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CORDIS - Resultados de investigaciones de la UE
CORDIS

Non-sequence models for tokenization replacement

CORDIS proporciona enlaces a los documentos públicos y las publicaciones de los proyectos de los programas marco HORIZONTE.

Los enlaces a los documentos y las publicaciones de los proyectos del Séptimo Programa Marco, así como los enlaces a algunos tipos de resultados específicos, como conjuntos de datos y «software», se obtienen dinámicamente de OpenAIRE .

Resultado final

Publicaciones

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

Autores: Leonie Weissweiler, Valentin Hofmann, Abdullatif Köksal, Hinrich Schütze
Publicado en: Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, Edición December 2022, 2022
Editor: Association for Computational Linguistics

Modular and Parameter-Efficient Multimodal Fusion with Prompting

Autores: Sheng Liang, Mengjie Zhao, Hinrich Schuetze
Publicado en: Findings of the Association for Computational Linguistics: ACL 2022, Edición May 2022, 2022
Editor: Association for Computational Linguistics

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

Autores: Victor Steinborn, Philipp Dufter, Haris Jabbar, Hinrich Schütze
Publicado en: Findings of the Association for Computational Linguistics: NAACL 2022, Edición July 2022, 2022
Editor: Association for Computational Linguistics

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

Autores: Mengjie Zhao, Fei Mi, Yasheng Wang, Minglei Li, Xin Jiang, Qun Liu, Hinrich Schuetze
Publicado en: Findings of the Association for Computational Linguistics: NAACL 2022, Edición July 2022, 2022
Editor: Association for Computational Linguistics

A Crosslingual Investigation of Conceptualization in 1335 Languages

Autores: Yihong Liu, Haotian Ye, Leonie Weissweiler, Philipp Wicke, Renhao Pei, Robert Zangenfeind, Hinrich Schütze
Publicado en: Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics, Edición July 2023, 2023
Editor: Association for Computational Linguistics

Increasing Learning Efficiency of Self-Attention Networks throughDirect Position Interactions, Learnable Temperature,and Convoluted Attention (se abrirá en una nueva ventana)

Autores: Philipp Dufter, Martin Schmitt, Hinrich Schütze
Publicado en: Proceedings of the 28th International Conference on Computational Linguistics, Edición December 2020, 2020
Editor: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.74088

Glot500: Scaling Multilingual Corpora and Language Models to 500 Languages

Autores: Ayyoob ImaniGooghari, Peiqin Lin, Amir Hossein Kargaran, Silvia Severini, Masoud Jalili Sabet, Nora Kassner, Chunlan Ma, Helmut Schmid, André Martins, François Yvon, Hinrich Schütze
Publicado en: Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics, Edición July 2023, 2023
Editor: Association for Computational Linguistics

Graph Algorithms for Multiparallel Word Alignment (se abrirá en una nueva ventana)

Autores: Ayyoob Imani, Masoud Jalili Sabet, Lutfi Kerem Senel, Philipp Dufter, François Yvon, Hinrich Schütze
Publicado en: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, Edición November 2021, 2021
Editor: 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 (se abrirá en una nueva ventana)

Autores: Mengjie Zhao, Yi Zhu, Ehsan Shareghi, Ivan Vulić, Roi Reichart, Anna Korhonen, Hinrich Schütze
Publicado en: 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), Edición August 2021, 2021
Editor: 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

Autores: Verena Blaschke, Hinrich Schütze, Barbara Plank
Publicado en: Tenth Workshop on NLP for Similar Languages, Varieties and Dialects, Edición May 2023, 2023
Editor: Association for Computational Linguistics

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

Autores: Ayyoob ImaniGooghari, Silvia Severini, Masoud Jalili Sabet, François Yvon, Hinrich Schütze
Publicado en: Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, Edición December 2022, 2022
Editor: Association for Computational Linguistics

Monolingual and Multilingual Reduction of Gender Bias in Contextualized Representations (se abrirá en una nueva ventana)

Autores: Sheng Liang, Philipp Dufter, Hinrich Schütze
Publicado en: Proceedings of the 28th International Conference on Computational Linguistics, Edición December 2020, 2020
Editor: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.74040

Automatically Identifying Words That Can Serve as Labels for Few-ShotText Classification (se abrirá en una nueva ventana)

Autores: Timo Schick, Helmut Schmid, Hinrich Schütze
Publicado en: Proceedings of the 28th International Conference on Computational Linguistics, Edición 8. - 11. December 2020, 2020
Editor: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.74034

