Papers › Few-Shot Document-Level Relation Extraction
Few-Shot Document-Level Relation Extraction
Nicholas Popovic, Michael Färber
We present FREDo, a few-shot document-level relation extraction (FSDLRE) benchmark. As opposed to existing benchmarks which are built on sentence-level relation extraction corpora, we argue that document-level corpora provide more realism, particularly regarding none-of-the-above (NOTA) distributions. Therefore, we propose a set of FSDLRE tasks and construct a benchmark based on two existing supervised learning data sets, DocRED and sciERC. We adapt the state-of-the-art sentence-level method MNAV to the document-level and develop it further for improved domain adaptation. We find FSDLRE to be a challenging setting with interesting new characteristics such as the ability to sample NOTA instances from the support set. The data, code, and trained models are available online (https://github.com/nicpopovic/FREDo).
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Datasets
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Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Few-Shot Relation Classification | DocRED | DL-MNAV | F1 (1-Doc) | 7.05 | #1 of 1 | Archive leaderboard | report |
| Few-Shot Relation Classification | DocRED | DL-MNAV | F1 (3-Doc) | 8.42 | #1 of 1 | Archive leaderboard | report |
| Few-Shot Relation Classification | FREDo | DL-MNAV | F1 (1-Doc) | 7.05 | #1 of 1 | Archive leaderboard | report |
| Few-Shot Relation Classification | FREDo | DL-MNAV | F1 (3-Doc) | 8.42 | #1 of 1 | Archive leaderboard | report |
| Few-Shot Relation Classification | FREDo (cross-domain) | DL-MNAV+SIE+SBN | F1 (1-Doc) | 2.85 | #1 of 1 | Archive leaderboard | report |
| Few-Shot Relation Classification | FREDo (cross-domain) | DL-MNAV+SIE+SBN | F1 (3-Doc) | 3.72 | #1 of 1 | Archive leaderboard | report |
| Few-Shot Relation Classification | SciERC | DL-MNAV+SIE+SBN | F1 (1-Doc) | 2.85 | #1 of 1 | Archive leaderboard | report |
| Few-Shot Relation Classification | SciERC | DL-MNAV+SIE+SBN | F1 (3-Doc) | 3.72 | #1 of 1 | Archive leaderboard | report |
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