readme

README.md

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-license: mit
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+## LCHAIM: A Hebrew Natural Language Inference Dataset
+
+### Overview
+
+LCHAIM is a dataset designed to evaluate Natural Language Inference (NLI) models in Hebrew. Unlike English, Hebrew is a Morphologically Rich Language (MRL), requiring more research to develop robust NLI models. LCHAIM provides a benchmark for models that need to handle long premises and complex reasoning in Hebrew.
+
+### Dataset Description
+
+LCHAIM was created by translating and validating the English ConTRoL dataset into Hebrew. It consists of 8,325 context-hypothesis pairs that require various types of reasoning, including:
+
+* Coreferential reasoning
+
+* Temporal reasoning
+
+* Logical reasoning
+
+* Analytical reasoning
+
+### Performance Benchmarks
+
+Experiments with LCHAIM highlight the challenges of contextual reasoning in Hebrew. Key results include:
+
+Fine-tuning the LongHero model on both Hebrew NLI datasets and LCHAIM yielded a mean accuracy of 52%, which is 35% (absolute) lower than human performance.
+
+Large Language Models (LLMs) in a few-shot setting achieved the following top mean accuracies:
+
+* Gemma-9B
+
+* Dicta-LM-2.0-7B
+
+* GPT-4o
+
+Top performance: 60.12% mean accuracy
+
+### Citation
+
+If you use LCHAIM in your research, please cite our work, which should be published in the next month
+
+### License
+
+
+LCHAIM is released under the mit license.
+
+### Contact
+
+For questions or feedback, please contact orielpe@post.bgu.ac.il
+