1 citations · 3 across the 11 of their papers we have counts for
12 papers · 1 filter
AuthorMix: Modular Authorship Style Transfer via Layer-wise Adapter Mixing
Sarubi Thillainathan, Ji-Ung Lee, Michael Sullivan +1
The task of authorship style transfer involves rewriting text in the style of a target author while preserving the meaning of the original text. Existing style transfer methods tra…
Bridging Fairness and Explainability: Can Input-Based Explanations Promote Fairness in Hate Speech Detection?
Yifan Wang, Mayank Jobanputra, Ji-Ung Lee +3
Natural language processing (NLP) models often replicate or amplify social bias from training data, raising concerns about fairness. At the same time, their black-box nature makes…
B-cos LM: Efficiently Transforming Pre-trained Language Models for Improved Explainability
Yifan Wang, Sukrut Rao, Ji-Ung Lee +2
Post-hoc explanation methods for black-box models often struggle with faithfulness and human interpretability due to the lack of explainability in current neural architectures. Mea…
Constrained C-Test Generation via Mixed-Integer Programming
Ji-Ung Lee, Marc E. Pfetsch, Iryna Gurevych
This work proposes a novel method to generate C-Tests; a deviated form of cloze tests (a gap filling exercise) where only the last part of a word is turned into a gap. In contrast…
Surveying (Dis)Parities and Concerns of Compute Hungry NLP Research
Ji-Ung Lee, Haritz Puerto, Betty van Aken +8
Many recent improvements in NLP stem from the development and use of large pre-trained language models (PLMs) with billions of parameters. Large model sizes makes computational cos…
Rediscovering Hashed Random Projections for Efficient Quantization of Contextualized Sentence Embeddings
Ulf A. Hamster, Ji-Ung Lee, Alexander Geyken +1
Training and inference on edge devices often requires an efficient setup due to computational limitations. While pre-computing data representations and caching them on a server can…