activity
20132023
most citedComparative Study of CNN and RNN for Natural Language Processing

895 citations · 932 across the 34 of their papers we have counts for

collaborators

109 papers

cs.CL2023

Multilingual Word Embeddings for Low-Resource Languages using Anchors and a Chain of Related Languages

Viktor Hangya, Silvia Severini, Radoslav Ralev +2

Very low-resource languages, having only a few million tokens worth of data, are not well-supported by multilingual NLP approaches due to poor quality cross-lingual word representa…

cs.CL20221 cited

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…

cs.CL2022

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…

cs.CL20223 cited

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…

cs.CL2022

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…

cs.CL20221 cited

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…