Non-sequence models for tokenization replacement

CORDIS fournit des liens vers les livrables publics et les publications des projets HORIZON.

Les liens vers les livrables et les publications des projets du 7e PC, ainsi que les liens vers certains types de résultats spécifiques tels que les jeux de données et les logiciels, sont récupérés dynamiquement sur OpenAIRE .

Livrables

Data Management Plan

Publish datasets and software produced in the project.

Publications

The better your Syntax, the better your Semantics? Probing Pretrained Language Models for the English Comparative Correlative

Auteurs: Leonie Weissweiler, Valentin Hofmann, Abdullatif Köksal, Hinrich Schütze
Publié dans: Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, Numéro December 2022, 2022
Éditeur: Association for Computational Linguistics

Modular and Parameter-Efficient Multimodal Fusion with Prompting

Auteurs: Sheng Liang, Mengjie Zhao, Hinrich Schuetze
Publié dans: Findings of the Association for Computational Linguistics: ACL 2022, Numéro May 2022, 2022
Éditeur: Association for Computational Linguistics

An Information-Theoretic Approach and Dataset for Probing GenderStereotypes in Multilingual Masked Language Models

Auteurs: Victor Steinborn, Philipp Dufter, Haris Jabbar, Hinrich Schütze
Publié dans: Findings of the Association for Computational Linguistics: NAACL 2022, Numéro July 2022, 2022
Éditeur: Association for Computational Linguistics

LMTurk: Few-Shot Learners as Crowdsourcing Workers in a Language-Model-as-a-Service Framework

Auteurs: Mengjie Zhao, Fei Mi, Yasheng Wang, Minglei Li, Xin Jiang, Qun Liu, Hinrich Schuetze
Publié dans: Findings of the Association for Computational Linguistics: NAACL 2022, Numéro July 2022, 2022
Éditeur: Association for Computational Linguistics

A Crosslingual Investigation of Conceptualization in 1335 Languages

Auteurs: Yihong Liu, Haotian Ye, Leonie Weissweiler, Philipp Wicke, Renhao Pei, Robert Zangenfeind, Hinrich Schütze
Publié dans: Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics, Numéro July 2023, 2023
Éditeur: Association for Computational Linguistics

Increasing Learning Efficiency of Self-Attention Networks throughDirect Position Interactions, Learnable Temperature,and Convoluted Attention

Auteurs: Philipp Dufter, Martin Schmitt, Hinrich Schütze
Publié dans: Proceedings of the 28th International Conference on Computational Linguistics, Numéro December 2020, 2020
Éditeur: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.74088

Glot500: Scaling Multilingual Corpora and Language Models to 500 Languages

Auteurs: Ayyoob ImaniGooghari, Peiqin Lin, Amir Hossein Kargaran, Silvia Severini, Masoud Jalili Sabet, Nora Kassner, Chunlan Ma, Helmut Schmid, André Martins, François Yvon, Hinrich Schütze
Publié dans: Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics, Numéro July 2023, 2023
Éditeur: Association for Computational Linguistics

Graph Algorithms for Multiparallel Word Alignment

Auteurs: Ayyoob Imani, Masoud Jalili Sabet, Lutfi Kerem Senel, Philipp Dufter, François Yvon, Hinrich Schütze
Publié dans: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, Numéro November 2021, 2021
Éditeur: Association for Computational Linguistics
DOI: 10.18653/v1/2021.emnlp-main.665

A Closer Look at Few-Shot Crosslingual Transfer: The Choice of Shots Matters

Auteurs: Mengjie Zhao, Yi Zhu, Ehsan Shareghi, Ivan Vulić, Roi Reichart, Anna Korhonen, Hinrich Schütze
Publié dans: Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), Numéro August 2021, 2021
Éditeur: Association for Computational Linguistics
DOI: 10.18653/v1/2021.acl-long.447

Does Manipulating Tokenization Aid Cross-Lingual Transfer? A Study on POS Tagging for Non-Standardized Languages

Auteurs: Verena Blaschke, Hinrich Schütze, Barbara Plank
Publié dans: Tenth Workshop on NLP for Similar Languages, Varieties and Dialects, Numéro May 2023, 2023
Éditeur: Association for Computational Linguistics