Flow-Adapter Architecture for Unsupervised Machine Translation

Autores: Yihong Liu, Haris Jabbar, Hinrich Schuetze
Publicado en: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Edición May 2022, 2022
Editor: Association for Computational Linguistics

Exploiting Cloze-Questions for Few-Shot Text Classification and Natural Language Inference (se abrirá en una nueva ventana)

Autores: Timo Schick, Hinrich Schütze
Publicado en: Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, Edición April 2021, 2021
Editor: Association for Computational Linguistics
DOI: 10.18653/v1/2021.eacl-main.20

CaMEL: Case Marker Extraction without Labels

Autores: Leonie Weissweiler, Valentin Hofmann, Masoud Jalili Sabet, Hinrich Schuetze
Publicado en: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Edición May 2022, 2022
Editor: Association for Computational Linguistics

Superbizarre Is Not Superb: Derivational Morphology Improves BERT’s Interpretation of Complex Words (se abrirá en una nueva ventana)

Autores: Valentin Hofmann, Janet Pierrehumbert, Hinrich Schütze
Publicado en: 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), Edición August 2021, 2021
Editor: 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

Autores: Yihong Liu, Alexandra Chronopoulou, Hinrich Schütze, Alexander Fraser
Publicado en: Proceedings of the 20th International Conference on Spoken Language Translation, Edición July 2023, 2023
Editor: Association for Computational Linguistics

Generating Datasets with Pretrained Language Models (se abrirá en una nueva ventana)

Autores: Timo Schick, Hinrich Schütze
Publicado en: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, Edición November 2021, 2021
Editor: Association for Computational Linguistics
DOI: 10.18653/v1/2021.emnlp-main.555

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

Autores: Junze Li, Mengjie Zhao, Yubo Xie, Antonis Maronikolakis, Pearl Pu, Hinrich Schuetze
Publicado en: Proceedings of The 1st Transfer Learning for Natural Language Processing Workshop, Edición December 2022, 2022
Editor: Proceedings of Machine Learning Research

It’s Not Just Size That Matters: Small Language Models Are Also Few-Shot Learners (se abrirá en una nueva ventana)

Autores: Timo Schick, Hinrich Schütze
Publicado en: Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Edición June 2021, 2021
Editor: 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

Autores: Valentin Hofmann, Hinrich Schütze, Janet B. Pierrehumbert
Publicado en: Proceedings of the International AAAI Conference on Web and Social Media, Edición May 2022, 2022
Editor: AAAI

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

Autores: Silvia Severini, Ayyoob ImaniGooghari, Philipp Dufter, Hinrich Schütze
Publicado en: Proceedings of the Thirteenth Language Resources and Evaluation Conference, Edición June 2022, 2022
Editor: European Language Resources Association

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

Autores: Valentin Hofmann, Hinrich Schuetze, Janet Pierrehumbert
Publicado en: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), Edición May 2022, 2022
Editor: Association for Computational Linguistics

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

Autores: Valentin Hofmann, Xiaowen Dong, Janet Pierrehumbert, Hinrich Schuetze
Publicado en: Findings of the Association for Computational Linguistics: NAACL 2022, Edición July 2022, 2022
Editor: Association for Computational Linguistics

Wine is not v i n. On the Compatibility of Tokenizations across Languages (se abrirá en una nueva ventana)

Autores: Antonis Maronikolakis, Philipp Dufter, Hinrich Schütze
Publicado en: Findings of the Association for Computational Linguistics: EMNLP 2021, Edición November 2021, 2021
Editor: Association for Computational Linguistics
DOI: 10.18653/v1/2021.findings-emnlp.205

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

Autores: Lütfi Kerem Senel, Timo Schick, Hinrich Schuetze
Publicado en: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), Edición May 2022, 2022
Editor: Association for Computational Linguistics

Unsupervised Detection of Contextualized Embedding Bias with Application to Ideology

Autores: Valentin Hofmann, Janet Pierrehumbert, Hinrich Schütze
Publicado en: Proceedings of the 39th International Conference on Machine Learning, Edición July 2022, 2022
Editor: Proceedings of Machine Learning Research

Multi-Multi-View Learning: Multilingual and Multi-Representation Entity Typing (se abrirá en una nueva ventana)

Autores: Yadollah Yaghoobzadeh, Hinrich Schütze
Publicado en: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Edición 31. October - 04. November 2018, 2018, Página(s) 3060-3066, ISBN 978-1-948087-84-1
Editor: 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 (se abrirá en una nueva ventana)

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

Embedding Learning Through Multilingual Concept Induction (se abrirá en una nueva ventana)

