Researchers are questioning whether large language models (LLMs) are truly "reasoning" in the way humans do, or if their performance is due to other factors. Studies have shown that LLMs can produce accurate results on reasoning tasks, but the "chains of thought" that underlie these results may not be meaningful or causal to the model's reasoning process. Instead, these chains of thought may be simply a way to load up the model's context window and make it more likely to predict certain strings of text. AI summary
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