Graph-Based Multilingual Label Propagation for Low-Resource Part-of-Speech Tagging

Auteurs: Ayyoob ImaniGooghari, Silvia Severini, Masoud Jalili Sabet, François Yvon, Hinrich Schütze
Publié dans: Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, Numéro December 2022, 2022
Éditeur: Association for Computational Linguistics

Monolingual and Multilingual Reduction of Gender Bias in Contextualized Representations

Auteurs: Sheng Liang, Philipp Dufter, Hinrich Schütze
Publié dans: Proceedings of the 28th International Conference on Computational Linguistics, Numéro December 2020, 2020
Éditeur: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.74040

Automatically Identifying Words That Can Serve as Labels for Few-ShotText Classification

Auteurs: Timo Schick, Helmut Schmid, Hinrich Schütze
Publié dans: Proceedings of the 28th International Conference on Computational Linguistics, Numéro 8. - 11. December 2020, 2020
Éditeur: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.74034

Flow-Adapter Architecture for Unsupervised Machine Translation

Auteurs: Yihong Liu, Haris Jabbar, Hinrich Schuetze
Publié dans: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Numéro May 2022, 2022
Éditeur: Association for Computational Linguistics

Exploiting Cloze-Questions for Few-Shot Text Classification and Natural Language Inference

Auteurs: Timo Schick, Hinrich Schütze
Publié dans: Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, Numéro April 2021, 2021
Éditeur: Association for Computational Linguistics
DOI: 10.18653/v1/2021.eacl-main.20

CaMEL: Case Marker Extraction without Labels

Auteurs: Leonie Weissweiler, Valentin Hofmann, Masoud Jalili Sabet, Hinrich Schuetze
Publié dans: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Numéro May 2022, 2022
Éditeur: Association for Computational Linguistics

Superbizarre Is Not Superb: Derivational Morphology Improves BERT’s Interpretation of Complex Words

Auteurs: Valentin Hofmann, Janet Pierrehumbert, Hinrich Schütze
Publié dans: Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), Numéro August 2021, 2021
Éditeur: Association for Computational Linguistics
DOI: 10.18653/v1/2021.acl-long.279

On the Copying Problem of Unsupervised NMT: A Training Schedule with a Language Discriminator Loss

Auteurs: Yihong Liu, Alexandra Chronopoulou, Hinrich Schütze, Alexander Fraser
Publié dans: Proceedings of the 20th International Conference on Spoken Language Translation, Numéro July 2023, 2023
Éditeur: Association for Computational Linguistics

Generating Datasets with Pretrained Language Models

Auteurs: Timo Schick, Hinrich Schütze
Publié dans: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, Numéro November 2021, 2021
Éditeur: Association for Computational Linguistics
DOI: 10.18653/v1/2021.emnlp-main.555

This joke is [MASK]: Recognizing Humor and Offense with Prompting

Auteurs: Junze Li, Mengjie Zhao, Yubo Xie, Antonis Maronikolakis, Pearl Pu, Hinrich Schuetze
Publié dans: Proceedings of The 1st Transfer Learning for Natural Language Processing Workshop, Numéro December 2022, 2022
Éditeur: Proceedings of Machine Learning Research

It’s Not Just Size That Matters: Small Language Models Are Also Few-Shot Learners

Auteurs: Timo Schick, Hinrich Schütze
Publié dans: Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Numéro June 2021, 2021
Éditeur: Association for Computational Linguistics
DOI: 10.18653/v1/2021.naacl-main.185

The Reddit Politosphere: A Large-Scale Text and Network Resource of Online Political Discourse

Auteurs: Valentin Hofmann, Hinrich Schütze, Janet B. Pierrehumbert
Publié dans: Proceedings of the International AAAI Conference on Web and Social Media, Numéro May 2022, 2022
Éditeur: AAAI

Towards a Broad Coverage Named Entity Resource: A Data-Efficient Approach for Many Diverse Languages

Auteurs: Silvia Severini, Ayyoob ImaniGooghari, Philipp Dufter, Hinrich Schütze
Publié dans: Proceedings of the Thirteenth Language Resources and Evaluation Conference, Numéro June 2022, 2022
Éditeur: European Language Resources Association

