Non-sequence models for tokenization replacement

CORDIS fornisce collegamenti ai risultati finali pubblici e alle pubblicazioni dei progetti ORIZZONTE.

I link ai risultati e alle pubblicazioni dei progetti del 7° PQ, così come i link ad alcuni tipi di risultati specifici come dataset e software, sono recuperati dinamicamente da .OpenAIRE .

Risultati finali

Data Management Plan

Publish datasets and software produced in the project.

Pubblicazioni

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

Autori: Leonie Weissweiler, Valentin Hofmann, Abdullatif Köksal, Hinrich Schütze
Pubblicato in: Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, Numero December 2022, 2022
Editore: Association for Computational Linguistics

Modular and Parameter-Efficient Multimodal Fusion with Prompting

Autori: Sheng Liang, Mengjie Zhao, Hinrich Schuetze
Pubblicato in: Findings of the Association for Computational Linguistics: ACL 2022, Numero May 2022, 2022
Editore: Association for Computational Linguistics

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

Autori: Victor Steinborn, Philipp Dufter, Haris Jabbar, Hinrich Schütze
Pubblicato in: Findings of the Association for Computational Linguistics: NAACL 2022, Numero July 2022, 2022
Editore: Association for Computational Linguistics

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

Autori: Mengjie Zhao, Fei Mi, Yasheng Wang, Minglei Li, Xin Jiang, Qun Liu, Hinrich Schuetze
Pubblicato in: Findings of the Association for Computational Linguistics: NAACL 2022, Numero July 2022, 2022
Editore: Association for Computational Linguistics

A Crosslingual Investigation of Conceptualization in 1335 Languages

Autori: Yihong Liu, Haotian Ye, Leonie Weissweiler, Philipp Wicke, Renhao Pei, Robert Zangenfeind, Hinrich Schütze
Pubblicato in: Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics, Numero July 2023, 2023
Editore: Association for Computational Linguistics

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

Autori: Philipp Dufter, Martin Schmitt, Hinrich Schütze
Pubblicato in: Proceedings of the 28th International Conference on Computational Linguistics, Numero December 2020, 2020
Editore: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.74088

Glot500: Scaling Multilingual Corpora and Language Models to 500 Languages

Autori: Ayyoob ImaniGooghari, Peiqin Lin, Amir Hossein Kargaran, Silvia Severini, Masoud Jalili Sabet, Nora Kassner, Chunlan Ma, Helmut Schmid, André Martins, François Yvon, Hinrich Schütze
Pubblicato in: Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics, Numero July 2023, 2023
Editore: Association for Computational Linguistics

Graph Algorithms for Multiparallel Word Alignment

Autori: Ayyoob Imani, Masoud Jalili Sabet, Lutfi Kerem Senel, Philipp Dufter, François Yvon, Hinrich Schütze
Pubblicato in: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, Numero November 2021, 2021
Editore: 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

Autori: Mengjie Zhao, Yi Zhu, Ehsan Shareghi, Ivan Vulić, Roi Reichart, Anna Korhonen, Hinrich Schütze
Pubblicato in: 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), Numero August 2021, 2021
Editore: 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

Autori: Verena Blaschke, Hinrich Schütze, Barbara Plank
Pubblicato in: Tenth Workshop on NLP for Similar Languages, Varieties and Dialects, Numero May 2023, 2023
Editore: Association for Computational Linguistics

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

Autori: Ayyoob ImaniGooghari, Silvia Severini, Masoud Jalili Sabet, François Yvon, Hinrich Schütze
Pubblicato in: Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, Numero December 2022, 2022
Editore: Association for Computational Linguistics

Monolingual and Multilingual Reduction of Gender Bias in Contextualized Representations

Autori: Sheng Liang, Philipp Dufter, Hinrich Schütze
Pubblicato in: Proceedings of the 28th International Conference on Computational Linguistics, Numero December 2020, 2020
Editore: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.74040

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

Autori: Timo Schick, Helmut Schmid, Hinrich Schütze
Pubblicato in: Proceedings of the 28th International Conference on Computational Linguistics, Numero 8. - 11. December 2020, 2020
Editore: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.74034

Flow-Adapter Architecture for Unsupervised Machine Translation

Autori: Yihong Liu, Haris Jabbar, Hinrich Schuetze
Pubblicato in: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Numero May 2022, 2022
Editore: Association for Computational Linguistics

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

Autori: Timo Schick, Hinrich Schütze
Pubblicato in: Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, Numero April 2021, 2021
Editore: Association for Computational Linguistics
DOI: 10.18653/v1/2021.eacl-main.20