Autores: Philipp Dufter, Mengjie Zhao, Martin Schmitt, Alexander Fraser, Hinrich Schütze
Publicado en: Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, Edición July 15-20, 2018, 2018, Página(s) 1520–1530, ISBN 978-1-948087-32-2
Editor: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.61841

Recurrent One-Hop Predictions for Reasoning over Knowledge Graphs (se abrirá en una nueva ventana)

Autores: Wenpeng Yin, Yadollah Yaghoobzadeh, Hinrich Schütze
Publicado en: Proceedings of the 27th International Conference on Computational Linguistics, Edición August 20-26, 2018, Página(s) 2369–2378, ISBN 978-1-948087-50-6
Editor: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.61860

Neural Transductive Learning and Beyond: Morphological Generation in the Minimal-Resource Setting (se abrirá en una nueva ventana)

Autores: Katharina Kann, Hinrich Schütze
Publicado en: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Edición October 31 - November 4, 2018, 2018, Página(s) 3254–3264, ISBN 978-1-948087-84-1
Editor: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.61867

Evaluating neural network explanation methods using hybrid documents and morphosyntactic agreement (se abrirá en una nueva ventana)

Autores: Nina Poerner, Benjamin Roth, Hinrich Schütze
Publicado en: Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, Edición July 15 - 20, 2018, 2018, Página(s) pages 340–350, ISBN 978-1-948087-32-2
Editor: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.61866

Probing for Semantic Classes: Diagnosing the Meaning Content of Word Embeddings (se abrirá en una nueva ventana)

Autores: Yadollah Yaghoobzadeh, Katharina Kann, T. J. Hazen, Eneko Agirre, Hinrich Schütze
Publicado en: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, 2019, Página(s) 5740-5753
Editor: Association for Computational Linguistics
DOI: 10.18653/v1/p19-1574

SimAlign: High Quality Word Alignments without Parallel Training Data using Static and Contextualized Embeddings. (se abrirá en una nueva ventana)

Autores: Masoud Jalili Sabet,Philipp Dufter,Hinrich Schütze
Publicado en: In: Findings of ACL: EMNLP 2020, 2020
Editor: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.72200

Automatic Domain Adaptation Outperforms Manual Domain Adaptation for Predicting Financial Outcomes (se abrirá en una nueva ventana)

Autores: Marina Sedinkina, Nikolas Breitkopf, Hinrich Schütze
Publicado en: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, 2019, Página(s) 346-359
Editor: Association for Computational Linguistics
DOI: 10.18653/v1/p19-1034

BERTRAM: Improved Word Embeddings Have Big Impact on Contextualized Model Performance (se abrirá en una nueva ventana)

Autores: Timo Schick,Hinrich Schütze
Publicado en: Proceedings of the 58th Conference of the Association for Computational Linguistics, ACL 2020, Seattle, USA, July 5 - July 10, 2020, 2020
Editor: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.72196

A Graph Auto-encoder Model of Derivational Morphology (se abrirá en una nueva ventana)

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

Negated and Misprimed Probes for Pretrained Language Models: Birds Can Talk, But Cannot Fly (se abrirá en una nueva ventana)

Autores: Nora Kassner, Hinrich Schütze
Publicado en: Proceedings of the 58th Conference of the Association for Computational Linguistics, ACL 2020, Seattle, USA, July 5 - July 10, 2020, 2020
Editor: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.72195

Sentence Meta-Embeddings for Unsupervised Semantic Textual Similarity (se abrirá en una nueva ventana)

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

Analytical Methods for Interpretable Ultradense Word Embeddings (se abrirá en una nueva ventana)

Autores: Philipp Dufter, Hinrich Schütze
Publicado en: 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, Página(s) 1185-1191
Editor: Association for Computational Linguistics
DOI: 10.18653/v1/d19-1111

Predicting the Growth of Morphological Families from Social and Linguistic Factors (se abrirá en una nueva ventana)

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

A Multilingual BPE Embedding Space for Universal Sentiment Lexicon Induction (se abrirá en una nueva ventana)

Autores: Mengjie Zhao, Hinrich Schütze
Publicado en: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, 2019, Página(s) 3506-3517
Editor: Association for Computational Linguistics
DOI: 10.18653/v1/p19-1341

Neural Semi-Markov Conditional Random Fields for Robust Character-Based Part-of-Speech Tagging (se abrirá en una nueva ventana)

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

Attentive Mimicking: Better Word Embeddings by Attending to Informative Contexts (se abrirá en una nueva ventana)

Autores: Timo Schick, Hinrich Schütze
Publicado en: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2019, 2019
Editor: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.61844