An Embarrassingly Simple Method to Mitigate Undesirable Properties of Pretrained Language Model Tokenizers

Auteurs: Valentin Hofmann, Hinrich Schuetze, Janet Pierrehumbert
Publié dans: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), Numéro May 2022, 2022
Éditeur: Association for Computational Linguistics

Modeling Ideological Salience and Framing in Polarized Online Groups with Graph Neural Networks and Structured Sparsity

Auteurs: Valentin Hofmann, Xiaowen Dong, Janet Pierrehumbert, Hinrich Schuetze
Publié dans: Findings of the Association for Computational Linguistics: NAACL 2022, Numéro July 2022, 2022
Éditeur: Association for Computational Linguistics

Wine is not v i n. On the Compatibility of Tokenizations across Languages

Auteurs: Antonis Maronikolakis, Philipp Dufter, Hinrich Schütze
Publié dans: Findings of the Association for Computational Linguistics: EMNLP 2021, Numéro November 2021, 2021
Éditeur: Association for Computational Linguistics
DOI: 10.18653/v1/2021.findings-emnlp.205

CoDA21: Evaluating Language Understanding Capabilities of NLP Models With Context-Definition Alignment

Auteurs: Lütfi Kerem Senel, Timo Schick, Hinrich Schuetze
Publié dans: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), Numéro May 2022, 2022
Éditeur: Association for Computational Linguistics

Unsupervised Detection of Contextualized Embedding Bias with Application to Ideology

Auteurs: Valentin Hofmann, Janet Pierrehumbert, Hinrich Schütze
Publié dans: Proceedings of the 39th International Conference on Machine Learning, Numéro July 2022, 2022
Éditeur: Proceedings of Machine Learning Research

Multi-Multi-View Learning: Multilingual and Multi-Representation Entity Typing

Auteurs: Yadollah Yaghoobzadeh, Hinrich Schütze
Publié dans: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Numéro 31. October - 04. November 2018, 2018, Page(s) 3060-3066, ISBN 978-1-948087-84-1
Éditeur: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.61855

Joint Aspect and Polarity Classification for Aspect-based Sentiment Analysis with End-to-End Neural Networks

Auteurs: Martin Schmitt, Simon Steinheber, Konrad Schreiber, Benjamin Roth
Publié dans: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Numéro 31. October - 02. November 2018, 2018, Page(s) pp. 1109-1114, ISBN 978-1-948087-84-1
Éditeur: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.61858

Embedding Learning Through Multilingual Concept Induction

Auteurs: Philipp Dufter, Mengjie Zhao, Martin Schmitt, Alexander Fraser, Hinrich Schütze
Publié dans: Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, Numéro July 15-20, 2018, 2018, Page(s) 1520–1530, ISBN 978-1-948087-32-2
Éditeur: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.61841

Recurrent One-Hop Predictions for Reasoning over Knowledge Graphs

Auteurs: Wenpeng Yin, Yadollah Yaghoobzadeh, Hinrich Schütze
Publié dans: Proceedings of the 27th International Conference on Computational Linguistics, Numéro August 20-26, 2018, Page(s) 2369–2378, ISBN 978-1-948087-50-6
Éditeur: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.61860

Neural Transductive Learning and Beyond: Morphological Generation in the Minimal-Resource Setting

Auteurs: Katharina Kann, Hinrich Schütze
Publié dans: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Numéro October 31 - November 4, 2018, 2018, Page(s) 3254–3264, ISBN 978-1-948087-84-1
Éditeur: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.61867

Evaluating neural network explanation methods using hybrid documents and morphosyntactic agreement

Auteurs: Nina Poerner, Benjamin Roth, Hinrich Schütze
Publié dans: Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, Numéro July 15 - 20, 2018, 2018, Page(s) pages 340–350, ISBN 978-1-948087-32-2
Éditeur: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.61866

Probing for Semantic Classes: Diagnosing the Meaning Content of Word Embeddings

Auteurs: Yadollah Yaghoobzadeh, Katharina Kann, T. J. Hazen, Eneko Agirre, Hinrich Schütze
Publié dans: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, 2019, Page(s) 5740-5753
Éditeur: Association for Computational Linguistics
DOI: 10.18653/v1/p19-1574

SimAlign: High Quality Word Alignments without Parallel Training Data using Static and Contextualized Embeddings.

