Leveraging Language Models for Commonsense Reasoning
Commonsense reasoning is crucial in AI models, yet modern ML methods struggle with it. This study explores how explanations can enhance reasoning in language models, focusing on the Common Sense Question Answering dataset. Key contributions include Common Sense Explanations (CoS-E) and Commonsense Auto-Generated Explanations (CAGE) which outperform baselines and provide justifications for predictions. Related works delve into natural language explanations and interpretability. The goal is to improve AI performance through enhanced commonsense reasoning.
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Discussion Topics How to green the three dimensions of entrepreneurship/job creation 1. Policy framework 2. Skills development/innovation 3. Services to business/financing
Questions 1. Policy framework: What are the priority aspects for policy framework change to enable growth of green businesses? 2. Skills development/innovation: How can skills development / eco-innovation be best facilitated in the private sector? 3. Services to business/financing: What are the key requirements to facilitate access to finance for green investments in SMEs?
