3 citations · 4 across the 6 of their papers we have counts for
6 papers
Adaptive Detoxification: Safeguarding General Capabilities of LLMs through Toxicity-Aware Knowledge Editing
Yifan Lu, Jing Li, Yigeng Zhou +7
Large language models (LLMs) exhibit impressive language capabilities but remain vulnerable to malicious prompts and jailbreaking attacks. Existing knowledge editing methods for LL…
Handling Imbalanced Pseudolabels for Vision-Language Models with Concept Alignment and Confusion-Aware Calibrated Margin
Yuchen Wang, Xuefeng Bai, Xiucheng Li +3
Adapting vision-language models (VLMs) to downstream tasks with pseudolabels has gained increasing attention. A major obstacle is that the pseudolabels generated by VLMs tend to be…
Spatial-Temporal Cross-View Contrastive Pre-training for Check-in Sequence Representation Learning
Letian Gong, Huaiyu Wan, Shengnan Guo +6
The rapid growth of location-based services (LBS) has yielded massive amounts of data on human mobility. Effectively extracting meaningful representations for user-generated check-…
UrbanLLM: Autonomous Urban Activity Planning and Management with Large Language Models
Yue Jiang, Qin Chao, Yile Chen +3
Location-based services play an critical role in improving the quality of our daily lives. Despite the proliferation of numerous specialized AI models within spatio-temporal contex…
SAGDFN: A Scalable Adaptive Graph Diffusion Forecasting Network for Multivariate Time Series Forecasting
Yue Jiang, Xiucheng Li, Yile Chen +4
Time series forecasting is essential for our daily activities and precise modeling of the complex correlations and shared patterns among multiple time series is essential for impro…
Semantic-Enhanced Representation Learning for Road Networks with Temporal Dynamics
Yile Chen, Xiucheng Li, Gao Cong +2
In this study, we introduce a novel framework called Toast for learning general-purpose representations of road networks, along with its advanced counterpart DyToast, designed to e…