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README.md

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-license: mit
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+---
+license: mit
+tags:
+- arxiv:2602.01285
+- conformal-inference
+- llm
+- maci
+---
+
+# MACI: Multi-LLM Adaptive Conformal Inference
+
+This is the official repository for the paper **"Multi-LLM Adaptive Conformal Inference for Reliable LLM Responses"**.
+
+📄 **Paper**: [arXiv:2602.01285](https://arxiv.org/abs/2602.01285)  
+💻 **Code**: [GitHub Repository](https://github.com/MLAI-Yonsei/MACI)
+
+## Abstract
+Ensuring factuality is essential for the safe use of Large Language Models (LLMs) in high-stakes domains such as medicine and law. Conformal inference provides distribution-free guarantees, but existing approaches are either overly conservative, discarding many true-claims, or rely on adaptive error rates and simple linear models that fail to capture complex group structures. To address these challenges, we reformulate conformal inference in a multiplicative filtering setting, modeling factuality as a product of claim-level scores. Our method, Multi-LLM Adaptive Conformal Inference (MACI), leverages ensembles to produce more accurate factuality-scores, which in our experiments led to higher retention, while validity is preserved through group-conditional calibration. Experiments show that MACI consistently achieves user-specified coverage with substantially higher retention and lower time cost than baselines.
+## Usage
+Please refer to our [GitHub Repository](https://github.com/MLAI-Yonsei/MACI) for installation and usage instructions.