Search Results for author: Songqiao Han

Found 8 papers, 5 papers with code

Weakly Supervised Anomaly Detection: A Survey

1 code implementation9 Feb 2023 Minqi Jiang, Chaochuan Hou, Ao Zheng, Xiyang Hu, Songqiao Han, Hailiang Huang, Xiangnan He, Philip S. Yu, Yue Zhao

Anomaly detection (AD) is a crucial task in machine learning with various applications, such as detecting emerging diseases, identifying financial frauds, and detecting fake news.

supervised anomaly detection Time Series Analysis

GENIUS: Sketch-based Language Model Pre-training via Extreme and Selective Masking for Text Generation and Augmentation

2 code implementations18 Nov 2022 Biyang Guo, Yeyun Gong, Yelong Shen, Songqiao Han, Hailiang Huang, Nan Duan, Weizhu Chen

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 spans, phrases, or words, concatenated by mask tokens).

Conditional Text Generation Data Augmentation +8

IDEA: Interactive DoublE Attentions from Label Embedding for Text Classification

no code implementations23 Sep 2022 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 the label text.

text-classification Text Classification

Selective Text Augmentation with Word Roles for Low-Resource Text Classification

1 code implementation4 Sep 2022 Biyang Guo, Songqiao Han, Hailiang Huang

Different words may play different roles in text classification, which inspires us to strategically select the proper roles for text augmentation.

Language Modelling Semantic Similarity +4

ADBench: Anomaly Detection Benchmark

2 code implementations19 Jun 2022 Songqiao Han, Xiyang Hu, Hailiang Huang, Mingqi Jiang, Yue Zhao

Given a long list of anomaly detection algorithms developed in the last few decades, how do they perform with regard to (i) varying levels of supervision, (ii) different types of anomalies, and (iii) noisy and corrupted data?

Anomaly Detection Outlier Detection

American Hate Crime Trends Prediction with Event Extraction

no code implementations9 Nov 2021 Songqiao Han, Hailiang Huang, Jiangwei Liu, Shengsheng Xiao

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.

Event Extraction Hate Speech Detection +1

Neural News Recommendation with Event Extraction

no code implementations9 Nov 2021 Songqiao Han, Hailiang Huang, Jiangwei Liu

These methods encode news content on the word level and jointly train the attention parameters in the recommendation network, leading to more corpora being required to train the model.

Event Extraction News Recommendation

Label Confusion Learning to Enhance Text Classification Models

1 code implementation9 Dec 2020 Biyang Guo, Songqiao Han, Xiao Han, Hailiang Huang, Ting Lu

LCM can learn label confusion to capture semantic overlap among labels by calculating the similarity between instances and labels during training and generate a better label distribution to replace the original one-hot label vector, thus improving the final classification performance.

General Classification text-classification +1

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