Subjective Topic meets LLMs: Unleashing Comprehensive, Reflective and Creative Thinking through the Negation of Negation
Fangrui Lv, Kaixiong Gong, Jian Liang, Xinyu Pang, Changshui Zhang
摘要
Large language models (LLMs) exhibit powerful reasoning capacity, as evidenced by prior studies focusing on objective topics that with unique standard answer such as arithmetic and commonsense reasoning. However, the reasoning to definite answers emphasizes more on logical thinking, and falls short in effectively reflecting the comprehensive, reflective, and creative thinking that is also critical for the overall reasoning prowess of LLMs. In light of this, we build a dataset SJTP comprising diverse SubJective ToPics with free responses, as well as three evaluation indicators to fully explore LLM's reasoning ability. We observe that a sole emphasis on logical thinking falls short in effectively tackling subjective challenges. Therefore, we introduce a framework grounded in the principle of the Negation of Negation (NeoN) to unleash the potential comprehensive, reflective, and creative thinking abilities of LLMs. Comprehensive experiments on SJTP demonstrate the efficacy of NeoN, and the enhanced performance on various objective reasoning tasks unequivocally underscores the benefits of stimulating LLM's subjective thinking in augmenting overall reasoning capabilities.
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引用它的顶会 Paper2
- Diversity-Enhanced Reasoning for Subjective QuestionsYumeng Wang, Zhiyuan Fan, Jiayu Liu, Jen-Tse Huang 等ICLR 2026 · 被引用 13 次
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