2 citations · 5 across the 4 of their papers we have counts for
4 papers
Harnessing Test-time Adaptation for NLU tasks Involving Dialects of English
Duke Nguyen, Aditya Joshi, Flora Salim
Test-time domain adaptation (TTDA) is an excellent method which helps generalize models across domains, tasks, and distributions without the use of labeled datasets. Thus, TTDA is…
"Is Hate Lost in Translation?": Evaluation of Multilingual LGBTQIA+ Hate Speech Detection
Fai Leui Chan, Duke Nguyen, Aditya Joshi
This paper explores the challenges of detecting LGBTQIA+ hate speech of large language models across multiple languages, including English, Italian, Chinese and (code-switched) Eng…
Spectraformer: A Unified Random Feature Framework for Transformer
Duke Nguyen, Du Yin, Aditya Joshi +1
Linearization of attention using various kernel approximation and kernel learning techniques has shown promise. Past methods used a subset of combinations of component functions an…
Stacking the Odds: Transformer-Based Ensemble for AI-Generated Text Detection
Duke Nguyen, Khaing Myat Noe Naing, Aditya Joshi
This paper reports our submission under the team name `SynthDetectives' to the ALTA 2023 Shared Task. We use a stacking ensemble of Transformers for the task of AI-generated text d…