35 citations · 93 across the 10 of their papers we have counts for
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Automatic Question-Answer Generation for Long-Tail Knowledge
Rohan Kumar, Youngmin Kim, Sunitha Ravi +4
Pretrained Large Language Models (LLMs) have gained significant attention for addressing open-domain Question Answering (QA). While they exhibit high accuracy in answering question…
SEMQA: Semi-Extractive Multi-Source Question Answering
Tal Schuster, Adam D. Lelkes, Haitian Sun +4
Recently proposed long-form question answering (QA) systems, supported by large language models (LLMs), have shown promising capabilities. Yet, attributing and verifying their gene…
Answering Ambiguous Questions with a Database of Questions, Answers, and Revisions
Haitian Sun, William W. Cohen, Ruslan Salakhutdinov
Many open-domain questions are under-specified and thus have multiple possible answers, each of which is correct under a different interpretation of the question. Answering such am…
Reasoning over Logically Interacted Conditions for Question Answering
Haitian Sun, William W. Cohen, Ruslan Salakhutdinov
Some questions have multiple answers that are not equally correct, i.e. answers are different under different conditions. Conditions are used to distinguish answers as well as to p…
ConditionalQA: A Complex Reading Comprehension Dataset with Conditional Answers
Haitian Sun, William W. Cohen, Ruslan Salakhutdinov
We describe a Question Answering (QA) dataset that contains complex questions with conditional answers, i.e. the answers are only applicable when certain conditions apply. We call…
Iterative Hierarchical Attention for Answering Complex Questions over Long Documents
Haitian Sun, William W. Cohen, Ruslan Salakhutdinov
We propose a new model, DocHopper, that iteratively attends to different parts of long, hierarchically structured documents to answer complex questions. Similar to multi-hop questi…