Papers with dual process theory

3 papers
Deep Cognitive Reasoning Network for Multi-hop Question Answering over Knowledge Graphs (2021.findings-acl)

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Challenge: Knowledge Graphs (KGs) store structured human knowledge with nodes and edges being entities and relations between them.
Approach: They propose a deep cognitive reasoning network that uses two phases to find answers in large candidate entity sets.
Outcome: The proposed method significantly outperforms state-of-the-art methods on benchmark datasets.
Cognitive Graph for Multi-Hop Reading Comprehension at Scale (P19-1)

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Challenge: a new framework for multi-hop reading comprehension question answering is needed to cross the chasm of reading comprehension between machine and human.
Approach: They propose a CogQA framework for multi-hop reading comprehension question answering in web-scale documents that builds a cognitive graph in an iterative process by coordinating an implicit extraction module and an explicit reasoning module.
Outcome: The proposed framework outperforms the best competitor in the hotpotQA dataset in F1 . it provides explainable reasoning paths and accurate answers, while giving accurate answers .
From Complex to Simple: Unraveling the Cognitive Tree for Reasoning with Small Language Models (2023.findings-emnlp)

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Challenge: Existing methods to solve complex logical reasoning problems are cumbersome for language models.
Approach: They propose to use iterative methodology to construct a cognitive tree using language models . they propose to generate multiple responses by utilizing in-context examples .
Outcome: The proposed model achieves a performance level comparable to that of GPT-3.5 . the proposed model contains fewer parameters than 5% of the model with 175B parameters .

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