Reasoning skills of large language models are often overestimated
https://news.mit.edu/2024/reasoning-skills-large-language-models-often-overestimated-0711
#ycombinator #MIT_CSAIL #MIT_IBM_Watson_AI_Lab #MIT_Quest_for_Intelligence #large_language_models_LLMs #computer_reasoning #abstract_task_solving #Counterfactual_tasks #general_AI #Zhaofeng_Wu #Yoon_Kim #Jacob_Andreas
https://news.mit.edu/2024/reasoning-skills-large-language-models-often-overestimated-0711
#ycombinator #MIT_CSAIL #MIT_IBM_Watson_AI_Lab #MIT_Quest_for_Intelligence #large_language_models_LLMs #computer_reasoning #abstract_task_solving #Counterfactual_tasks #general_AI #Zhaofeng_Wu #Yoon_Kim #Jacob_Andreas
Reasoning skills of large language models are often overestimated
MIT CSAIL researchers developed an evaluation framework for large language models about counterfactual tasks. They found that LLMs can recite answers, but struggle to reason as it relates to abstract task-solving.
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