Papers › Iterative Hierarchical Attention for Answering Complex Questions over Long Documents
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 question-answering (QA) systems, at each step, DocHopper uses a query q to attend to information from a document, combines this ``retrieved'' information with q to produce the next query. However, in contrast to most previous multi-hop QA systems, DocHopper is able to ``retrieve'' either short passages or long sections of the document, thus emulating a multi-step process of ``navigating'' through a long document to answer a question. To enable this novel behavior, DocHopper does not combine document information with q by concatenating text to the text of q, but by combining a compact neural representation of q with a compact neural representation of a hierarchical part of the document, which can potentially be quite large. We experiment with DocHopper on four different QA tasks that require reading long and complex documents to answer multi-hop questions, and show that DocHopper achieves state-of-the-art results on three of the datasets. Additionally, DocHopper is efficient at inference time, being 3--10 times faster than the baselines.
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Question Answering | ConditionalQA | DocHopper | Conditional (answers) | 42.0 / 46.4 | #2 of 3 | Archive leaderboard | report |
| Question Answering | ConditionalQA | DocHopper | Conditional (w/ conditions) | 3.1 / 3.8 | #2 of 3 | Archive leaderboard | report |
| Question Answering | ConditionalQA | DocHopper | Overall (answers) | 40.6 / 45.2 | #2 of 3 | Archive leaderboard | report |
| Question Answering | ConditionalQA | DocHopper | Overall (w/ conditions) | 31.9 / 36.0 | #2 of 3 | Archive leaderboard | report |
| Question Answering | HybridQA | DocHopper | ANS-EM | 46.3 | #3 of 4 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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