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--- |
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license: mit |
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task_categories: |
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- text-classification |
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language: |
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- he |
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pretty_name: LCHAIM |
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size_categories: |
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- 1K<n<10K |
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--- |
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## LCHAIM: Investigating Long Context Reasoning in Hebrew |
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### Overview |
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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. |
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### Dataset Description |
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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: |
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* Coreferential reasoning |
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* Temporal reasoning |
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* Logical reasoning |
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* Analytical reasoning |
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### Performance Benchmarks |
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Experiments with LCHAIM highlight the challenges of contextual reasoning in Hebrew. Key results include: |
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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. |
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Large Language Models (LLMs) in a few-shot setting achieved the following top mean accuracies: |
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* Gemma-9B |
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* Dicta-LM-2.0-7B |
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* GPT-4o |
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Top performance: 60.12% mean accuracy |
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### Citation |
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If you use LCHAIM in your research, please cite our work: |
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``` |
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@inproceedings{malul2025lchaim, |
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title={Lchaim-investigating long context reasoning in hebrew}, |
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author={Malul, Ehud and Perets, Oriel and Mor, Ziv and Kassel, Yigal and Sulem, Elior}, |
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booktitle={Findings of the Association for Computational Linguistics: ACL 2025}, |
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pages={7928--7939}, |
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year={2025} |
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} |
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``` |
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### License |
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LCHAIM is released under the mit license. |
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### Contact |
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For questions or feedback, please contact orielpe@post.bgu.ac.il |
