Commonsense Reasoning
Commonsense reasoning, the ability of AI systems to understand and apply everyday knowledge, is a crucial area of research aiming to bridge the gap between human and artificial intelligence. Current research focuses on integrating large language models (LLMs) with other modalities like vision and tactile data, often using techniques like instruction tuning, multimodal learning, and knowledge graph integration to improve performance on various benchmarks. This work is significant because enhanced commonsense reasoning is essential for building more robust, reliable, and explainable AI systems across diverse applications, including robotics, deepfake detection, and conversational AI.
Papers
What Makes the Story Forward? Inferring Commonsense Explanations as Prompts for Future Event Generation
Li Lin, Yixin Cao, Lifu Huang, Shu'ang Li, Xuming Hu, Lijie Wen, Jianmin Wang
COPA-SSE: Semi-structured Explanations for Commonsense Reasoning
Ana Brassard, Benjamin Heinzerling, Pride Kavumba, Kentaro Inui