5 citations · 15 across the 8 of their papers we have counts for
8 papers
SemRel2024: A Collection of Semantic Textual Relatedness Datasets for 13 Languages
Nedjma Ousidhoum, Shamsuddeen Hassan Muhammad, Mohamed Abdalla +24
Exploring and quantifying semantic relatedness is central to representing language and holds significant implications across various NLP tasks. While earlier NLP research primarily…
DBLP-QuAD: A Question Answering Dataset over the DBLP Scholarly Knowledge Graph
Debayan Banerjee, Sushil Awale, Ricardo Usbeck +1
In this work we create a question answering dataset over the DBLP scholarly knowledge graph (KG). DBLP is an on-line reference for bibliographic information on major computer scien…
A System for Human-AI collaboration for Online Customer Support
Debayan Banerjee, Mathis Poser, Christina Wiethof +4
AI enabled chat bots have recently been put to use to answer customer service queries, however it is a common feedback of users that bots lack a personal touch and are often unable…
ARDIAS: AI-Enhanced Research Management, Discovery, and Advisory System
Debayan Banerjee, Seid Muhie Yimam, Sushil Awale +1
In this work, we present ARDIAS, a web-based application that aims to provide researchers with a full suite of discovery and collaboration tools. ARDIAS currently allows searching…
How Hateful are Movies? A Study and Prediction on Movie Subtitles
Niklas von Boguszewski, Sana Moin, Anirban Bhowmick +2
In this research, we investigate techniques to detect hate speech in movies. We introduce a new dataset collected from the subtitles of six movies, where each utterance is annotate…
Improving Unsupervised Sparsespeech Acoustic Models with Categorical Reparameterization
Benjamin Milde, Chris Biemann
The Sparsespeech model is an unsupervised acoustic model that can generate discrete pseudo-labels for untranscribed speech. We extend the Sparsespeech model to allow for sampling o…
UHH-LT at SemEval-2020 Task 12: Fine-Tuning of Pre-Trained Transformer Networks for Offensive Language Detection
Gregor Wiedemann, Seid Muhie Yimam, Chris Biemann
Fine-tuning of pre-trained transformer networks such as BERT yield state-of-the-art results for text classification tasks. Typically, fine-tuning is performed on task-specific trai…
Word Sense Disambiguation for 158 Languages using Word Embeddings Only
Varvara Logacheva, Denis Teslenko, Artem Shelmanov +7
Disambiguation of word senses in context is easy for humans, but is a major challenge for automatic approaches. Sophisticated supervised and knowledge-based models were developed t…