CaMEL: Case Marker Extraction without Labels

Autori: Leonie Weissweiler, Valentin Hofmann, Masoud Jalili Sabet, Hinrich Schuetze
Pubblicato in: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Numero May 2022, 2022
Editore: Association for Computational Linguistics

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

Autori: Valentin Hofmann, Janet Pierrehumbert, Hinrich Schütze
Pubblicato in: 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), Numero August 2021, 2021
Editore: 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

Autori: Yihong Liu, Alexandra Chronopoulou, Hinrich Schütze, Alexander Fraser
Pubblicato in: Proceedings of the 20th International Conference on Spoken Language Translation, Numero July 2023, 2023
Editore: Association for Computational Linguistics

Generating Datasets with Pretrained Language Models

Autori: Timo Schick, Hinrich Schütze
Pubblicato in: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, Numero November 2021, 2021
Editore: Association for Computational Linguistics
DOI: 10.18653/v1/2021.emnlp-main.555

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

Autori: Junze Li, Mengjie Zhao, Yubo Xie, Antonis Maronikolakis, Pearl Pu, Hinrich Schuetze
Pubblicato in: Proceedings of The 1st Transfer Learning for Natural Language Processing Workshop, Numero December 2022, 2022
Editore: Proceedings of Machine Learning Research

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

Autori: Timo Schick, Hinrich Schütze
Pubblicato in: Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Numero June 2021, 2021
Editore: 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

Autori: Valentin Hofmann, Hinrich Schütze, Janet B. Pierrehumbert
Pubblicato in: Proceedings of the International AAAI Conference on Web and Social Media, Numero May 2022, 2022
Editore: AAAI

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

Autori: Silvia Severini, Ayyoob ImaniGooghari, Philipp Dufter, Hinrich Schütze
Pubblicato in: Proceedings of the Thirteenth Language Resources and Evaluation Conference, Numero June 2022, 2022
Editore: European Language Resources Association

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

Autori: Valentin Hofmann, Hinrich Schuetze, Janet Pierrehumbert
Pubblicato in: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), Numero May 2022, 2022
Editore: Association for Computational Linguistics

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

Autori: Valentin Hofmann, Xiaowen Dong, Janet Pierrehumbert, Hinrich Schuetze
Pubblicato in: Findings of the Association for Computational Linguistics: NAACL 2022, Numero July 2022, 2022
Editore: Association for Computational Linguistics

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

Autori: Antonis Maronikolakis, Philipp Dufter, Hinrich Schütze
Pubblicato in: Findings of the Association for Computational Linguistics: EMNLP 2021, Numero November 2021, 2021
Editore: Association for Computational Linguistics
DOI: 10.18653/v1/2021.findings-emnlp.205

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

Autori: Lütfi Kerem Senel, Timo Schick, Hinrich Schuetze
Pubblicato in: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), Numero May 2022, 2022
Editore: Association for Computational Linguistics

Unsupervised Detection of Contextualized Embedding Bias with Application to Ideology

Autori: Valentin Hofmann, Janet Pierrehumbert, Hinrich Schütze
Pubblicato in: Proceedings of the 39th International Conference on Machine Learning, Numero July 2022, 2022
Editore: Proceedings of Machine Learning Research

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

Autori: Yadollah Yaghoobzadeh, Hinrich Schütze
Pubblicato in: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Numero 31. October - 04. November 2018, 2018, Pagina/e 3060-3066, ISBN 978-1-948087-84-1
Editore: 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

Autori: Martin Schmitt, Simon Steinheber, Konrad Schreiber, Benjamin Roth
Pubblicato in: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Numero 31. October - 02. November 2018, 2018, Pagina/e pp. 1109-1114, ISBN 978-1-948087-84-1
Editore: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.61858

Embedding Learning Through Multilingual Concept Induction

Autori: Philipp Dufter, Mengjie Zhao, Martin Schmitt, Alexander Fraser, Hinrich Schütze
Pubblicato in: Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, Numero July 15-20, 2018, 2018, Pagina/e 1520–1530, ISBN 978-1-948087-32-2
Editore: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.61841

Recurrent One-Hop Predictions for Reasoning over Knowledge Graphs

Autori: Wenpeng Yin, Yadollah Yaghoobzadeh, Hinrich Schütze
Pubblicato in: Proceedings of the 27th International Conference on Computational Linguistics, Numero August 20-26, 2018, Pagina/e 2369–2378, ISBN 978-1-948087-50-6
Editore: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.61860

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

Autori: Katharina Kann, Hinrich Schütze
Pubblicato in: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Numero October 31 - November 4, 2018, 2018, Pagina/e 3254–3264, ISBN 978-1-948087-84-1
Editore: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.61867

Evaluating neural network explanation methods using hybrid documents and morphosyntactic agreement

