16 citations · 16 across the 4 of their papers we have counts for
3 papers
cs.CL2023
LMGQS: A Large-scale Dataset for Query-focused Summarization
Ruochen Xu, Song Wang, Yang Liu +5
Query-focused summarization (QFS) aims to extract or generate a summary of an input document that directly answers or is relevant to a given query. The lack of large-scale datasets…
cs.SE2022★ 3 cited
Are We Building on the Rock? On the Importance of Data Preprocessing for Code Summarization
Lin Shi, Fangwen Mu, Xiao Chen +6
Code summarization, the task of generating useful comments given the code, has long been of interest. Most of the existing code summarization models are trained and validated on wi…
cs.CV2021
Style Mixing and Patchwise Prototypical Matching for One-Shot Unsupervised Domain Adaptive Semantic Segmentation
Xinyi Wu, Zhenyao Wu, Yuhang Lu +2
In this paper, we tackle the problem of one-shot unsupervised domain adaptation (OSUDA) for semantic segmentation where the segmentors only see one unlabeled target image during tr…