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-license: cc-by-4.0
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+license: cc-by-4.0
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+# NYT-Connections
+This repository contains the `NYT-Connections` dataset proposed in the work *NYT-Connections: A Deceptively Simple Text Classification Task that Stumps System-1 Thinkers*. This work will be published in the 31st International Conference on Computational Linguistics in January of 2025.
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+Authors: Angel Yahir Loredo Lopez, Tyler McDonald, Ali Emami
+## Paper Abstract
+Large Language Models (LLMs) have shown impressive performance on various benchmarks, yet their ability to engage in deliberate reasoning remains questionable. We present NYT-Connections, a collection of 358 simple word classification puzzles derived from the New York Times Connections game. This benchmark is designed to penalize quick, intuitive ``System 1'' thinking, isolating fundamental reasoning skills. We evaluated six recent LLMs, a simple machine learning heuristic, and humans across three configurations: single-attempt, multiple attempts without hints, and multiple attempts with contextual hints. Our findings reveal a significant performance gap: even top-performing LLMs like GPT-4 fall short of human performance by nearly 30\%. Notably, advanced prompting techniques such as Chain-of-Thought and Self-Consistency show diminishing returns as task difficulty increases. NYT-Connections uniquely combines linguistic isolation, resistance to intuitive shortcuts, and regular updates to mitigate data leakage, offering a novel tool for assessing LLM reasoning capabilities.