Auteurs: Masoud Jalili Sabet,Philipp Dufter,Hinrich Schütze
Publié dans: In: Findings of ACL: EMNLP 2020, 2020
Éditeur: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.72200

Automatic Domain Adaptation Outperforms Manual Domain Adaptation for Predicting Financial Outcomes

Auteurs: Marina Sedinkina, Nikolas Breitkopf, Hinrich Schütze
Publié dans: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, 2019, Page(s) 346-359
Éditeur: Association for Computational Linguistics
DOI: 10.18653/v1/p19-1034

BERTRAM: Improved Word Embeddings Have Big Impact on Contextualized Model Performance

Auteurs: Timo Schick,Hinrich Schütze
Publié dans: Proceedings of the 58th Conference of the Association for Computational Linguistics, ACL 2020, Seattle, USA, July 5 - July 10, 2020, 2020
Éditeur: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.72196

A Graph Auto-encoder Model of Derivational Morphology

Auteurs: Valentin Hofmann, Hinrich Schütze, Janet B. Pierrehumbert
Publié dans: Proceedings of the 58th Conference of the Association for Computational Linguistics, ACL 2020, Seattle, USA, July 5 - July 10, 2020, 2020
Éditeur: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.72197

Negated and Misprimed Probes for Pretrained Language Models: Birds Can Talk, But Cannot Fly

Auteurs: Nora Kassner, Hinrich Schütze
Publié dans: Proceedings of the 58th Conference of the Association for Computational Linguistics, ACL 2020, Seattle, USA, July 5 - July 10, 2020, 2020
Éditeur: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.72195

Sentence Meta-Embeddings for Unsupervised Semantic Textual Similarity

Auteurs: Nina Poerner, Ulli Waltinger, Hinrich Schütze
Publié dans: Proceedings of the 58th Conference of the Association for Computational Linguistics, ACL 2020, Seattle, USA, July 5 - July 10, 2020, 2020
Éditeur: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.72194

Analytical Methods for Interpretable Ultradense Word Embeddings

Auteurs: Philipp Dufter, Hinrich Schütze
Publié dans: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), 2019, Page(s) 1185-1191
Éditeur: Association for Computational Linguistics
DOI: 10.18653/v1/d19-1111

Predicting the Growth of Morphological Families from Social and Linguistic Factors

Auteurs: Valentin Hofmann, Janet B. Pierrehumbert, Hinrich Schütze
Publié dans: Proceedings of the 58th Conference of the Association for Computational Linguistics, ACL 2020, Seattle, USA, July 5 - July 10, 2020, 2020
Éditeur: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.72198

A Multilingual BPE Embedding Space for Universal Sentiment Lexicon Induction

Auteurs: Mengjie Zhao, Hinrich Schütze
Publié dans: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, 2019, Page(s) 3506-3517
Éditeur: Association for Computational Linguistics
DOI: 10.18653/v1/p19-1341

Neural Semi-Markov Conditional Random Fields for Robust Character-Based Part-of-Speech Tagging

Auteurs: Apostolos Kemos, Heike Adel, Hinrich Schütze
Publié dans: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2019, 2019
Éditeur: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.61846

Attentive Mimicking: Better Word Embeddings by Attending to Informative Contexts

Auteurs: Timo Schick, Hinrich Schütze
Publié dans: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2019, 2019
Éditeur: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.61844

Learning Semantic Representations for Novel Words: Leveraging Both Form and Context

Auteurs: Timo Schick, Hinrich Schütze
Publié dans: The Thirty-Third AAAI Conference on Artificial Intelligence, AAAI 2019, The Thirty-First Innovative Applications of Artificial Intelligence Conference, 2019
Éditeur: Association for the Advancement of Artificial Intelligence
DOI: 10.5282/ubm/epub.61859

Rare Words: A Major Problem for Contextualized Embeddings And How to Fix it by Attentive Mimicking

Auteurs: Timo Schick, Hinrich Schütze
Publié dans: The Thirty-Fourth AAAI Conference on Artificial Intelligence, AAAI 2020, The Thirty-Second Innovative Applications of Artificial Intelligence Conference,, 2020, ISBN 978-1-57735-809-1
Éditeur: Association for the Advancement of Artificial Intelligence
DOI: 10.5282/ubm/epub.61863

