Cover Image

Addressing the Abstraction and Reasoning Corpus via Procedural Example Generation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Hodel, Michael
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

ARC-GEN: A Mimetic Procedural Benchmark Generator for the Abstraction and Reasoning Corpus
by: Moffitt, Michael D.
Published: (2025)

Vector Symbolic Algebras for the Abstraction and Reasoning Corpus
by: Joffe, Isaac, et al.
Published: (2025)

ARCLE: The Abstraction and Reasoning Corpus Learning Environment for Reinforcement Learning
by: Lee, Hosung, et al.
Published: (2024)

Program Synthesis using Inductive Logic Programming for the Abstraction and Reasoning Corpus
by: Rocha, Filipe Marinho, et al.
Published: (2024)

Procedural Content Generation via Generative Artificial Intelligence
by: Mao, Xinyu, et al.
Published: (2024)

Generalized Planning for the Abstraction and Reasoning Corpus
by: Lei, Chao, et al.
Published: (2024)

Synthesizing 3D Abstractions by Inverting Procedural Buildings with Transformers
by: Dax, Maximilian, et al.
Published: (2025)

JaxARC: A High-Performance JAX-based Environment for Abstraction and Reasoning Research
by: Aadam, et al.
Published: (2026)

Take a Step Back: Evoking Reasoning via Abstraction in Large Language Models
by: Zheng, Huaixiu Steven, et al.
Published: (2023)

Neural Causal Abstractions
by: Xia, Kevin, et al.
Published: (2024)

Epistemic diversity across language models mitigates knowledge collapse
by: Hodel, Damian, et al.
Published: (2025)

Consciousness-Inspired Spatio-Temporal Abstractions for Better Generalization in Reinforcement Learning
by: Zhao, Mingde, et al.
Published: (2023)

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

Learning to Reason as Action Abstractions with Scalable Mid-Training RL
by: Zhang, Shenao, et al.
Published: (2025)

Parallel LLM Reasoning for Bias-Resilient, Robust Conceptual Abstraction
by: Adeseye, Aisvarya, et al.
Published: (2026)

Efficient Discovery of Approximate Causal Abstractions via Neural Mechanism Sparsification
by: Asiaee, Amir
Published: (2026)

PLOT: Progressive Localization via Optimal Transport in Neural Causal Abstraction
by: Chang, Jonathn, et al.
Published: (2026)

Contrastive Abstraction for Reinforcement Learning
by: Patil, Vihang, et al.
Published: (2024)

Distributionally Robust Causal Abstractions
by: Felekis, Yorgos, et al.
Published: (2025)

Inference of Abstraction for a Unified Account of Reasoning and Learning
by: Kido, Hiroyuki
Published: (2024)

Procedural Generation of Algorithm Discovery Tasks in Machine Learning
by: Goldie, Alexander D., et al.
Published: (2026)

Enhancing Reasoning Capabilities of LLMs via Principled Synthetic Logic Corpus
by: Morishita, Terufumi, et al.
Published: (2024)

Multiple Abstraction Level Retrieve Augment Generation
by: Zheng, Zheng, et al.
Published: (2025)

Interval Abstractions for Robust Counterfactual Explanations
by: Jiang, Junqi, et al.
Published: (2024)

In-Context Planning with Latent Temporal Abstractions
by: Luo, Baiting, et al.
Published: (2026)

Spectral Alignment in Forward-Backward Representations via Temporal Abstraction
by: Azad, Seyed Mahdi B., et al.
Published: (2026)

Efficient Monte Carlo Tree Search via On-the-Fly State-Conditioned Action Abstraction
by: Kwak, Yunhyeok, et al.
Published: (2024)

Verification-Guided Falsification for Safe RL via Explainable Abstraction and Risk-Aware Exploration
by: Le, Tuan, et al.
Published: (2025)

Abstraction for Offline Goal-Conditioned Reinforcement Learning
by: Wibault, Clarisse, et al.
Published: (2026)

Offline Policy Learning via Skill-step Abstraction for Long-horizon Goal-Conditioned Tasks
by: Kim, Donghoon, et al.
Published: (2024)

Semantic Level of Detail for Knowledge Graphs: Discovering Abstraction Boundaries via Spectral Heat Diffusion
by: Izgorodin, Edward
Published: (2026)

Towards Interpretable Adversarial Examples via Sparse Adversarial Attack
by: Lin, Fudong, et al.
Published: (2025)

The Procedural Content Generation Benchmark: An Open-source Testbed for Generative Challenges in Games
by: Khalifa, Ahmed, et al.
Published: (2025)

Context-Sensitive Abstractions for Reinforcement Learning with Parameterized Actions
by: Nayyar, Rashmeet Kaur, et al.
Published: (2025)

Causal Abstraction Learning based on the Semantic Embedding Principle
by: D'Acunto, Gabriele, et al.
Published: (2025)

Policy Gradient Methods in the Presence of Symmetries and State Abstractions
by: Panangaden, Prakash, et al.
Published: (2023)

Realizable Abstractions: Near-Optimal Hierarchical Reinforcement Learning
by: Cipollone, Roberto, et al.
Published: (2025)

A Modular Dataset to Demonstrate LLM Abstraction Capability
by: Atanas, Adam, et al.
Published: (2025)

Learning Markov State Abstractions for Deep Reinforcement Learning
by: Allen, Cameron, et al.
Published: (2021)

Generating Realistic Adversarial Examples for Business Processes using Variational Autoencoders
by: Stevens, Alexander, et al.
Published: (2024)