BAMO at SemEval-2024 Task 9: BRAINTEASER: A Novel Task Defying Common Sense

Baktash Ansari, Mohammadmostafa Rostamkhani, Sauleh Eetemadi
6/7/2024
cs.CL

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Abstract

This paper outlines our approach to SemEval 2024 Task 9, BRAINTEASER: A Novel Task Defying Common Sense. The task aims to evaluate the ability of language models to think creatively. The dataset comprises multi-choice questions that challenge models to think "outside of the box". We fine-tune 2 models, BERT and RoBERTa Large. Next, we employ a Chain of Thought (CoT) zero-shot prompting approach with 6 large language models, such as GPT-3.5, Mixtral, and Llama2. Finally, we utilize ReConcile, a technique that employs a "round table conference" approach with multiple agents for zero-shot learning, to generate consensus answers among 3 selected language models. Our best method achieves an overall accuracy of 85 percent on the sentence puzzles subtask.

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Cite this paper

@article{ansari2024bamo,
  title  = {BAMO at SemEval-2024 Task 9: BRAINTEASER: A Novel Task Defying Common Sense},
  author = {Baktash Ansari and Mohammadmostafa Rostamkhani and Sauleh Eetemadi},
  year   = {2024},
  eprint = {2406.04947},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2406.04947v1}
}

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