4 citations · 9 across the 6 of their papers we have counts for
6 papers
StockMem: An Event-Reflection Memory Framework for Stock Forecasting
He Wang, Wenyilin Xiao, Songqiao Han +1
Stock price prediction is challenging due to market volatility and its sensitivity to real-time events. While large language models (LLMs) offer new avenues for text-based forecast…
TSGym: Design Choices for Deep Multivariate Time-Series Forecasting
Shuang Liang, Chaochuan Hou, Xu Yao +4
Recently, deep learning has driven significant advancements in multivariate time series forecasting (MTSF) tasks. However, much of the current research in MTSF tends to evaluate mo…
GENIUS: Sketch-based Language Model Pre-training via Extreme and Selective Masking for Text Generation and Augmentation
Biyang Guo, Yeyun Gong, Yelong Shen +4
We introduce GENIUS: a conditional text generation model using sketches as input, which can fill in the missing contexts for a given sketch (key information consisting of textual s…
IDEA: Interactive DoublE Attentions from Label Embedding for Text Classification
Ziyuan Wang, Hailiang Huang, Songqiao Han
Current text classification methods typically encode the text merely into embedding before a naive or complicated classifier, which ignores the suggestive information contained in…
American Hate Crime Trends Prediction with Event Extraction
Songqiao Han, Hailiang Huang, Jiangwei Liu +1
Social media platforms may provide potential space for discourses that contain hate speech, and even worse, can act as a propagation mechanism for hate crimes. The FBI's Uniform Cr…
Label Confusion Learning to Enhance Text Classification Models
Biyang Guo, Songqiao Han, Xiao Han +2
Representing a true label as a one-hot vector is a common practice in training text classification models. However, the one-hot representation may not adequately reflect the relati…