895 citations · 2.1k across the 169 of their papers we have counts for
18 papers · 1 filter
Unsupervised Detection of Contextualized Embedding Bias with Application to Ideology
Valentin Hofmann, Janet B. Pierrehumbert, Hinrich Schütze
We propose a fully unsupervised method to detect bias in contextualized embeddings. The method leverages the assortative information latently encoded by social networks and combine…
Cross-Lingual Retrieval Augmented Prompt for Low-Resource Languages
Ercong Nie, Sheng Liang, Helmut Schmid +1
Multilingual Pretrained Language Models (MPLMs) have shown their strong multilinguality in recent empirical cross-lingual transfer studies. In this paper, we propose the Prompts Au…
Graph-Based Multilingual Label Propagation for Low-Resource Part-of-Speech Tagging
Ayyoob Imani, Silvia Severini, Masoud Jalili Sabet +2
Part-of-Speech (POS) tagging is an important component of the NLP pipeline, but many low-resource languages lack labeled data for training. An established method for training a POS…
This joke is [MASK]: Recognizing Humor and Offense with Prompting
Junze Li, Mengjie Zhao, Yubo Xie +3
Humor is a magnetic component in everyday human interactions and communications. Computationally modeling humor enables NLP systems to entertain and engage with users. We investiga…
The Better Your Syntax, the Better Your Semantics? Probing Pretrained Language Models for the English Comparative Correlative
Leonie Weissweiler, Valentin Hofmann, Abdullatif Köksal +1
Construction Grammar (CxG) is a paradigm from cognitive linguistics emphasising the connection between syntax and semantics. Rather than rules that operate on lexical items, it pos…
SilverAlign: MT-Based Silver Data Algorithm For Evaluating Word Alignment
Abdullatif Köksal, Silvia Severini, Hinrich Schütze
Word alignments are essential for a variety of NLP tasks. Therefore, choosing the best approaches for their creation is crucial. However, the scarce availability of gold evaluation…
Modeling Content-Emotion Duality via Disentanglement for Empathetic Conversation
Peiqin Lin, Jiashuo Wang, Hinrich Schütze +1
The task of empathetic response generation aims to understand what feelings a speaker expresses on his/her experiences and then reply to the speaker appropriately. To solve the tas…
Don't Forget Cheap Training Signals Before Building Unsupervised Bilingual Word Embeddings
Silvia Severini, Viktor Hangya, Masoud Jalili Sabet +2
Bilingual Word Embeddings (BWEs) are one of the cornerstones of cross-lingual transfer of NLP models. They can be built using only monolingual corpora without supervision leading t…
Analyzing Hate Speech Data along Racial, Gender and Intersectional Axes
Antonis Maronikolakis, Philip Baader, Hinrich Schütze
To tackle the rising phenomenon of hate speech, efforts have been made towards data curation and analysis. When it comes to analysis of bias, previous work has focused predominantl…
Differentiable Multi-Agent Actor-Critic for Multi-Step Radiology Report Summarization
Sanjeev Kumar Karn, Ning Liu, Hinrich Schuetze +1
The IMPRESSIONS section of a radiology report about an imaging study is a summary of the radiologist's reasoning and conclusions, and it also aids the referring physician in confir…
Flow-Adapter Architecture for Unsupervised Machine Translation
Yihong Liu, Haris Jabbar, Hinrich Schütze
In this work, we propose a flow-adapter architecture for unsupervised NMT. It leverages normalizing flows to explicitly model the distributions of sentence-level latent representat…
CaMEL: Case Marker Extraction without Labels
Leonie Weissweiler, Valentin Hofmann, Masoud Jalili Sabet +1
We introduce CaMEL (Case Marker Extraction without Labels), a novel and challenging task in computational morphology that is especially relevant for low-resource languages. We prop…
Listening to Affected Communities to Define Extreme Speech: Dataset and Experiments
Antonis Maronikolakis, Axel Wisiorek, Leah Nann +3
Building on current work on multilingual hate speech (e.g., Ousidhoum et al. (2019)) and hate speech reduction (e.g., Sap et al. (2020)), we present XTREMESPEECH, a new hate speech…
Modular and Parameter-Efficient Multimodal Fusion with Prompting
Sheng Liang, Mengjie Zhao, Hinrich Schütze
Recent research has made impressive progress in large-scale multimodal pre-training. In the context of the rapid growth of model size, it is necessary to seek efficient and flexibl…
CoDA21: Evaluating Language Understanding Capabilities of NLP Models With Context-Definition Alignment
Lütfi Kerem Senel, Timo Schick, Hinrich Schütze
Pretrained language models (PLMs) have achieved superhuman performance on many benchmarks, creating a need for harder tasks. We introduce CoDA21 (Context Definition Alignment), a c…
ECOLA: Enhanced Temporal Knowledge Embeddings with Contextualized Language Representations
Zhen Han, Ruotong Liao, Jindong Gu +6
Since conventional knowledge embedding models cannot take full advantage of the abundant textual information, there have been extensive research efforts in enhancing knowledge embe…
Semantic-Oriented Unlabeled Priming for Large-Scale Language Models
Yanchen Liu, Timo Schick, Hinrich Schütze
Due to the high costs associated with finetuning large language models, various recent works propose to adapt them to specific tasks without any parameter updates through in-contex…
Towards a Broad Coverage Named Entity Resource: A Data-Efficient Approach for Many Diverse Languages
Silvia Severini, Ayyoob Imani, Philipp Dufter +1
Parallel corpora are ideal for extracting a multilingual named entity (MNE) resource, i.e., a dataset of names translated into multiple languages. Prior work on extracting MNE data…