Add to ORKGLogical reasoning remains a pivotal component within the realm of artificial intelligence. The recent evolution of large language models (LLMs) has marked significant progress in this domain. The adoption of strategies like chain-of-thought (CoT) has enhanced the performance of LLMs across diverse reasoning tasks. Nonetheless, logical reasoning that involves proof planning, specifically those that necessitate the validation of explanation accuracy, continues to present stumbling blocks. In this study, we first evaluate the efficacy of LLMs with advanced CoT strategies concerning such tasks. Our analysis reveals that LLMs still struggle to navigate complex reasoning chains, which demand the meticulous linkage of premises to derive a cogent c...
One way that the current state of the art measures the reasoning ability of transformer-based models...
Large language models (LMs) beyond a certain scale, demonstrate the emergent capability of generatin...
Combining large language models with logical reasoning enhance their capacity to address problems in...
Large language models (LLMs) have shown remarkable reasoning capabilities given chain-of-thought pro...
Logical reasoning consistently plays a fundamental and significant role in the domains of knowledge ...
Large language models (LLMs) have gained enormous attention from both academia and industry, due to ...
Recently, large language models (LLMs), including notable models such as GPT-4 and burgeoning commun...
Deductive reasoning (drawing conclusions from assumptions) is a challenging problem in NLP. In this ...
In this position paper, we propose a way of exploiting formal proofs to put forward several explaina...
Large language models (LLMs), such as GPT-3.5 and GPT-4, have greatly advanced the performance of ar...
Remarkable progress has been made on automated reasoning with knowledge specified as unstructured, n...
Chain-of-Thought(CoT) prompting and its variants explore equipping large language models (LLMs) with...
In settings from fact-checking to question answering, we frequently want to know whether a collectio...
Large language models (LLMs) can perform complex reasoning by generating intermediate reasoning step...
To augment language models with the ability to reason, researchers usually prompt or finetune them t...
One way that the current state of the art measures the reasoning ability of transformer-based models...
Large language models (LMs) beyond a certain scale, demonstrate the emergent capability of generatin...
Combining large language models with logical reasoning enhance their capacity to address problems in...
Large language models (LLMs) have shown remarkable reasoning capabilities given chain-of-thought pro...
Logical reasoning consistently plays a fundamental and significant role in the domains of knowledge ...
Large language models (LLMs) have gained enormous attention from both academia and industry, due to ...
Recently, large language models (LLMs), including notable models such as GPT-4 and burgeoning commun...
Deductive reasoning (drawing conclusions from assumptions) is a challenging problem in NLP. In this ...
In this position paper, we propose a way of exploiting formal proofs to put forward several explaina...
Large language models (LLMs), such as GPT-3.5 and GPT-4, have greatly advanced the performance of ar...
Remarkable progress has been made on automated reasoning with knowledge specified as unstructured, n...
Chain-of-Thought(CoT) prompting and its variants explore equipping large language models (LLMs) with...
In settings from fact-checking to question answering, we frequently want to know whether a collectio...
Large language models (LLMs) can perform complex reasoning by generating intermediate reasoning step...
To augment language models with the ability to reason, researchers usually prompt or finetune them t...
One way that the current state of the art measures the reasoning ability of transformer-based models...
Large language models (LMs) beyond a certain scale, demonstrate the emergent capability of generatin...
Combining large language models with logical reasoning enhance their capacity to address problems in...