b'Heike Adel'

research

∙ 05/04/2023

Neighboring Words Affect Human Interpretation of Saliency Explanations

Word-level saliency explanations ("heat maps over words") are often used...

0 Alon Jacovi, et al. ∙

research

∙ 04/28/2023

NLNDE at SemEval-2023 Task 12: Adaptive Pretraining and Source Language Selection for Low-Resource Multilingual Sentiment Analysis

This paper describes our system developed for the SemEval-2023 Task 12 "...

0 Mingyang Wang, et al. ∙

research

∙ 02/14/2023

SwitchPrompt: Learning Domain-Specific Gated Soft Prompts for Classification in Low-Resource Domains

Prompting pre-trained language models leads to promising results across ...

0 Koustava Goswami, et al. ∙

research

∙ 10/13/2022

How (Not) To Evaluate Explanation Quality

The importance of explainability is increasingly acknowledged in natural...

0 Hendrik Schuff, et al. ∙

research

∙ 05/20/2022

Multilingual Normalization of Temporal Expressions with Masked Language Models

The detection and normalization of temporal expressions is an important ...

0 Lukas Lange, et al. ∙

research

∙ 01/27/2022

Human Interpretation of Saliency-based Explanation Over Text

While a lot of research in explainable AI focuses on producing effective...

14 Hendrik Schuff, et al. ∙

research

∙ 12/16/2021

CLIN-X: pre-trained language models and a study on cross-task transfer for concept extraction in the clinical domain

The field of natural language processing (NLP) has recently seen a large...

0 Lukas Lange, et al. ∙

research

∙ 09/17/2021

Boosting Transformers for Job Expression Extraction and Classification in a Low-Resource Setting

In this paper, we explore possible improvements of transformer models in...

0 Lukas Lange, et al. ∙

research

∙ 09/16/2021

Does External Knowledge Help Explainable Natural Language Inference? Automatic Evaluation vs. Human Ratings

Natural language inference (NLI) requires models to learn and apply comm...

0 Hendrik Schuff, et al. ∙

research

∙ 07/26/2021

Thought Flow Nets: From Single Predictions to Trains of Model Thought

When humans solve complex problems, they rarely come up with a decision ...

0 Hendrik Schuff, et al. ∙

research

∙ 04/22/2021

Enriched Attention for Robust Relation Extraction

The performance of relation extraction models has increased considerably...

0 Heike Adel, et al. ∙

research

∙ 04/16/2021

To Share or not to Share: Predicting Sets of Sources for Model Transfer Learning

In low-resource settings, model transfer can help to overcome a lack of ...

0 Lukas Lange, et al. ∙

research

∙ 10/23/2020

NLNDE at CANTEMIST: Neural Sequence Labeling and Parsing Approaches for Clinical Concept Extraction

The recognition and normalization of clinical information, such as tumor...

0 Lukas Lange, et al. ∙

research

∙ 10/23/2020

A Survey on Recent Approaches for Natural Language Processing in Low-Resource Scenarios

Current developments in natural language processing offer challenges and...

0 Michael A. Hedderich, et al. ∙

research

∙ 10/23/2020

Adversarial Learning of Feature-based Meta-Embeddings

Certain embedding types outperform others in different scenarios, e.g., ...

0 Lukas Lange, et al. ∙

research

∙ 10/22/2020

An Analysis of Simple Data Augmentation for Named Entity Recognition

Simple yet effective data augmentation techniques have been proposed for...

0 Xiang Dai, et al. ∙

research

∙ 10/13/2020

F1 is Not Enough! Models and Evaluation Towards User-Centered Explainable Question Answering

Explainable question answering systems predict an answer together with a...

0 Hendrik Schuff, et al. ∙

research

∙ 07/02/2020

NLNDE: The Neither-Language-Nor-Domain-Experts' Way of Spanish Medical Document De-Identification

Natural language processing has huge potential in the medical domain whi...

