42 citations · 110 across the 36 of their papers we have counts for
7 papers · 1 filter
AugCSE: Contrastive Sentence Embedding with Diverse Augmentations
Zilu Tang, Muhammed Yusuf Kocyigit, Derry Wijaya
Data augmentation techniques have been proven useful in many applications in NLP fields. Most augmentations are task-specific, and cannot be used as a general-purpose tool. In our…
Knowledge Based Template Machine Translation In Low-Resource Setting
Zilu Tang, Derry Wijaya
Incorporating tagging into neural machine translation (NMT) systems has shown promising results in helping translate rare words such as named entities (NE). However, translating NE…
On Measuring Social Biases in Prompt-Based Multi-Task Learning
Afra Feyza Akyürek, Sejin Paik, Muhammed Yusuf Kocyigit +3
Large language models trained on a mixture of NLP tasks that are converted into a text-to-text format using prompts, can generalize into novel forms of language and handle novel ta…
Challenges in Measuring Bias via Open-Ended Language Generation
Afra Feyza Akyürek, Muhammed Yusuf Kocyigit, Sejin Paik +1
Researchers have devised numerous ways to quantify social biases vested in pretrained language models. As some language models are capable of generating coherent completions given…
Referring Expressions with Rational Speech Act Framework: A Probabilistic Approach
Hieu Le, Taufiq Daryanto, Fabian Zhafransyah +3
This paper focuses on a referring expression generation (REG) task in which the aim is to pick out an object in a complex visual scene. One common theoretical approach to this prob…
Creating Multimedia Summaries Using Tweets and Videos
Anietie Andy, Siyi Liu, Daphne Ippolito +3
While popular televised events such as presidential debates or TV shows are airing, people provide commentary on them in real-time. In this paper, we propose a simple yet effective…
Better Quality Estimation for Low Resource Corpus Mining
Muhammed Yusuf Kocyigit, Jiho Lee, Derry Wijaya
Quality Estimation (QE) models have the potential to change how we evaluate and maybe even train machine translation models. However, these models still lack the robustness to achi…