Thinking about the future is one of the important activities that people do in daily life. Futurists also pay a lot of effort into figuring out possible scenarios for the future. We argue that the exploration of this direction is still in an early stage in the NLP research. To this end, we propose three argument generation tasks in the financial application scenario. Our experimental results show these tasks are still big challenges for representative generation models. Based on our empirical results, we further point out several unresolved issues and challenges in this research direction.

翻译：思考未来是人们日常生活中的重要活动之一。未来学家也投入大量精力探索未来可能的情景。我们认为，自然语言处理研究对这一方向的探索仍处于早期阶段。为此，我们提出了金融应用场景下的三项论证生成任务。实验结果表明，这些任务对当前具有代表性的生成模型仍构成重大挑战。基于实证结果，我们进一步指出了该研究方向中若干尚未解决的问题与挑战。