What type of study is this?

This is a Literature Review study.

October 17, 2025Open Access

Reasoning in Large Language Models: A Survey

View Full Paper

Ask AI

Bookmark

Authors

YFYu FuUniversity of Science and Technology of China YKYu KangUniversity of Science and Technology of China YZYong ZhaoHankyong National University

Discussion

Member takes

Implication

This survey explores reasoning methods in large language models and their impact on information retrieval, suggesting improvements in performance and interpretability.

Key Points

Large language models exhibit significant capabilities but struggle with structured reasoning, impacting complex tasks.
Cutting-edge strategies like prompt engineering and neural-symbolic architectures show measurable enhancement in accuracy.
Establishing a taxonomy of reasoning-enhanced information retrieval models reveals issues in multi-hop reasoning and consistency.
Future efforts should focus on dynamic knowledge integration and reasoning-aware training to advance large language models.

Cite This Study

Fu et al. (2025) studied this question.

synapsesocial.com/papers/68f199c5de32064e504dcf5a https://doi.org/10.20944/preprints202510.1024.v1

View Full Paper

Ask AI

Bookmark

Implication

This survey explores reasoning methods in large language models and their impact on information retrieval, suggesting improvements in performance and interpretability.

Reasoning in Large Language Models: A Survey

Discussion

Member takes

Implication

Key Points

Cite This Study

Reasoning in Large Language Models: A Survey

Discussion

Member takes

Implication

Key Points

Cite This Study

Also Consider

Also Consider