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---
license: apache-2.0
base_model:
- meta-llama/Llama-3.1-8B-Instruct
tags:
- reasoning
- agent
- program
- code
---
**CodeARC: Benchmarking Reasoning Capabilities of LLM Agents for Inductive Program Synthesis**
Paper: https://arxiv.org/pdf/2503.23145
Code: https://github.com/Anjiang-Wei/CodeARC
Website: https://anjiang-wei.github.io/CodeARC-Website/
Dataset: https://huggingface.co/datasets/anjiangwei/CodeARC-Problems
10 Input-Output examples for each problem: https://huggingface.co/datasets/anjiangwei/CodeARC-Invocations
Fine-tuned models:
https://huggingface.co/LLM4Code/CodeARC_annotated_llama3.1
https://huggingface.co/LLM4Code/CodeARC_anonymous_llama3.1
```
@article{wei2025codearc,
title={CodeARC: Benchmarking Reasoning Capabilities of LLM Agents for Inductive Program Synthesis},
author={Wei, Anjiang and Suresh, Tarun and Cao, Jiannan and Kannan, Naveen and Wu, Yuheng and Yan, Kai and Teixeira, Thiago SFX and Wang, Ke and Aiken, Alex},
journal={arXiv preprint arXiv:2503.23145},
year={2025}
}
``` |