The Odyssey of Commonsense Causality: From Foundational Benchmarks to Cutting-Edge Reasoning
Shaobo Cui, Zhijing Jin, Bernhard Schölkopf, Boi Faltings
摘要
Understanding commonsense causality is a unique mark of intelligence for humans.It helps people understand the principles of the real world better and benefits the decisionmaking process related to causation.For instance, commonsense causality is crucial in judging whether a defendant's action causes the plaintiff's loss in determining legal liability.Despite its significance, a systematic exploration of this topic is notably lacking.Our comprehensive survey bridges this gap by focusing on taxonomies, benchmarks, acquisition methods, qualitative reasoning, and quantitative measurements in commonsense causality, synthesizing insights from over 200 representative articles.Our work aims to provide a systematic overview, update scholars on recent advancements, provide a pragmatic guide for beginners, and highlight promising future research directions in this vital field.A summary of the related literature is available at https://github. com/cui-shaobo/causality-papers .
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引用它的顶会 Paper2
- Discovery of the Hidden World with Large Language ModelsChenxi Liu, Yongqiang Chen, Tongliang Liu, Mingming Gong 等NeurIPS 2024 · 被引用 26 次
- Nuance Matters: Probing Epistemic Consistency in Causal ReasoningShaobo Cui, Junyou Li, Luca Mouchel, Yiyang Feng 等AAAI 2025 · 被引用 2 次
它引用的顶会 Paper23
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- Chain-of-Thought Prompting Elicits Reasoning in Large Language ModelsJason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma 等NeurIPS 2022 · 被引用 22,562 次
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- Deberta: decoding-Enhanced Bert with Disentangled AttentionPengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu ChenICLR 2021 · 被引用 3,729 次
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