Large Language Model Reasoning Failures https://www.arxiv.org/abs/2602.06176 (Transactions on Machine Learning Research)
"our survey provides a structured perspective on systemic weaknesses in LLM reasoning, offering valuable insights and guiding future research towards building stronger, more reliable, and robust reasoning capabilities. We additionally release a comprehensive collection of research works on LLM reasoning failures, as a GitHub repository at https://github.com/Peiyang-Song/Awesome-LLM-Reasoning-Failures, to provide an easy entry point to this area." JM -- LOGICA-L Lista acadêmica brasileira dos profissionais e estudantes da área de Lógica <[email protected]> --- Você está recebendo esta mensagem porque se inscreveu no grupo "LOGICA-L" dos Grupos do Google. Para cancelar inscrição nesse grupo e parar de receber e-mails dele, envie um e-mail para [email protected]. Para ver esta conversa, acesse https://groups.google.com/a/dimap.ufrn.br/d/msgid/logica-l/CAO6j_LjUDXc7RDxg%3DV6h4qSn4_ayYsX77xJuKwr9BhvZC-G1aA%40mail.gmail.com.
