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 …
Improving causal reasoning in large language models: A survey
Causal reasoning (CR) is a crucial aspect of intelligence, essential for problem-solving,
decision-making, and understanding the world. While large language models (LLMs) can …
decision-making, and understanding the world. While large language models (LLMs) can …
Logical reasoning over natural language as knowledge representation: A survey
Logical reasoning is central to human cognition and intelligence. It includes deductive,
inductive, and abductive reasoning. Past research of logical reasoning within AI uses formal …
inductive, and abductive reasoning. Past research of logical reasoning within AI uses formal …
Large language models are not strong abstract reasoners
Large Language Models have shown tremendous performance on a large variety of natural
language processing tasks, ranging from text comprehension to common sense reasoning …
language processing tasks, ranging from text comprehension to common sense reasoning …
tasksource: A large collection of nlp tasks with a structured dataset preprocessing framework
D Sileo - Proceedings of the 2024 Joint International Conference …, 2024 - aclanthology.org
Abstract The HuggingFace Datasets Hub hosts thousands of datasets, offering exciting
opportunities for language model training and evaluation. However, datasets for a specific …
opportunities for language model training and evaluation. However, datasets for a specific …
LogicNet: A Logical Consistency Embedded Face Attribute Learning Network
Ensuring logical consistency in predictions is a crucial yet overlooked aspect in multi-
attribute classification. We explore the potential reasons for this oversight and introduce two …
attribute classification. We explore the potential reasons for this oversight and introduce two …
Enhancing Reasoning Capabilities of LLMs via Principled Synthetic Logic Corpus
T Morishita, G Morio, A Yamaguchi… - arXiv preprint arXiv …, 2024 - arxiv.org
Large language models (LLMs) are capable of solving a wide range of tasks, yet they have
struggled with reasoning. To address this, we propose $\textbf {Additional Logic Training …
struggled with reasoning. To address this, we propose $\textbf {Additional Logic Training …
Abstract Meaning Representation-Based Logic-Driven Data Augmentation for Logical Reasoning
Combining large language models with logical reasoning enhances their capacity to
address problems in a robust and reliable manner. Nevertheless, the intricate nature of …
address problems in a robust and reliable manner. Nevertheless, the intricate nature of …