Papers with multi-hop models

3 papers
How Well Do Multi-hop Reading Comprehension Models Understand Date Information? (2022.aacl-short)

Copied to clipboard

Challenge: Existing multi-hop reading comprehension datasets have reasoning shortcuts that can be used to answer comparison questions without performing multi- hop reasoning.
Approach: They propose a dataset with three probing tasks in addition to the main question . they then evaluate the model's ability to understand date information .
Outcome: The proposed model performs well in date comparison and number subtraction tasks.
Compositional Questions Do Not Necessitate Multi-hop Reasoning (P19-1)

Copied to clipboard

Challenge: a single-hop reasoning model can solve much more of the dataset than previously thought.
Approach: They propose a single-hop BERT-based RC model that achieves 67 F1 . they propose an evaluation setting where humans are not shown all paragraphs .
Outcome: The proposed model achieves 67 F1—comparable to state-of-the-art multi-hop models.
Constructing A Multi-hop QA Dataset for Comprehensive Evaluation of Reasoning Steps (2020.coling-main)

Copied to clipboard

Challenge: Existing multi-hop question answering datasets do not provide a complete explanation for the reasoning process from the question to the answer.
Approach: They propose a multi-hop question answering dataset that uses structured and unstructured data to test reasoning skills.
Outcome: The proposed dataset ensures multi-hop reasoning while being challenging for multi-models.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations