Papers › Multi-Hop Paragraph Retrieval for Open-Domain Question Answering
Multi-Hop Paragraph Retrieval for Open-Domain Question Answering
Yair Feldman, Ran El-Yaniv
This paper is concerned with the task of multi-hop open-domain Question Answering (QA). This task is particularly challenging since it requires the simultaneous performance of textual reasoning and efficient searching. We present a method for retrieving multiple supporting paragraphs, nested amidst a large knowledge base, which contain the necessary evidence to answer a given question. Our method iteratively retrieves supporting paragraphs by forming a joint vector representation of both a question and a paragraph. The retrieval is performed by considering contextualized sentence-level representations of the paragraphs in the knowledge source. Our method achieves state-of-the-art performance over two well-known datasets, SQuAD-Open and HotpotQA, which serve as our single- and multi-hop open-domain QA benchmarks, respectively.
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Code
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Code Syntology ran Syntology
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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 | HotpotQA | MUPPET | ANS-EM | 0.306 | #55 of 72 | Archive leaderboard | report |
| Question Answering | HotpotQA | MUPPET | ANS-F1 | 0.403 | #55 of 72 | Archive leaderboard | report |
| Question Answering | HotpotQA | MUPPET | JOINT-EM | 0.109 | #55 of 72 | Archive leaderboard | report |
| Question Answering | HotpotQA | MUPPET | JOINT-F1 | 0.270 | #55 of 72 | Archive leaderboard | report |
| Question Answering | HotpotQA | MUPPET | SUP-EM | 0.167 | #55 of 72 | Archive leaderboard | report |
| Question Answering | HotpotQA | MUPPET | SUP-F1 | 0.473 | #55 of 72 | 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.
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