Graph Propagation
by: Wilson, JJ, et al.
Published: (2024)

Large Language Models as Attribution Regularizers for Efficient Model Training
by: Vukadin, Davor, et al.
Published: (2025)

Deep Equilibrium Algorithmic Reasoning
by: Georgiev, Dobrik, et al.
Published: (2024)

Asynchronous Algorithmic Alignment with Cocycles
by: Dudzik, Andrew, et al.
Published: (2023)

Latent Space Representations of Neural Algorithmic Reasoners
by: Mirjanić, Vladimir V., et al.
Published: (2023)

Leveraging Classical Algorithms for Graph Neural Networks
by: Wu, Jason, et al.
Published: (2025)

Positional Attention: Expressivity and Learnability of Algorithmic Computation
by: de Luca, Artur Back, et al.
Published: (2024)

Softmax is not Enough (for Sharp Size Generalisation)
by: Veličković, Petar, et al.
Published: (2024)

Temporal Graph Rewiring with Expander Graphs
by: Petrović, Katarina, et al.
Published: (2024)

Mining Generalizable Activation Functions
by: Vitvitskyi, Alex, et al.
Published: (2026)

The CLRS-Text Algorithmic Reasoning Language Benchmark
by: Markeeva, Larisa, et al.
Published: (2024)

Perplexity Cannot Always Tell Right from Wrong
by: Veličković, Petar, et al.
Published: (2026)

Tackling GNARLy Problems: Graph Neural Algorithmic Reasoning Reimagined through Reinforcement Learning
by: Schutz, Alex, et al.
Published: (2025)

What makes a good feedforward computational graph?
by: Vitvitskyi, Alex, et al.
Published: (2025)

How do LLMs Compute Verbal Confidence
by: Kumaran, Dharshan, et al.
Published: (2026)

Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation
by: Vukadin, Davor, et al.
Published: (2024)

Open-Book Neural Algorithmic Reasoning
by: Li, Hefei, et al.
Published: (2024)

Solving Probabilistic Verification Problems of Neural Networks using Branch and Bound
by: Boetius, David, et al.
Published: (2024)

Decomposing Elements of Problem Solving: What "Math" Does RL Teach?
by: Qin, Tian, et al.
Published: (2025)

MINAR: Mechanistic Interpretability for Neural Algorithmic Reasoning
by: He, Jesse, et al.
Published: (2026)

PUZZLES: A Benchmark for Neural Algorithmic Reasoning
by: Estermann, Benjamin, et al.
Published: (2024)

RLAD: Training LLMs to Discover Abstractions for Solving Reasoning Problems
by: Qu, Yuxiao, et al.
Published: (2025)

When To Solve, When To Verify: Compute-Optimal Problem Solving and Generative Verification for LLM Reasoning
by: Singhi, Nishad, et al.
Published: (2025)

SPARQ: Synthetic Problem Generation for Reasoning via Quality-Diversity Algorithms
by: Havrilla, Alex, et al.
Published: (2025)

Beyond Either-Or Reasoning: Transduction and Induction as Cooperative Problem-Solving Paradigms
by: Zenkner, Janis, et al.
Published: (2025)

Richer Representations for Neural Algorithmic Reasoning via Auxiliary Reconstruction
by: Huang, Jiafu, et al.
Published: (2026)

Learning to Solve Resource-Constrained Project Scheduling Problems with Duration Uncertainty using Graph Neural Networks
by: Infantes, Guillaume, et al.
Published: (2025)

Matching Problems to Solutions: An Explainable Way of Solving Machine Learning Problems
by: Saleh, Lokman, et al.
Published: (2024)

Unsupervised Learning for Solving the Travelling Salesman Problem
by: Min, Yimeng, et al.
Published: (2023)

Rotary Position Encodings for Graphs
by: Reid, Isaac, et al.
Published: (2025)

Position: Rethinking Post-Hoc Search-Based Neural Approaches for Solving Large-Scale Traveling Salesman Problems
by: Xia, Yifan, et al.
Published: (2024)

Evidence of Learned Look-Ahead in a Chess-Playing Neural Network
by: Jenner, Erik, et al.
Published: (2024)

Geometric Analysis of Reasoning Trajectories: A Phase Space Approach to Understanding Valid and Invalid Multi-Hop Reasoning in LLMs
by: Marin, Javier
Published: (2024)