b'Chris Biemann'

research

∙ 09/14/2023

DBLPLink: An Entity Linker for the DBLP Scholarly Knowledge Graph

In this work, we present a web application named DBLPLink, which perform...

0 Debayan Banerjee, et al. ∙

research

∙ 05/24/2023

The Role of Output Vocabulary in T2T LMs for SPARQL Semantic Parsing

In this work, we analyse the role of output vocabulary for text-to-text ...

0 Debayan Banerjee, et al. ∙

research

∙ 03/23/2023

DBLP-QuAD: A Question Answering Dataset over the DBLP Scholarly Knowledge Graph

In this work we create a question answering dataset over the DBLP schola...

0 Debayan Banerjee, et al. ∙

research

∙ 03/23/2023

GETT-QA: Graph Embedding based T2T Transformer for Knowledge Graph Question Answering

In this work, we present an end-to-end Knowledge Graph Question Answerin...

0 Debayan Banerjee, et al. ∙

research

∙ 01/28/2023

A system for Human-AI collaboration for Online Customer Support

AI enabled chat bots have recently been put to use to answer customer se...

0 Debayan Banerjee, et al. ∙

research

∙ 01/25/2023

ARDIAS: AI-Enhanced Research Management, Discovery, and Advisory System

In this work, we present ARDIAS, a web-based application that aims to pr...

0 Debayan Banerjee, et al. ∙

research

∙ 04/27/2022

Modern Baselines for SPARQL Semantic Parsing

In this work, we focus on the task of generating SPARQL queries from nat...

0 Debayan Banerjee, et al. ∙

research

∙ 03/18/2022

SCoT: Sense Clustering over Time: a tool for the analysis of lexical change

We present Sense Clustering over Time (SCoT), a novel network-based tool...

0 Christian Haase, et al. ∙

research

∙ 02/02/2022

Language Models Explain Word Reading Times Better Than Empirical Predictability

Though there is a strong consensus that word length and frequency are th...

0 Markus J. Hofmann, et al. ∙

research

∙ 08/19/2021

How Hateful are Movies? A Study and Prediction on Movie Subtitles

In this research, we investigate techniques to detect hate speech in mov...

0 Niklas von Boguszewski, et al. ∙

research

∙ 12/18/2020

HateXplain: A Benchmark Dataset for Explainable Hate Speech Detection

Hate speech is a challenging issue plaguing the online social media. Whi...

0 Binny Mathew, et al. ∙

research

∙ 12/08/2020

Social Media Unrest Prediction during the COVID-19 Pandemic: Neural Implicit Motive Pattern Recognition as Psychometric Signs of Severe Crises

The COVID-19 pandemic has caused international social tension and unrest...

0 Dirk Johannßen, et al. ∙

research

∙ 11/02/2020

Introducing various Semantic Models for Amharic: Experimentation and Evaluation with multiple Tasks and Datasets

The availability of different pre-trained semantic models enabled the qu...

0 Seid Muhie Yimam, et al. ∙

research

∙ 10/20/2020

Individual corpora predict fast memory retrieval during reading

The corpus, from which a predictive language model is trained, can be co...

0 Markus J. Hofmann, et al. ∙

research

∙ 05/31/2020

Neural Entity Linking: A Survey of Models based on Deep Learning

In this survey, we provide a comprehensive description of recent neural ...

0 Ozge Sevgili, et al. ∙

research

∙ 05/29/2020

Improving Unsupervised Sparsespeech Acoustic Models with Categorical Reparameterization

The Sparsespeech model is an unsupervised acoustic model that can genera...

0 Benjamin Milde, et al. ∙

research

∙ 04/23/2020

UHH-LT LT2 at SemEval-2020 Task 12: Fine-Tuning of Pre-Trained Transformer Networks for Offensive Language Detection

Fine-tuning of pre-trained transformer networks such as BERT yield state...

0 Gregor Wiedemann, et al. ∙

research

∙ 03/14/2020

Word Sense Disambiguation for 158 Languages using Word Embeddings Only

Disambiguation of word senses in context is easy for humans, but is a ma...

0 Varvara Logacheva, et al. ∙

research

∙ 03/05/2020

Automatic Compilation of Resources for Academic Writing and Evaluating with Informal Word Identification and Paraphrasing System

We present the first approach to automatically building resources for ac...

0 Seid Muhie Yimam, et al. ∙

research

∙ 12/09/2019

Analysis of the Ethiopic Twitter Dataset for Abusive Speech in Amharic

In this paper, we present an analysis of the first Ethiopic Twitter Data...

0 Seid Muhie Yimam, et al. ∙

research

∙ 09/23/2019

Does BERT Make Any Sense? Interpretable Word Sense Disambiguation with Contextualized Embeddings

Contextualized word embeddings (CWE) such as provided by ELMo (Peters et...

0 Gregor Wiedemann, et al. ∙

research

∙ 06/17/2019

Making Fast Graph-based Algorithms with Graph Metric Embeddings

The computation of distance measures between nodes in graphs is ineffici...

0 Andrey Kutuzov, et al. ∙

research

∙ 06/12/2019

Adversarial Learning of Privacy-Preserving Text Representations for De-Identification of Medical Records

De-identification is the task of detecting protected health information ...

0 Max Friedrich, et al. ∙

research

∙ 06/07/2019

On the Compositionality Prediction of Noun Phrases using Poincaré Embeddings

The compositionality degree of multiword expressions indicates to what e...

