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Relational and Fine-Grained Argument Mining
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In: Datenbank-Spektrum (2020)
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SimAlign: High Quality Word Alignments without Parallel Training Data using Static and Contextualized Embeddings
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In: Findings of ACL: EMNLP 2020 (2020)
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Monolingual and Multilingual Reduction of Gender Bias in Contextualized Representations
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Increasing Learning Efficiency of Self-Attention Networks through Direct Position Interactions, Learnable Temperature, and Convoluted Attention
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47 |
SimAlign: High Quality Word Alignments without Parallel Training Data using Static and Contextualized Embeddings ...
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48 |
Identifying Necessary Elements for BERT's Multilinguality ...
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49 |
Identifying Elements Essential for BERT’s Multilinguality ...
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50 |
Identifying Necessary Elements for BERT’s Multilinguality ...
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51 |
Monolingual and Multilingual Reduction of Gender Bias in Contextualized Representations ...
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52 |
SimAlign: High Quality Word Alignments without Parallel Training Data using Static and Contextualized Embeddings ...
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54 |
Predicting the Growth of Morphological Families from Social and Linguistic Factors ...
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55 |
Negated and Misprimed Probes for Pretrained Language Models: Birds Can Talk, But Cannot Fly ...
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56 |
Quantifying the Contextualization of Word Representations with Semantic Class Probing ...
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57 |
Sentence Meta-Embeddings for Unsupervised Semantic Textual Similarity ...
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58 |
Monolingual and Multilingual Reduction of Gender Bias in Contextualized Representations ...
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A Closer Look at Few-Shot Crosslingual Transfer: The Choice of Shots Matters ...
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Unsupervised Embedding-based Detection of Lexical Semantic Changes ...
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