Abdelhak at SemEval-2024 Task 9 : Decoding Brainteasers, The Efficacy of Dedicated Models Versus ChatGPT
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Abstract (arXiv)
This study introduces a dedicated model aimed at solving the BRAINTEASER task 9 , a novel challenge designed to assess models lateral thinking capabilities through sentence and word puzzles. Our model demonstrates remarkable efficacy, securing Rank 1 in sentence puzzle solving during the test phase with an overall score of 0.98. Additionally, we explore the comparative performance of ChatGPT, specifically analyzing how variations in temperature settings affect its ability to engage in lateral thinking and problem-solving. Our findings indicate a notable performance disparity between the dedicated model and ChatGPT, underscoring the potential of specialized approaches in enhancing creative reasoning in AI.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 8 of its 15 references that are in the map. First posted on arXiv 24 Feb 2024.
Builds on
8 of 15 references.
References · 8
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- 2021DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharingcited by 1,219
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- 2018A Simple Method for Commonsense Reasoningcited by 223
- 2019Semantics-aware BERT for Language Understandingcited by 111
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- 2021Prompting Contrastive Explanations for Commonsense Reasoning Taskscited by 45
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Citing papers per year: 2024: 1.
1 paper.