Výsledky vyhledávání - "Fisher, Doug"

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Large Language Model Recall Uncertainty is Modulated by the Fan Effect

Autor: Roberts, Jesse, Moore, Kyle, Pham, Thao, Ewaleifoh, Oseremhen, Fisher, Doug

This paper evaluates whether large language models (LLMs) exhibit cognitive fan effects, similar to those discovered by Anderson in humans, after being pre-trained on human textual data. We conduct two sets of in-context recall experiments designed t

Externí odkaz: http://arxiv.org/abs/2407.06349

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The Base-Rate Effect on LLM Benchmark Performance: Disambiguating Test-Taking Strategies from Benchmark Performance

Autor: Moore, Kyle, Roberts, Jesse, Pham, Thao, Ewaleifoh, Oseremhen, Fisher, Doug

Cloze testing is a common method for measuring the behavior of large language models on a number of benchmark tasks. Using the MMLU dataset, we show that the base-rate probability (BRP) differences across answer tokens are significant and affect task

Externí odkaz: http://arxiv.org/abs/2406.11634

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Do Large Language Models Learn Human-Like Strategic Preferences?

Autor: Roberts, Jesse, Moore, Kyle, Fisher, Doug

In this paper, we evaluate whether LLMs learn to make human-like preference judgements in strategic scenarios as compared with known empirical results. Solar and Mistral are shown to exhibit stable value-based preference consistent with humans and ex

Externí odkaz: http://arxiv.org/abs/2404.08710

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Using Artificial Populations to Study Psychological Phenomena in Neural Models

Autor: Roberts, Jesse, Moore, Kyle, Wilenzick, Drew, Fisher, Doug

The recent proliferation of research into transformer based natural language processing has led to a number of studies which attempt to detect the presence of human-like cognitive behavior in the models. We contend that, as is true of human psycholog

Externí odkaz: http://arxiv.org/abs/2308.08032

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