0 Abhik Jana, et al. ∙

research

∙ 06/05/2019

Every child should have parents: a taxonomy refinement algorithm based on hyperbolic term embeddings

We introduce the use of Poincaré embeddings to improve existing state-of...

0 Rami Aly, et al. ∙

research

∙ 05/05/2019

HHMM at SemEval-2019 Task 2: Unsupervised Frame Induction using Contextualized Word Embeddings

We present our system for semantic frame induction that showed the best ...

0 Saba Anwar, et al. ∙

research

∙ 01/15/2019

Answering Comparative Questions: Better than Ten-Blue-Links?

We present CAM (comparative argumentative machine), a novel open-domain ...

0 Matthias Schildwächter, et al. ∙

research

∙ 11/07/2018

Transfer Learning from LDA to BiLSTM-CNN for Offensive Language Detection in Twitter

We investigate different strategies for automatic offensive language cla...

0 Gregor Wiedemann, et al. ∙

research

∙ 11/07/2018

microNER: A Micro-Service for German Named Entity Recognition based on BiLSTM-CRF

For named entity recognition (NER), bidirectional recurrent neural netwo...

0 Gregor Wiedemann, et al. ∙

research

∙ 09/17/2018

Unsupervised Sense-Aware Hypernymy Extraction

In this paper, we show how unsupervised sense representations can be use...

0 Dmitry Ustalov, et al. ∙

research

∙ 09/17/2018

Categorization of Comparative Sentences for Argument Mining

We present the first work on domain-independent comparative argument min...

0 Mirco Franzek, et al. ∙

research

∙ 09/01/2018

A Multilingual Information Extraction Pipeline for Investigative Journalism

We introduce an advanced information extraction pipeline to automaticall...

0 Gregor Wiedemann, et al. ∙

research

∙ 08/21/2018

Demonstrating PAR4SEM - A Semantic Writing Aid with Adaptive Paraphrasing

In this paper, we present Par4Sem, a semantic writing aid tool based on ...

0 Seid Muhie Yimam, et al. ∙

research

∙ 08/20/2018

Local-Global Graph Clustering with Applications in Sense and Frame Induction

We present Watset, a new meta-algorithm for fuzzy graph clustering. This...

0 Dmitry Ustalov, et al. ∙

research

∙ 08/16/2018

Learning Graph Embeddings from WordNet-based Similarity Measures

We present a new approach for learning graph embeddings, that relies on ...

0 Andrey Kutuzov, et al. ∙

research

∙ 07/13/2018

New/s/leak 2.0 - Multilingual Information Extraction and Visualization for Investigative Journalism

Investigative journalism in recent years is confronted with two major ch...

0 Gregor Wiedemann, et al. ∙

research

∙ 06/21/2018

Par4Sim -- Adaptive Paraphrasing for Text Simplification

Learning from a real-world data stream and continuously updating the mod...

0 Seid Muhie Yimam, et al. ∙

research

∙ 05/12/2018

Unsupervised Semantic Frame Induction using Triclustering

We use dependency triples automatically extracted from a Web-scale corpu...

0 Dmitry Ustalov, et al. ∙

research

∙ 04/30/2018

BomJi at SemEval-2018 Task 10: Combining Vector-, Pattern- and Graph-based Information to Identify Discriminative Attributes

This paper describes BomJi, a supervised system for capturing discrimina...

0 Enrico Santus, et al. ∙

research

∙ 04/27/2018

An Unsupervised Word Sense Disambiguation System for Under-Resourced Languages

In this paper, we present Watasense, an unsupervised system for word sen...

0 Dmitry Ustalov, et al. ∙

research

∙ 04/24/2018

A Report on the Complex Word Identification Shared Task 2018

We report the findings of the second Complex Word Identification (CWI) s...

0 Seid Muhie Yimam, et al. ∙

research

∙ 04/18/2018

Unspeech: Unsupervised Speech Context Embeddings

We introduce "Unspeech" embeddings, which are based on unsupervised lear...

0 Benjamin Milde, et al. ∙

research

∙ 03/15/2018

Enriching Frame Representations with Distributionally Induced Senses

We introduce a new lexical resource that enriches the Framester knowledg...

0 Stefano Faralli, et al. ∙

research

∙ 12/28/2017

What do we need to build explainable AI systems for the medical domain?

Artificial intelligence (AI) generally and machine learning (ML) specifi...

0 Andreas Holzinger, et al. ∙

research

∙ 12/23/2017

A Framework for Enriching Lexical Semantic Resources with Distributional Semantics

We present an approach to combining distributional semantic representati...

0 Chris Biemann, et al. ∙

research

∙ 11/08/2017

Improving Hypernymy Extraction with Distributional Semantic Classes

In this paper, we show for the first time how distributionally-induced s...

0 Alexander Panchenko, et al. ∙

research

∙ 10/04/2017

Building a Web-Scale Dependency-Parsed Corpus from CommonCrawl

We present DepCC, the largest to date linguistically analyzed corpus in ...

0 Alexander Panchenko, et al. ∙

research

∙ 08/31/2017

Human and Machine Judgements for Russian Semantic Relatedness

Semantic relatedness of terms represents similarity of meaning by a nume...

0 Alexander Panchenko, et al. ∙

research

∙ 08/30/2017

Fighting with the Sparsity of Synonymy Dictionaries

Graph-based synset induction methods, such as MaxMax and Watset, induce ...

0 Dmitry Ustalov, et al. ∙

research

∙ 08/10/2017

Making Sense of Word Embeddings

We present a simple yet effective approach for learning word sense embed...

0 Maria Pelevina, et al. ∙

Chris Biemann

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