Few-Shot Text Generation with Natural Language Instructions

PVGRU: Generating Diverse and Relevant Dialogue Responses via Pseudo-Variational Mechanism

Auteurs: Yongkang Liu, Shi Feng, Daling Wang, Yifei Zhang, Hinrich Schütze
Publié dans: Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics, Numéro July 2023, 2023
Éditeur: Association for Computational Linguistics

BeliefBank: Adding Memory to a Pre-Trained Language Model for a Systematic Notion of Belief

Auteurs: Nora Kassner, Oyvind Tafjord, Hinrich Schütze, Peter Clark
Publié dans: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, Numéro November 2021, 2021
Éditeur: Association for Computational Linguistics
DOI: 10.18653/v1/2021.emnlp-main.697

Does She Wink or Does She Nod? A Challenging Benchmark for Evaluating Word Understanding of Language Models

Auteurs: Lutfi Kerem Senel, Hinrich Schütze
Publié dans: Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, Numéro April 2021, 2021
Éditeur: Association for Computational Linguistics
DOI: 10.18653/v1/2021.eacl-main.42

Dynamic Contextualized Word Embeddings

Multilingual LAMA: Investigating Knowledge in Multilingual Pretrained Language Models

Auteurs: Nora Kassner, Philipp Dufter, Hinrich Schütze
Publié dans: Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, Numéro April 2021, 2021
Éditeur: Association for Computational Linguistics
DOI: 10.18653/v1/2021.eacl-main.284

Static Embeddings as Efficient Knowledge Bases?

Auteurs: Philipp Dufter, Nora Kassner, Hinrich Schütze
Publié dans: Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Numéro June 2021, 2021
Éditeur: Association for Computational Linguistics
DOI: 10.18653/v1/2021.naacl-main.186

Cross-Lingual Retrieval Augmented Prompt for Low-Resource Languages

Auteurs: Ercong Nie, Sheng Liang, Helmut Schmid, Hinrich Schütze
Publié dans: Findings of the Association for Computational Linguistics: ACL 2023, Numéro July 2023, 2023
Éditeur: Association for Computational Linguistics

Discrete and Soft Prompting for Multilingual Models

Auteurs: Mengjie Zhao, Hinrich Schütze
Publié dans: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021
Éditeur: Association for Computational Linguistics
DOI: 10.18653/v1/2021.emnlp-main.672

A Survey of Corpora for Germanic Low-Resource Languages and Dialects

Auteurs: Verena Blaschke, Hinrich Schuetze, Barbara Plank
Publié dans: Proceedings of the 24th Nordic Conference on Computational Linguistics, Numéro May 2023, 2023
Éditeur: University of Tartu Library

Combining Word Embeddings with Bilingual Orthography Embeddings for Bilingual Dictionary Induction

Auteurs: Silvia Severini, Viktor Hangya, Alexander Fraser, Hinrich Schütze
Publié dans: Proceedings of the 28th International Conference on Computational Linguistics, Numéro December 2020, 2020
Éditeur: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.74087

DagoBERT: Generating Derivational Morphology with a Pretrained Language Model

Auteurs: Valentin Hofmann, Janet B. Pierrehumbert, Hinrich Schütze
Publié dans: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, Numéro 16. – 20. November, 2020
Éditeur: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.74031

Quantifying the Contextualization of Word Representations with Semantic Class Probing

Auteurs: Mengjie Zhao, Philipp Dufter, Yadollah Yaghoobzadeh, Hinrich Schütze
Publié dans: In: Findings of ACL: EMNLP 2020, 2020
Éditeur: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.74039

Graph Neural Networks for Multiparallel Word Alignment

Auteurs: Ayyoob Imani, Lütfi Kerem Senel, Masoud Jalili Sabet, François Yvon, Hinrich Schuetze
Publié dans: Findings of the Association for Computational Linguistics: ACL 2022, Numéro May 2022, 2022
Éditeur: Association for Computational Linguistics

Listening to Affected Communities to Define Extreme Speech: Dataset and Experiments