Learning Semantic Representations for Novel Words: Leveraging Both Form and Context (se abrirá en una nueva ventana)

Autores: Timo Schick, Hinrich Schütze
Publicado en: The Thirty-Third AAAI Conference on Artificial Intelligence, AAAI 2019, The Thirty-First Innovative Applications of Artificial Intelligence Conference, 2019
Editor: 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 (se abrirá en una nueva ventana)

Autores: Timo Schick, Hinrich Schütze
Publicado en: 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
Editor: Association for the Advancement of Artificial Intelligence
DOI: 10.5282/ubm/epub.61863

Few-Shot Text Generation with Natural Language Instructions (se abrirá en una nueva ventana)

Autores: Timo Schick, Hinrich Schütze
Publicado en: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, Edición November 2021, 2021
Editor: Association for Computational Linguistics
DOI: 10.18653/v1/2021.emnlp-main.32

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

Autores: Yongkang Liu, Shi Feng, Daling Wang, Yifei Zhang, Hinrich Schütze
Publicado en: Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics, Edición July 2023, 2023
Editor: Association for Computational Linguistics

BeliefBank: Adding Memory to a Pre-Trained Language Model for a Systematic Notion of Belief (se abrirá en una nueva ventana)

Autores: Nora Kassner, Oyvind Tafjord, Hinrich Schütze, Peter Clark
Publicado en: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, Edición November 2021, 2021
Editor: 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 (se abrirá en una nueva ventana)

Autores: Lutfi Kerem Senel, Hinrich Schütze
Publicado en: Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, Edición April 2021, 2021
Editor: Association for Computational Linguistics
DOI: 10.18653/v1/2021.eacl-main.42

Dynamic Contextualized Word Embeddings (se abrirá en una nueva ventana)

Autores: Valentin Hofmann, Janet Pierrehumbert, Hinrich Schütze
Publicado en: 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), Edición August 2021, 2021
Editor: Association for Computational Linguistics
DOI: 10.18653/v1/2021.acl-long.542

Multilingual LAMA: Investigating Knowledge in Multilingual Pretrained Language Models (se abrirá en una nueva ventana)

Autores: Nora Kassner, Philipp Dufter, Hinrich Schütze
Publicado en: Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, Edición April 2021, 2021
Editor: Association for Computational Linguistics
DOI: 10.18653/v1/2021.eacl-main.284

Static Embeddings as Efficient Knowledge Bases? (se abrirá en una nueva ventana)

Autores: Philipp Dufter, Nora Kassner, Hinrich Schütze
Publicado en: Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Edición June 2021, 2021
Editor: Association for Computational Linguistics
DOI: 10.18653/v1/2021.naacl-main.186

Cross-Lingual Retrieval Augmented Prompt for Low-Resource Languages

Autores: Ercong Nie, Sheng Liang, Helmut Schmid, Hinrich Schütze
Publicado en: Findings of the Association for Computational Linguistics: ACL 2023, Edición July 2023, 2023
Editor: Association for Computational Linguistics

Discrete and Soft Prompting for Multilingual Models (se abrirá en una nueva ventana)

Autores: Mengjie Zhao, Hinrich Schütze
Publicado en: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021
Editor: Association for Computational Linguistics
DOI: 10.18653/v1/2021.emnlp-main.672

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

Autores: Verena Blaschke, Hinrich Schuetze, Barbara Plank
Publicado en: Proceedings of the 24th Nordic Conference on Computational Linguistics, Edición May 2023, 2023
Editor: University of Tartu Library

Combining Word Embeddings with Bilingual Orthography Embeddings for Bilingual Dictionary Induction (se abrirá en una nueva ventana)

Autores: Silvia Severini, Viktor Hangya, Alexander Fraser, Hinrich Schütze
Publicado en: Proceedings of the 28th International Conference on Computational Linguistics, Edición December 2020, 2020
Editor: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.74087

DagoBERT: Generating Derivational Morphology with a Pretrained Language Model (se abrirá en una nueva ventana)

Autores: Valentin Hofmann, Janet B. Pierrehumbert, Hinrich Schütze
Publicado en: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, Edición 16. – 20. November, 2020
Editor: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.74031

Quantifying the Contextualization of Word Representations with Semantic Class Probing (se abrirá en una nueva ventana)

Autores: Mengjie Zhao, Philipp Dufter, Yadollah Yaghoobzadeh, Hinrich Schütze
Publicado en: In: Findings of ACL: EMNLP 2020, 2020
Editor: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.74039