Autori: Nina Poerner, Benjamin Roth, Hinrich Schütze
Pubblicato in: Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, Numero July 15 - 20, 2018, 2018, Pagina/e pages 340–350, ISBN 978-1-948087-32-2
Editore: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.61866

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

Autori: Yadollah Yaghoobzadeh, Katharina Kann, T. J. Hazen, Eneko Agirre, Hinrich Schütze
Pubblicato in: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, 2019, Pagina/e 5740-5753
Editore: Association for Computational Linguistics
DOI: 10.18653/v1/p19-1574

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

Autori: Masoud Jalili Sabet,Philipp Dufter,Hinrich Schütze
Pubblicato in: In: Findings of ACL: EMNLP 2020, 2020
Editore: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.72200

Automatic Domain Adaptation Outperforms Manual Domain Adaptation for Predicting Financial Outcomes

Autori: Marina Sedinkina, Nikolas Breitkopf, Hinrich Schütze
Pubblicato in: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, 2019, Pagina/e 346-359
Editore: Association for Computational Linguistics
DOI: 10.18653/v1/p19-1034

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

Autori: Timo Schick,Hinrich Schütze
Pubblicato in: Proceedings of the 58th Conference of the Association for Computational Linguistics, ACL 2020, Seattle, USA, July 5 - July 10, 2020, 2020
Editore: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.72196

A Graph Auto-encoder Model of Derivational Morphology

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

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

Autori: Nora Kassner, Hinrich Schütze
Pubblicato in: Proceedings of the 58th Conference of the Association for Computational Linguistics, ACL 2020, Seattle, USA, July 5 - July 10, 2020, 2020
Editore: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.72195

Sentence Meta-Embeddings for Unsupervised Semantic Textual Similarity

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

Analytical Methods for Interpretable Ultradense Word Embeddings

Autori: Philipp Dufter, Hinrich Schütze
Pubblicato in: 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, Pagina/e 1185-1191
Editore: Association for Computational Linguistics
DOI: 10.18653/v1/d19-1111

Predicting the Growth of Morphological Families from Social and Linguistic Factors

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

A Multilingual BPE Embedding Space for Universal Sentiment Lexicon Induction

Autori: Mengjie Zhao, Hinrich Schütze
Pubblicato in: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, 2019, Pagina/e 3506-3517
Editore: Association for Computational Linguistics
DOI: 10.18653/v1/p19-1341

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

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

Attentive Mimicking: Better Word Embeddings by Attending to Informative Contexts

Autori: Timo Schick, Hinrich Schütze
Pubblicato in: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2019, 2019
Editore: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.61844

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

Autori: Timo Schick, Hinrich Schütze
Pubblicato in: The Thirty-Third AAAI Conference on Artificial Intelligence, AAAI 2019, The Thirty-First Innovative Applications of Artificial Intelligence Conference, 2019
Editore: 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

Autori: Timo Schick, Hinrich Schütze
Pubblicato in: 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
Editore: 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

Autori: Yongkang Liu, Shi Feng, Daling Wang, Yifei Zhang, Hinrich Schütze
Pubblicato in: Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics, Numero July 2023, 2023
Editore: Association for Computational Linguistics

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

Autori: Nora Kassner, Oyvind Tafjord, Hinrich Schütze, Peter Clark
Pubblicato in: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, Numero November 2021, 2021
Editore: 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

Autori: Lutfi Kerem Senel, Hinrich Schütze
Pubblicato in: Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, Numero April 2021, 2021
Editore: 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

Autori: Nora Kassner, Philipp Dufter, Hinrich Schütze
Pubblicato in: Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, Numero April 2021, 2021
Editore: Association for Computational Linguistics
DOI: 10.18653/v1/2021.eacl-main.284

Static Embeddings as Efficient Knowledge Bases?

Autori: Philipp Dufter, Nora Kassner, Hinrich Schütze
Pubblicato in: Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Numero June 2021, 2021
Editore: Association for Computational Linguistics
DOI: 10.18653/v1/2021.naacl-main.186

Cross-Lingual Retrieval Augmented Prompt for Low-Resource Languages

Autori: Ercong Nie, Sheng Liang, Helmut Schmid, Hinrich Schütze
Pubblicato in: Findings of the Association for Computational Linguistics: ACL 2023, Numero July 2023, 2023
Editore: Association for Computational Linguistics

Discrete and Soft Prompting for Multilingual Models

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

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

Autori: Verena Blaschke, Hinrich Schuetze, Barbara Plank
Pubblicato in: Proceedings of the 24th Nordic Conference on Computational Linguistics, Numero May 2023, 2023
Editore: University of Tartu Library

