55 citations · 146 across the 18 of their papers we have counts for
18 papers
The Robust Semantic Segmentation UNCV2023 Challenge Results
Xuanlong Yu, Yi Zuo, Zitao Wang +34
This paper outlines the winning solutions employed in addressing the MUAD uncertainty quantification challenge held at ICCV 2023. The challenge was centered around semantic segment…
FIAT: Fusing learning paradigms with Instruction-Accelerated Tuning
Xinyi Wang, John Wieting, Jonathan H. Clark
Learning paradigms for large language models (LLMs) currently tend to fall within either in-context learning (ICL) or full fine-tuning. Each of these comes with their own trade-off…
Multi-model fusion for Aerial Vision and Dialog Navigation based on human attention aids
Xinyi Wang, Xuan Cui, Danxu Li +2
Drones have been widely used in many areas of our daily lives. It relieves people of the burden of holding a controller all the time and makes drone control easier to use for peopl…
Generalizable and explainable prediction of potential miRNA-disease associations based on heterogeneous graph learning
Yi Zhou, Meixuan Wu, Chengzhou Ouyang +1
Biomedical research has revealed the crucial role of miRNAs in the progression of many diseases, and computational prediction methods are increasingly proposed for assisting biolog…
XTREME-UP: A User-Centric Scarce-Data Benchmark for Under-Represented Languages
Sebastian Ruder, Jonathan H. Clark, Alexander Gutkin +24
Data scarcity is a crucial issue for the development of highly multilingual NLP systems. Yet for many under-represented languages (ULs) -- languages for which NLP re-search is part…
mmT5: Modular Multilingual Pre-Training Solves Source Language Hallucinations
Jonas Pfeiffer, Francesco Piccinno, Massimo Nicosia +3
Multilingual sequence-to-sequence models perform poorly with increased language coverage and fail to consistently generate text in the correct target language in few-shot settings.…