17 citations · 71 across the 24 of their papers we have counts for
4 papers · 1 filter
GradSim: Gradient-Based Language Grouping for Effective Multilingual Training
Mingyang Wang, Heike Adel, Lukas Lange +2
Most languages of the world pose low-resource challenges to natural language processing models. With multilingual training, knowledge can be shared among languages. However, not al…
TADA: Efficient Task-Agnostic Domain Adaptation for Transformers
Chia-Chien Hung, Lukas Lange, Jannik Strötgen
Intermediate training of pre-trained transformer-based language models on domain-specific data leads to substantial gains for downstream tasks. To increase efficiency and prevent c…
NLNDE at SemEval-2023 Task 12: Adaptive Pretraining and Source Language Selection for Low-Resource Multilingual Sentiment Analysis
Mingyang Wang, Heike Adel, Lukas Lange +2
This paper describes our system developed for the SemEval-2023 Task 12 "Sentiment Analysis for Low-resource African Languages using Twitter Dataset". Sentiment analysis is one of t…
SwitchPrompt: Learning Domain-Specific Gated Soft Prompts for Classification in Low-Resource Domains
Koustava Goswami, Lukas Lange, Jun Araki +1
Prompting pre-trained language models leads to promising results across natural language processing tasks but is less effective when applied in low-resource domains, due to the dom…