Combining Word Embeddings with Bilingual Orthography Embeddings for Bilingual Dictionary Induction

Autori: Silvia Severini, Viktor Hangya, Alexander Fraser, Hinrich Schütze
Pubblicato in: Proceedings of the 28th International Conference on Computational Linguistics, Numero December 2020, 2020
Editore: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.74087

DagoBERT: Generating Derivational Morphology with a Pretrained Language Model

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

Quantifying the Contextualization of Word Representations with Semantic Class Probing

Autori: Mengjie Zhao, Philipp Dufter, Yadollah Yaghoobzadeh, Hinrich Schütze
Pubblicato in: In: Findings of ACL: EMNLP 2020, 2020
Editore: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.74039

Graph Neural Networks for Multiparallel Word Alignment

Autori: Ayyoob Imani, Lütfi Kerem Senel, Masoud Jalili Sabet, François Yvon, Hinrich Schuetze
Pubblicato in: Findings of the Association for Computational Linguistics: ACL 2022, Numero May 2022, 2022
Editore: Association for Computational Linguistics

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

Autori: Antonis Maronikolakis, Axel Wisiorek, Leah Nann, Haris Jabbar, Sahana Udupa, Hinrich Schuetze
Pubblicato in: Findings of the Association for Computational Linguistics: ACL 2022, Numero May 2022, 2022
Editore: Association for Computational Linguistics

Masking as an Efficient Alternative to Finetuning for Pretrained Language Models

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

Identifying Elements Essential for BERT’s Multilinguality

Autori: Philipp Dufter, Hinrich Schutze
Pubblicato in: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, Numero 16th – 20th November 2020, 2020
Editore: Association for Computational Linguistics
DOI: 10.5282/ubm/epub.74030

Position Information in Transformers: An Overview

Autori: Philipp Dufter, Martin Schmitt, Hinrich Schütze
Pubblicato in: Computational Linguistics, Numero Volume 48, Numero 3 - September 2022, 2022, ISSN 0891-2017
Editore: MIT Press

Attentive Convolution: Equipping CNNs with RNN-style Attention Mechanisms

Autori: Wenpeng Yin, Hinrich Schütze
Pubblicato in: Transactions of the Association for Computational Linguistics, Numero 6, 2018, Pagina/e 687-702, ISSN 2307-387X
Editore: MIT Press
DOI: 10.1162/tacl_a_00249

Corpus-Level Fine-Grained Entity Typing

Autori: Yadollah Yaghoobzadeh, Heike Adel, Hinrich Schuetze
Pubblicato in: Journal of Artificial Intelligence Research, Numero 61, 2018, Pagina/e 835-862, ISSN 1076-9757
Editore: Morgan Kaufmann Publishers, Inc.
DOI: 10.1613/jair.5601

SMAPH

Autori: Marco Cornolti, Paolo Ferragina, Massimiliano Ciaramita, Stefan Rüd, Hinrich Schütze
Pubblicato in: ACM Transactions on Information Systems, Numero 37/1, 2019, Pagina/e 1-42, ISSN 1046-8188
Editore: 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

Autori: James L. McClelland, Felix Hill, Maja Rudolph, Jason Baldridge, Hinrich Schütze
Pubblicato in: Proceedings of the National Academy of Sciences, Numero 117/42, 2020, Pagina/e 25966-25974, ISSN 0027-8424
Editore: National Academy of Sciences
DOI: 10.1073/pnas.1910416117

Type-aware Convolutional Neural Networks for Slot Filling

Autori: Heike Adel, Hinrich Schuetze
Pubblicato in: Journal of Artificial Intelligence Research, Numero 66, 2019, Pagina/e 297-339, ISSN 1076-9757
Editore: Morgan Kaufmann Publishers, Inc.
DOI: 10.1613/jair.1.11725

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

Autori: Timo Schick, Sahana Udupa, Hinrich Schütze
Pubblicato in: Transactions of the Association for Computational Linguistics, 2021, ISSN 2307-387X
Editore: Association for Computational Linguistics
DOI: 10.1162/tacl_a_00434

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

Autori: Timo Schick, Hinrich Schütze
Pubblicato in: Transactions of the Association for Computational Linguistics, Numero Volume 10, 2022, ISSN 2307-387X
Editore: MIT Press

A Stronger Baseline for Multilingual Word Embeddings

Autori: Philipp Dufter, Hinrich Schütze
Pubblicato in: 2018
Editore: arXiv
DOI: 10.5282/ubm/epub.61864

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

Autori: Nina Poerner, Masoud Jalili Sabet, Benjamin Roth and Hinrich Schütze
Pubblicato in: 2018
Editore: arXiv
DOI: 10.5282/ubm/epub.61865

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