The SIGMORPHON 2020 Shared Task on Unsupervised Morphological Paradigm Completion
원문 초록
In this paper, we describe the findings of the SIGMORPHON 2020 shared task on unsupervised morphological paradigm completion (SIGMORPHON 2020 Task 2), a novel task in the field of inflectional morphology. Participants were asked to submit systems which take raw text and a list of lemmas as input, and output all inflected forms, i.e., the entire morphological paradigm, of each lemma. In order to simulate a realistic use case, we first released data for 5 development languages. However, systems were officially evaluated on 9 surprise languages, which were only revealed a few days before the submission deadline. We provided a modular baseline system, which is a pipeline of 4 components. 3 teams submitted a total of 7 systems, but, surprisingly, none of the submitted systems was able to improve over the baseline on average over all 9 test languages. Only on 3 languages did a submitted system obtain the best results. This shows that unsupervised morphological paradigm completion is still largely unsolved. We present an analysis here, so that this shared task will ground further research on the topic.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Identifying the Smallest Adversarial Load Perturbations that Render DC-OPF Infeasible
Distributed Lyapunov Functions for Nonlinear Networks
Optimization over Sparse Support-Preserving Sets: Two-Step Projection with Global Optimality Guarantees
Know When to Abstain: Optimal Selective Classification with Likelihood Ratios
Prompt Tuning Vision Language Models with Margin Regularizer for Few-Shot Learning under Distribution Shifts
Vulnerability of Transfer-Learned Neural Networks to Data Reconstruction Attacks in Small-Data Regime
토론
이 논문과 연결된 포럼 글이 아직 없습니다.