Auteurs: Antonis Maronikolakis, Axel Wisiorek, Leah Nann, Haris Jabbar, Sahana Udupa, Hinrich Schuetze
Publié dans: Findings of the Association for Computational Linguistics: ACL 2022, Numéro May 2022, 2022
Éditeur: Association for Computational Linguistics

Masking as an Efficient Alternative to Finetuning for Pretrained Language Models

Auteurs: Mengjie Zhao, Tao Lin, Fei Mi, Martin Jaggi, Hinrich Schütze
Publié dans: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, Numéro 16. – 20. November 2020, 2020
Éditeur: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.74038

Identifying Elements Essential for BERT’s Multilinguality

Auteurs: Philipp Dufter, Hinrich Schutze
Publié dans: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, Numéro 16th – 20th November 2020, 2020
Éditeur: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.74030

Position Information in Transformers: An Overview

Auteurs: Philipp Dufter, Martin Schmitt, Hinrich Schütze
Publié dans: Computational Linguistics, Numéro Volume 48, Numéro 3 - September 2022, 2022, ISSN 0891-2017
Éditeur: MIT Press

Attentive Convolution: Equipping CNNs with RNN-style Attention Mechanisms

Auteurs: Wenpeng Yin, Hinrich Schütze
Publié dans: Transactions of the Association for Computational Linguistics, Numéro 6, 2018, Page(s) 687-702, ISSN 2307-387X
Éditeur: MIT Press
DOI: 10.1162/tacl_a_00249

Corpus-Level Fine-Grained Entity Typing

Auteurs: Yadollah Yaghoobzadeh, Heike Adel, Hinrich Schuetze
Publié dans: Journal of Artificial Intelligence Research, Numéro 61, 2018, Page(s) 835-862, ISSN 1076-9757
Éditeur: Morgan Kaufmann Publishers, Inc.
DOI: 10.1613/jair.5601

SMAPH

Auteurs: Marco Cornolti, Paolo Ferragina, Massimiliano Ciaramita, Stefan Rüd, Hinrich Schütze
Publié dans: ACM Transactions on Information Systems, Numéro 37/1, 2019, Page(s) 1-42, ISSN 1046-8188
Éditeur: Association for Computing Machinary, Inc.
DOI: 10.1145/3284102

Placing language in an integrated understanding system: Next steps toward human-level performance in neural language models

Auteurs: James L. McClelland, Felix Hill, Maja Rudolph, Jason Baldridge, Hinrich Schütze
Publié dans: Proceedings of the National Academy of Sciences, Numéro 117/42, 2020, Page(s) 25966-25974, ISSN 0027-8424
Éditeur: National Academy of Sciences
DOI: 10.1073/pnas.1910416117

Type-aware Convolutional Neural Networks for Slot Filling

Auteurs: Heike Adel, Hinrich Schuetze
Publié dans: Journal of Artificial Intelligence Research, Numéro 66, 2019, Page(s) 297-339, ISSN 1076-9757
Éditeur: Morgan Kaufmann Publishers, Inc.
DOI: 10.1613/jair.1.11725

Self-Diagnosis and Self-Debiasing: A Proposal for Reducing Corpus-Based Bias in NLP

Auteurs: Timo Schick, Sahana Udupa, Hinrich Schütze
Publié dans: Transactions of the Association for Computational Linguistics, 2021, ISSN 2307-387X
Éditeur: Association for Computational Linguistics
DOI: 10.1162/tacl_a_00434

True Few-Shot Learning with Prompts—A Real-World Perspective

Auteurs: Timo Schick, Hinrich Schütze
Publié dans: Transactions of the Association for Computational Linguistics, Numéro Volume 10, 2022, ISSN 2307-387X
Éditeur: MIT Press

A Stronger Baseline for Multilingual Word Embeddings

Auteurs: Philipp Dufter, Hinrich Schütze
Publié dans: 2018
Éditeur: arXiv
DOI: 10.5282/ubm/epub.61864

Aligning Very Small Parallel Corpora Using Cross-Lingual Word Embeddings and a Monogamy Objective

Auteurs: Nina Poerner, Masoud Jalili Sabet, Benjamin Roth and Hinrich Schütze
Publié dans: 2018
Éditeur: arXiv
DOI: 10.5282/ubm/epub.61865

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