Graph Neural Networks for Multiparallel Word Alignment

Autores: Ayyoob Imani, Lütfi Kerem Senel, Masoud Jalili Sabet, François Yvon, Hinrich Schuetze
Publicado en: Findings of the Association for Computational Linguistics: ACL 2022, Edición May 2022, 2022
Editor: Association for Computational Linguistics

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

Autores: Antonis Maronikolakis, Axel Wisiorek, Leah Nann, Haris Jabbar, Sahana Udupa, Hinrich Schuetze
Publicado en: Findings of the Association for Computational Linguistics: ACL 2022, Edición May 2022, 2022
Editor: Association for Computational Linguistics

Masking as an Efficient Alternative to Finetuning for Pretrained Language Models (se abrirá en una nueva ventana)

Autores: Mengjie Zhao, Tao Lin, Fei Mi, Martin Jaggi, Hinrich Schütze
Publicado en: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, Edición 16. – 20. November 2020, 2020
Editor: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.74038

Identifying Elements Essential for BERT’s Multilinguality (se abrirá en una nueva ventana)

Autores: Philipp Dufter, Hinrich Schutze
Publicado en: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, Edición 16th – 20th November 2020, 2020
Editor: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.74030

Position Information in Transformers: An Overview

Autores: Philipp Dufter, Martin Schmitt, Hinrich Schütze
Publicado en: Computational Linguistics, Edición Volume 48, Edición 3 - September 2022, 2022, ISSN 0891-2017
Editor: MIT Press

Attentive Convolution: Equipping CNNs with RNN-style Attention Mechanisms (se abrirá en una nueva ventana)

Autores: Wenpeng Yin, Hinrich Schütze
Publicado en: Transactions of the Association for Computational Linguistics, Edición 6, 2018, Página(s) 687-702, ISSN 2307-387X
Editor: MIT Press
DOI: 10.1162/tacl_a_00249

Corpus-Level Fine-Grained Entity Typing (se abrirá en una nueva ventana)

Autores: Yadollah Yaghoobzadeh, Heike Adel, Hinrich Schuetze
Publicado en: Journal of Artificial Intelligence Research, Edición 61, 2018, Página(s) 835-862, ISSN 1076-9757
Editor: Morgan Kaufmann Publishers, Inc.
DOI: 10.1613/jair.5601

SMAPH (se abrirá en una nueva ventana)

Autores: Marco Cornolti, Paolo Ferragina, Massimiliano Ciaramita, Stefan Rüd, Hinrich Schütze
Publicado en: ACM Transactions on Information Systems, Edición 37/1, 2019, Página(s) 1-42, ISSN 1046-8188
Editor: 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 (se abrirá en una nueva ventana)

Autores: James L. McClelland, Felix Hill, Maja Rudolph, Jason Baldridge, Hinrich Schütze
Publicado en: Proceedings of the National Academy of Sciences, Edición 117/42, 2020, Página(s) 25966-25974, ISSN 0027-8424
Editor: National Academy of Sciences
DOI: 10.1073/pnas.1910416117

Type-aware Convolutional Neural Networks for Slot Filling (se abrirá en una nueva ventana)

Autores: Heike Adel, Hinrich Schuetze
Publicado en: Journal of Artificial Intelligence Research, Edición 66, 2019, Página(s) 297-339, ISSN 1076-9757
Editor: Morgan Kaufmann Publishers, Inc.
DOI: 10.1613/jair.1.11725

Self-Diagnosis and Self-Debiasing: A Proposal for Reducing Corpus-Based Bias in NLP (se abrirá en una nueva ventana)

Autores: Timo Schick, Sahana Udupa, Hinrich Schütze
Publicado en: Transactions of the Association for Computational Linguistics, 2021, ISSN 2307-387X
Editor: Association for Computational Linguistics
DOI: 10.1162/tacl_a_00434

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

Autores: Timo Schick, Hinrich Schütze
Publicado en: Transactions of the Association for Computational Linguistics, Edición Volume 10, 2022, ISSN 2307-387X
Editor: MIT Press

A Stronger Baseline for Multilingual Word Embeddings (se abrirá en una nueva ventana)

Autores: Philipp Dufter, Hinrich Schütze
Publicado en: 2018
Editor: arXiv
DOI: 10.5282/ubm/epub.61864

Aligning Very Small Parallel Corpora Using Cross-Lingual Word Embeddings and a Monogamy Objective (se abrirá en una nueva ventana)

Autores: Nina Poerner, Masoud Jalili Sabet, Benjamin Roth and Hinrich Schütze
Publicado en: 2018
Editor: arXiv
DOI: 10.5282/ubm/epub.61865

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