0 Lukas Lange, et al. ∙

research

∙ 07/02/2020

NLNDE: Enhancing Neural Sequence Taggers with Attention and Noisy Channel for Robust Pharmacological Entity Detection

Named entity recognition has been extensively studied on English news te...

0 Lukas Lange, et al. ∙

research

∙ 06/04/2020

The SOFC-Exp Corpus and Neural Approaches to Information Extraction in the Materials Science Domain

This paper presents a new challenging information extraction task in the...

0 Annemarie Friedrich, et al. ∙

research

∙ 05/19/2020

Closing the Gap: Joint De-Identification and Concept Extraction in the Clinical Domain

Exploiting natural language processing in the clinical domain requires d...

0 Lukas Lange, et al. ∙

research

∙ 05/19/2020

Adversarial Alignment of Multilingual Models for Extracting Temporal Expressions from Text

Although temporal tagging is still dominated by rule-based systems, ther...

0 Lukas Lange, et al. ∙

research

∙ 05/19/2020

On the Choice of Auxiliary Languages for Improved Sequence Tagging

Recent work showed that embeddings from related languages can improve th...

0 Lukas Lange, et al. ∙

research

∙ 10/01/2019

Type-aware Convolutional Neural Networks for Slot Filling

The slot filling task aims at extracting answers for queries about entit...

0 Heike Adel, et al. ∙

research

∙ 02/28/2019

Adversarial Training for Satire Detection: Controlling for Confounding Variables

The automatic detection of satire vs. regular news is relevant for downs...

0 Robert McHardy, et al. ∙

research

∙ 11/06/2018

CIS at TAC Cold Start 2015: Neural Networks and Coreference Resolution for Slot Filling

This paper describes the CIS slot filling system for the TAC Cold Start ...

0 Heike Adel, et al. ∙

research

∙ 08/14/2018

Adversarial Neural Networks for Cross-lingual Sequence Tagging

We study cross-lingual sequence tagging with little or no labeled data i...

0 Heike Adel, et al. ∙

research

∙ 08/13/2018

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

Character-level models of tokens have been shown to be effective at deal...

0 Apostolos Kemos, et al. ∙

research

∙ 10/26/2017

Impact of Coreference Resolution on Slot Filling

In this paper, we demonstrate the importance of coreference resolution f...

0 Heike Adel, et al. ∙

research

∙ 10/04/2017

Syntactic and Semantic Features For Code-Switching Factored Language Models

This paper presents our latest investigations on different features for ...

0 Heike Adel, et al. ∙

research

∙ 08/07/2017

Corpus-level Fine-grained Entity Typing

This paper addresses the problem of corpus-level entity typing, i.e., in...

0 Yadollah Yaghoobzadeh, et al. ∙

research

∙ 07/24/2017

Global Normalization of Convolutional Neural Networks for Joint Entity and Relation Classification

We introduce globally normalized convolutional neural networks for joint...

0 Heike Adel, et al. ∙

research

∙ 12/22/2016

Noise Mitigation for Neural Entity Typing and Relation Extraction

In this paper, we address two different types of noise in information ex...

0 Yadollah Yaghoobzadeh, et al. ∙

research

∙ 12/20/2016

Exploring Different Dimensions of Attention for Uncertainty Detection

Neural networks with attention have proven effective for many natural la...

0 Heike Adel, et al. ∙

research

∙ 10/03/2016

Nonsymbolic Text Representation

We introduce the first generic text representation model that is complet...

0 Hinrich Schuetze, et al. ∙

research

∙ 05/24/2016

Combining Recurrent and Convolutional Neural Networks for Relation Classification

This paper investigates two different neural architectures for the task ...

0 Ngoc Thang Vu, et al. ∙

research

∙ 03/16/2016

Comparing Convolutional Neural Networks to Traditional Models for Slot Filling

We address relation classification in the context of slot filling, the t...

0 Heike Adel, et al. ∙

Heike Adel

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