activity
20222024
most citedPitfalls in Link Prediction with Graph Neural Networks: Understanding the Impact of Target-link Inclusion & Better Practices

16 citations · 23 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2024★ 1 cited

Mementos: A Comprehensive Benchmark for Multimodal Large Language Model Reasoning over Image Sequences

Xiyao Wang, Yuhang Zhou, Xiaoyu Liu +9

Multimodal Large Language Models (MLLMs) have demonstrated proficiency in handling a variety of visual-language tasks. However, current MLLM benchmarks are predominantly designed t…

cs.CL2023★ 1 cited

Explore Spurious Correlations at the Concept Level in Language Models for Text Classification

Yuhang Zhou, Paiheng Xu, Xiaoyu Liu +3

Language models (LMs) have achieved notable success in numerous NLP tasks, employing both fine-tuning and in-context learning (ICL) methods. While language models demonstrate excep…

cs.CY2023★ 1 cited

Emoji Promotes Developer Participation and Issue Resolution on GitHub

Yuhang Zhou, Xuan Lu, Ge Gao +2

Although remote working is increasingly adopted during the pandemic, many are concerned by the low-efficiency in the remote working. Missing in text-based communication are non-ver…

cs.LG2023★ 16 cited

Pitfalls in Link Prediction with Graph Neural Networks: Understanding the Impact of Target-link Inclusion & Better Practices

Jing Zhu, Yuhang Zhou, Vassilis N. Ioannidis +4

While Graph Neural Networks (GNNs) are remarkably successful in a variety of high-impact applications, we demonstrate that, in link prediction, the common practices of including th…

cs.LG2023★ 2 cited

GFairHint: Improving Individual Fairness for Graph Neural Networks via Fairness Hint

Paiheng Xu, Yuhang Zhou, Bang An +2

Given the growing concerns about fairness in machine learning and the impressive performance of Graph Neural Networks (GNNs) on graph data learning, algorithmic fairness in GNNs ha…

cs.CL2023★ 1 cited

Scalable Prompt Generation for Semi-supervised Learning with Language Models

Yuhang Zhou, Suraj Maharjan, Beiye Liu

Prompt-based learning methods in semi-supervised learning (SSL) settings have been shown to be effective on multiple natural language understanding (NLU) datasets and tasks in the…

cs.CV2022★ 1 cited

When Did It Happen? Duration-informed Temporal Localization of Narrated Actions in Vlogs

Oana Ignat, Santiago Castro, Yuhang Zhou +3

We consider the task of temporal human action localization in lifestyle vlogs. We introduce a novel dataset consisting of manual annotations of temporal localization for 13,000 nar…