3 papers
cs.LG2025
Ignite Forecasting with SPARK: An Efficient Generative Framework for Refining LLMs in Temporal Knowledge Graph Forecasting
Gongzhu Yin, Hongli Zhang, Yi Luo +3
Temporal Knowledge Graph (TKG) forecasting is crucial for predicting future events using historical data. With the surge of Large Language Models (LLMs), recent studies have begun…
cs.CV2023
A Sea-Land Clutter Classification Framework for Over-the-Horizon-Radar Based on Weighted Loss Semi-supervised GAN
Xiaoxuan Zhang, Zengfu Wang, Kun Lu +2
Deep convolutional neural network has made great achievements in sea-land clutter classification for over-the-horizon-radar (OTHR). The premise is that a large number of labeled tr…
cs.CV2022
Contrastive Monotonic Pixel-Level Modulation
Kun Lu, Rongpeng Li, Honggang Zhang
Continuous one-to-many mapping is a less investigated yet important task in both low-level visions and neural image translation. In this paper, we present a new formulation called…