{"ID":2868103,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.01219","arxiv_id":"2510.01219","title":"Uncovering Implicit Bias in Large Language Models with Concept Learning Dataset","abstract":"We introduce a dataset of concept learning tasks that helps uncover implicit biases in large language models. Using in-context concept learning experiments, we found that language models may have a bias toward upward monotonicity in quantifiers; such bias is less apparent when the model is tested by direct prompting without concept learning components. This demonstrates that in-context concept learning can be an effective way to discover hidden biases in language models.","short_abstract":"We introduce a dataset of concept learning tasks that helps uncover implicit biases in large language models. Using in-context concept learning experiments, we found that language models may have a bias toward upward monotonicity in quantifiers; such bias is less apparent when the model is tested by direct prompting wi...","url_abs":"https://arxiv.org/abs/2510.01219","url_pdf":"https://arxiv.org/pdf/2510.01219v2","authors":"[\"Leroy Z. Wang\"]","published":"2025-09-21T09:04:31Z","proceeding":"cs.CL","tasks":"[\"cs.CL\",\"cs.AI\"]","methods":"[\"Language Model\"]","has_code":false}