Reasoning with language model prompting: A survey
Reasoning, as an essential ability for complex problem-solving, can provide back-end
support for various real-world applications, such as medical diagnosis, negotiation, etc. This …
support for various real-world applications, such as medical diagnosis, negotiation, etc. This …
Is chatgpt a good causal reasoner? a comprehensive evaluation
Causal reasoning ability is crucial for numerous NLP applications. Despite the impressive
emerging ability of ChatGPT in various NLP tasks, it is unclear how well ChatGPT performs …
emerging ability of ChatGPT in various NLP tasks, it is unclear how well ChatGPT performs …
Leveraging on causal knowledge for enhancing the root cause analysis of equipment spot inspection failures
Causal correlation data over the equipment spot-inspection operation and maintenance
(O&M) records and fault investigation sheets potentially reflect the state related to the causal …
(O&M) records and fault investigation sheets potentially reflect the state related to the causal …
Improving deep learning with prior knowledge and cognitive models: A survey on enhancing explainability, adversarial robustness and zero-shot learning
F Mumuni, A Mumuni - Cognitive Systems Research, 2024 - Elsevier
We review current and emerging knowledge-informed and brain-inspired cognitive systems
for realizing adversarial defenses, eXplainable Artificial Intelligence (XAI), and zero-shot or …
for realizing adversarial defenses, eXplainable Artificial Intelligence (XAI), and zero-shot or …
CausalKGPT: industrial structure causal knowledge-enhanced large language model for cause analysis of quality problems in aerospace product manufacturing
The whole cycle for manufacturing aerospace thin-walled shells is a lengthy and
sophisticated process. A large amount of quality-related data exists within and between …
sophisticated process. A large amount of quality-related data exists within and between …
The magic of IF: Investigating causal reasoning abilities in large language models of code
Causal reasoning, the ability to identify cause-and-effect relationship, is crucial in human
thinking. Although large language models (LLMs) succeed in many NLP tasks, it is still …
thinking. Although large language models (LLMs) succeed in many NLP tasks, it is still …
Dual disentanglement of user–item interaction for recommendation with causal embedding
C Wang, Y Ye, L Ma, D Li, L Zhuang - Information Processing & …, 2023 - Elsevier
To achieve personalized recommendations, the recommender system selects the items that
users may like by learning the collected user–item interaction data. However, the acquisition …
users may like by learning the collected user–item interaction data. However, the acquisition …
Mitigating reporting bias in semi-supervised temporal commonsense inference with probabilistic soft logic
Acquiring high-quality temporal common sense (TCS) knowledge from free-form text is a
crucial but challenging problem for event-centric natural language understanding, due to the …
crucial but challenging problem for event-centric natural language understanding, due to the …
Towards fine-grained causal reasoning and qa
Understanding causality is key to the success of NLP applications, especially in high-stakes
domains. Causality comes in various perspectives such as enable and prevent that, despite …
domains. Causality comes in various perspectives such as enable and prevent that, despite …
On the Evolution of Knowledge Graphs: A Survey and Perspective
Knowledge graphs (KGs) are structured representations of diversified knowledge. They are
widely used in various intelligent applications. In this article, we provide a comprehensive …
widely used in various intelligent applications. In this article, we provide a comprehensive …